Orangemint Technologies Private Limited

Data Scientist – Machine Learning & Applied Analytics. 

Location: Bengaluru 

Experience: 5–8 Years 

Role Type: Full-Time 

Business Unit: Products & Platforms (PMG) 

Role Overview 

We are looking for a Data Scientist – Product Analytics & Machine Learning to help build differentiated analytics and ML capabilities across our product and platform portfolio, including MOBIUS+ and Signate. 

This is a hands-on product-focused role responsible for translating real-world customer and domain problems into scalable analytics and machine learning solutions. The role will work across the complete lifecycle — from data exploration and experimentation through model development, validation, productization and production monitoring. 

The Data Scientist will also work closely with Tata Elxsi's internal analytics teams, specialist solution providers and academic/research institutions to evaluate, integrate and evolve analytical capabilities as part of our products. 

Key Responsibilities 

Product Analytics & ML 

• Translate product and customer problems into well-defined analytics and ML use cases. 
• Perform data exploration, feature engineering, statistical analysis and experimentation. 
• Develop, train, validate and optimize machine learning and predictive models. 
• Define appropriate model performance metrics, benchmarks and acceptance criteria. 
• Convert prototypes and experiments into scalable, production-ready capabilities. 
• Work with Product, Architecture and Engineering teams to integrate models and analytics into SaaS products and platforms. 

Model Evaluation & Productization 

• Evaluate models and analytical solutions developed by internal teams, technology partners and specialist solution providers. 
• Assess model assumptions, data requirements, accuracy, robustness, explainability and limitations. 
• Benchmark alternative models/approaches and provide evidence-based recommendations. 
• Establish practices for model versioning, validation, monitoring, drift detection and continuous improvement. 
• Ensure that externally sourced models can be effectively integrated, governed and evolved within the product. 

Collaboration & Research 

• Collaborate with Tata Elxsi's broader AI, analytics and domain teams and leverage specialist capabilities where required. 
• Work technically with external solution providers to understand and integrate their algorithms and models. 
• Engage with researchers and academic institutions such as IITs, NITs and IISc on advanced analytics and ML opportunities. 
• Evaluate research, algorithms and PoCs and help translate promising approaches into production-grade product capabilities. 
• Build reusable analytical assets, datasets, features, evaluation frameworks and know-how across the product portfolio. 

Technical Skills 

• Strong foundation in statistics, probability, machine learning and data analysis. 
• Strong hands-on programming skills in Python and common data science libraries. 
• Experience with Pandas, NumPy, scikit-learn and relevant ML frameworks. 
• Experience developing predictive models using structured and time-series data. 
• Understanding of supervised/unsupervised learning, anomaly detection, forecasting, classification and regression techniques. 
• Experience with feature engineering, model selection, hyperparameter optimization and model evaluation. 
• Good understanding of model explainability, bias, uncertainty and robustness. 
• Working knowledge of SQL and large-scale data processing. 
• Experience deploying or integrating ML models into production applications through APIs, services or ML pipelines. 
• Understanding of MLOps, including model versioning, experiment tracking, monitoring and model lifecycle management. 
• Experience with cloud environments, preferably AWS, is desirable. 
• Exposure to GenAI/LLMs and their application within product analytics is an advantage. 

Product & Engineering Mindset 

• Ability to move beyond experimentation and think about how analytics becomes a repeatable product capability. 
• Strong problem-solving ability and comfort working with incomplete or imperfect real-world datasets. 
• Ability to distinguish between an interesting analytical result and one that creates measurable customer/product value. 
• Comfortable working closely with Product Managers, Domain SMEs, Architects and Software Engineers. 
• Ability to critically evaluate third-party algorithms and models rather than treating external solutions as black boxes. 
• Strong technical communication skills and ability to explain analytical concepts and model outcomes to both technical and business stakeholders. 

Preferred Experience 

• 5–8 years of relevant experience in Data Science, Machine Learning, Applied Analytics or related roles. 
• Experience building ML/analytics capabilities that have been deployed into production products or platforms. 
• Experience working with automotive, mobility, connected vehicle, battery/EV, IoT or industrial datasets is desirable but not mandatory. 
• Experience collaborating with technology partners, research organizations or academic institutions is an advantage. 
• Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering or a related quantitative discipline preferred. 

What Success Looks Like 

The successful candidate will help PMG establish a strong internal Data Science & ML capability that can build differentiated analytics, intelligently leverage Tata Elxsi's broader capabilities and external specialists, and retain the knowledge and ownership required to continuously evolve analytics as a core part of our products and platforms. 

About Client Company

Client is building autonomous ships and submarines that operate in the world's most hostile environments. We're executing India's flagship autonomous submarine project the Jalkapi XLAUV on order from the Indian Navy. This is an unmanned submarine weighing over 20 tons that can travel 5,000+ kilometers autonomously and operate in the ocean for 30+ days at a time.

We're creating some of the largest autonomous robots in the world, machines with direct impact on the global economy and national security. While autonomous cars in India may still be a dream, autonomous ships and submarines are already a reality, and it is possible to build for the world from India.

Job Title: Design Engineer

Location: Bangalore | Full-Time |

Experience: 4-10 Years

The Role

We are seeking a skilled CAD Designer with 4-10 years of experience to join our team. The ideal candidate will have a strong background in using NX CAD or other 3D CAD tools to create detailed and precise designs.

Key Responsibilities

Design and Modeling

• Create detailed 2D and 3D CAD designs of components and systems using tools such as NX CAD- preferred or Solidworks,AutoCAD, or CATIA.
• Develop and refine engineering drawings for manufacturing and assembly.
• Ensure designs meet technical specifications, functional requirements, and industry standards.

Prototyping and Testing

• Will be a part of R&D team to develop and test prototypes.
• Perform feasibility studies and stress analyses using simulation tools (e.g., ANSYS).
• Identify and address design issues during testing and validation phases.

Process Optimization

• Work closely with manufacturing teams to ensure designs are optimized for production.
• Implement Design for Manufacturing (DFM) and Design for Assembly (DFA) principles in projects.
• Continuously improve existing designs to enhance performance and cost efficiency.

Collaboration and Documentation

• Collaborate with multidisciplinary teams, including mechanical, electrical, and software engineers.
• Prepare technical documentation, including engineering reports, specifications, and design records.
• Support project planning and provide inputs for timelines and resource requirements.

Required Qualifications

• Bachelors or Masters degree in Mechanical Engineering, Industrial Design, or a related field.
• 4-10 years of experience in mechanical design or engineering, preferably in R&D focused industries working on electro-mechanical/robotic systems.
• Proven experience in designing components and systems for complex projects.
• Proficiency in NX CAD software and PLM.
• Familiarity with simulation tools like ANSYS or Abaqus.
• Strong knowledge of materials, manufacturing processes, and prototyping techniques.
• Experience in DFM, DFA, and DFMEA principles.
• Excellent problem-solving and analytical skills.
• Strong attention to detail and commitment to quality.
• Ability to manage multiple priorities and meet tight deadlines.

Why Join Rekise Marine

• Technical Excellence: Work on engineering challenges at the intersection of mechanical design, autonomous systems, and extreme environment engineering. Design pressure vessels operating at 300-meter depths and solve problems that few engineers in India have tackled.
• Mission Impact: Your work will directly strengthen India's underwater defense capabilities. The Jalkapi XLAUV isn't just a product,it's a strategic asset that will serve the Indian Navy for decades.
• Startup Velocity, Defense Rigor: Experience the best of both worlds,we move fast and empower team members to make decisions while maintaining the engineering discipline required for defense applications.
• Competitive Compensation: Market-leading salary, health insurance and benefits.
• Innovative Environment: Flexible, collaborative culture that values initiative and creative problem-solving over hierarchy. Access to cutting-edge design tools and software licenses.

Job Title: Senior Network & Application Delivery Engineer

Job Summary:

We are looking for a highly experienced professional with 10+ years of expertise in

application delivery, DNS, and open-source technologies. The role focuses on managing

and optimizing network services, ensuring high availability, performance, and scalability.

Key Responsibilities:

• Design, implement, and manage application delivery solutions using F5 (LTM/GTM).
• Administer and support DNS/DHCP/IPAM solutions using Infoblox.
• Deploy and manage web/application servers using NGINX.
• Develop and maintain scripts for automation, monitoring, and operational efficiency.
• Work with open-source technologies to build scalable and reliable solutions.
• Troubleshoot complex network and application delivery issues.
• Collaborate with cross-functional teams for seamless service delivery.
• Ensure high availability, performance, and security of infrastructure.

Required Skills & Experience:

• Minimum 10 years of experience in F5, Infoblox, and NGINX.
• Strong hands-on experience in application delivery and DNS management.
• Good scripting knowledge (Shell/Python or similar).
• Experience working with open-source tools and technologies.
• Strong troubleshooting and analytical skills.
• Excellent communication and stakeholder management skills.

Are you looking to break out of the silo of pure-tech engineering and build systems that directly move millions in global revenue? If you want to own an entire, high-impact platform end-to-end and see the immediate business value of your code every single day, this is your playground. At Ultrahuman, you will act as a critical bridge between deep engineering and global market execution, turning data intelligence into autonomous, revenue-driving action across 100+ countries. 

About the Company: 

Ultrahuman is one of the world's fastest-growing wearable companies. The Ultrahuman Ring AIR — the world's lightest sleep-tracking smart ring — sells in 100+ countries. We operate like a product company in every function, and marketplaces is no exception: our Amazon business across the UK, Germany, Canada, Australia, India, the UAE and beyond runs on uh-amazon, an in-house platform we built ourselves. 

Role: Marketplace Platform Engineer 

Location: Begur, Bengaluru 

Schedule: Hybrid. 

Marketplace Platform Engineer 

Turn a read-only intelligence platform into the hands that run a global Amazon business. 

Why this role exists 

uh-amazon already does the seeing: a fleet of agents producing daily intelligence across every marketplace, an automated fulfillment middleware that intercepts and routes every order, and a self-hosted agent platform the team uses without writing code. But it writes almost nothing back to Amazon — every ads change, price correction, and listing push is still done by hand. That write side is unbuilt, and it is worth more than the entire team's cost: the daily briefs already flag large sums of recoverable ad spend that no one has the hands to recover. You will be the platform's owner and the team's force multiplier. 

What you'll own 

• The uh-amazon codebase end-to-end — the FastAPI middleware, the agent fleet, the self-hosted agent platform, and the deploy pipeline 
• The write side, behind staged approval gates — the order-management bridge first, then ads execution, repricing, and listing-push agents, each earning the right to act 
• Platform trust — kill the false-positive classes and fix the chronically failing agents, so the team acts on the briefs instead of second-guessing them 
• Operator self-serve — the team adds and tunes agents through the platform without touching code 

Your first 90 days 

• Ship the order-management bridge that removes the last manual step in fulfillment 
• Ship the first ads-execution agent behind a human approval gate, working the platform's existing recommendation lists 
• Eliminate the top false-positive classes in the daily briefs 

What we're looking for 

• Strong Python (FastAPI or similar) and real API-integration depth — OAuth, rate limits, retries, idempotency; you have built against messy third-party APIs in production 
• LLM-agent experience — you have built tool-using agents or LLM pipelines, designed prompts and tool schemas, and debugged why a model did something 
• Ship-fast evidence — small PRs, production ownership, comfort being the only engineer on a system 
• Comfort owning production writes against a live revenue channel, with gates and audit trails you design 

Strongly preferred 

• Amazon SP-API or Ads API experience specifically — this collapses your ramp to near zero 
• E-commerce domain (order management, marketplaces, repricing, feeds); container/orchestration experience 
• A public GitHub with real contributions 

Interested in designing award-winning wearables while managing challenging constraints so that your products are used everyday by millions of users? Then read on..

ULTRAHUMAN • HARDWARE

Hardware Design Engineer Wearables

Bangalore (Kudlu Gate)| • On-site | Full-time |

ABOUT THE ROLE

Ultrahuman's Hardware division builds award-winning wearables the Ultrahuman Ring and Ring Air pushing consumer technology in health and metabolic fitness. We're looking for a Hardware Design Engineer to own electronics design for our next-generation smart rings, from architecture and schematic capture through PCB layout, bring-up, and mass production.

This is a hands-on role at the extremes of miniaturization and power efficiency. You'll make architecture-level component decisions, drive high-density and RF layout, and take designs through NPI to volume — working closely with mechanical, firmware, and manufacturing teams on fast product cycles.

KEY RESPONSIBILITIES

Architecture & Schematic Design

• Translate product requirements into hardware architecture, then into schematics and manufacturable PCB designs using OrCAD / Allegro (Cadence).
• Own component selection across MCU/SoC, PMIC, sensor AFEs, and RF front-ends — balancing size, power, cost, and supply availability.
• Handle schematic-to-layout conversion and netlist import; create and maintain symbol/footprint libraries and land patterns.

High-Density & RF Layout

• Design and review high-density (HDI), rigid, and rigid-flex PCB layouts for space-constrained wearable form factors.
• Design 2.4 GHz BLE antennas and NFC coils, matching networks, and controlled-impedance routing; support antenna tuning and RF validation.
• Apply signal-integrity best practices for high-speed digital interfaces and mixed-signal boards.

Power & Low-Power Design

• Architect power trees around PMICs, buck/boost converters, and LDOs, including Li-ion charging for small-capacity cells.
• Build and validate ultra-low-power current budgets to meet multi-day battery-life targets.
• Strong grasp of power electronics and active/passive component behaviour.

Sensor Integration

• Integrate optical biosensing (PPG) AFEs, IMUs, temperature sensors, and haptics; own I²C/SPI interface design and analog front-end layout.

Manufacturing & DFM

• Own Gerber/ODB++ release, fabrication and assembly drawings, panelization, and full manufacturing data packages.
• Prepare and maintain BOMs; evaluate and qualify alternate / second-source components.
• Drive DFM/DFA reviews with fab and SMT/EMS partners; support NPI through EVT/DVT/PVT to mass production.
• Sound understanding of PCB materials, stackups, and component assembly processes.

Compliance, Reliability & Validation

• Apply EMI/EMC, thermal, and mechanical design best practices.
• Support pre-compliance and certification across FCC, CE, BIS, and RoHS, and familiarity with IEC standards for PCB design safety.
• Coordinate with test engineers on board bring-up and PCB validation; run circuit simulations for RF and signal/timing optimization.

Ownership & Collaboration

• Independently manage hardware projects end-to-end, including vendor coordination and delivery of final hardware.
• Collaborate with mechanical engineers to optimize designs and meet project timelines.
• Bring the latest design tools, methodologies, and industry best practices into the team.

REQUIRED QUALIFICATIONS

• Bachelor's or Master's in EEE, Electronics, or equivalent practical experience.
• 4+ years of hands-on hardware / PCB design experience, ideally in consumer electronics or wearables.
• Proficiency with a leading schematic and PCB toolchain (OrCAD / Allegro preferred).
• Proven track record taking a product from schematic through layout to volume production.
• Working knowledge of power electronics and active/passive component selection.
• Familiarity with global certifications (FCC, CE, BIS, RoHS) and IEC PCB safety standards.

PREFERRED / BONUS

• Experience with miniaturized high-density or rigid-flex designs.
• RF design experience (2.4 GHz / BLE, NFC, antenna tuning and matching).
• EMI/EMC design and pre-compliance testing experience.
• Low-power / battery-operated wearable product experience.
• Familiarity with reliability methods (DFMEA, derating) and RF / signal-timing circuit simulation.

Are you looking to work in the cutting edge area of applying data-science to help global customers get a better insight into their health? If so, read on and apply.

Role Name: Senior Data Scientist

Science Team | Full-Time | In-Office | Bangalore

The Role

The Ultrahuman Science Team builds the algorithms behind the Ring, M1 CGM, blood and urine biomarkers, and Performance Lab assessments. We are hiring a Senior Data Scientist to own those algorithms end to end: from the raw sensor signal to a model that is shipped, monitored, and trusted in users' hands.

This is a build role with real scope. In a typical month you will improve a production algorithm, root-cause a metric users are complaining about, and stand up the data pipeline the next model needs. The common thread is ownership: you take a vague question and return a working answer, without waiting to be handed scope.

What You'll Do

·      Own algorithms end to end: sleep staging, activity detection, sensor-derived metrics, and health scores. You frame the problem, build the features, train and evaluate the model, and see it live

·      Ship models, not notebooks: you prove a change on our own cohort before it reaches users, and a model is done only when it runs in production and you can tell how it is behaving

·      Validate against reference standards: design evaluations against gold standards, reference devices, and study ground truth, and know when a result is real and when it is an artifact

·      Own the data layer: cohort extraction, feature pipelines, study data, and raw sensor data, so the next model starts from clean inputs

What This Looks Like in Practice

1. Improving production algorithms - Take an existing production model like sleep staging, root-cause the failure modes against reference data, and ship a fix you can defend with numbers.

2. Building new models - Train an activity classifier on raw sensor data, design the labeled data collection that expands it, and pick the operating point so false positives never erode trust.

3. Proving it before it ships - Run a new steps algorithm against reference-device cohorts, decide with data when it is ready, and monitor how it behaves after rollout.

Who You Are

The two things we can't coach

·      High ownership, end to end: you take a problem from a vague question to a shipped model without waiting to be handed scope, and you can point to something you owned from raw data all the way to production

·      Hungry for more scope: you have outgrown your current role and want problems biggerthan your title, with the technical depth to be trusted with them

Also important

·      You've worked with human health data: wearables, physiological signals, or clinical data.

If your experience is close but not exact, show us why you will ramp fast

·      You've built at a startup: or somewhere small enough that nobody handed you clean data, clear specs, or a mature ML platform

·      You work like it's 2026: coding agents and AI tooling are part of how you build every day, and you can tell which new capabilities are worth adopting

·      You communicate: you can explain a model and its limits to a product manager, an engineer, or a founder, and hold your own with our scientists Core Technical Skills

·      Languages and data: Python and SQL daily, comfortable working in a real codebase

·      Machine learning: PyTorch or TensorFlow, scikit-learn, and gradient boosting, with the judgment to know which the problem needs

·      Advanced machine learning: time series and sequence models, deep learning on continuous physiological signals, and ensembles

·      Statistics and evaluation: hypothesis testing, experiment and A/B design, model evaluation, and error analysis against a reference standard

·      Scale and cloud: Spark or equivalent on large datasets, and AWS, GCP, or Azure

·      Production ML and MLOps: training pipelines, model versioning, deployment, monitoring, and drift detection

·      LLMs and agentic systems: fine-tuning and serving models, building agentic pipelines, and using coding agents to move faster

Experience:

- 4 to 5 years building and shipping machine learning systems. We index on what you have shipped and on trajectory, not the exact number of years; if you are a little earlier but have clearly outgrown your current scope, we want to hear from you.

- Bachelor's or higher in engineering, computer science, statistics, or a related field.

How We Work and Who Thrives Here

- The Science team is small and moves fast, and much of the work has no precedent to copy.

- People do their best work here when they are energized by ambiguity, low on ego, quick to adopt a better idea no matter where it comes from, and comfortable owning something before anyone has told them how. If you need a mature data org, clean labelled datasets, and clear guardrails to thrive, this particular role will not be the right fit, and that is worth knowing up front.

What You'll Gain

·      Ownership of algorithms that hundreds of thousands of people see every morning

·      A dataset most scientists never get to touch: 100M+ nights of sleep and continuous physiological signals at scale

·      Direct collaboration with the engineering, product, and design teams building Ultrahuman

Are you interested in writing agentic systems that helps companies like Coca-Cola, ITC and Lenovo drive E-commerce success? Do you want to bring Autonomy to E-commerce? Then read on and apply.

Applied Scientist - Decision AI

Location: Bengaluru

Work Schedule: Hybrid (Candidate must be based in Bengaluru - 1-2 days of WFO may be required at a later date)

About Kily

Kily is an AI company bringing autonomy to digital commerce growth. We build autonomous agents that manage Advertising, Pricing and Listings for brands and sellers across commerce marketplaces.

Performance in modern commerce shifts constantly - across marketplaces, categories and cities - faster than teams can manually track, diagnose and act on. Kily's agents work continuously against real business objectives with each brands unique context, objectives and operating constraints and keeping humans in the loop where it matters.

The Role

We are looking for an Applied Scientist to build the models and decision systems behind Kily's recommendations and actions. The work is grounded in messy, real-world commerce data help build Kily's core decision intelligence layer: systems capable of understanding complex commerce data, determining why performance is changing, deciding what should be done about it, and ultimately taking actions autonomously at scale. You will work at the intersection of learning algorithms, decision making under uncertainty and agentic systems.

What You'll Do

·      Conduct deep analysis of commerce data to derive insights, and identify gaps and new opportunities

·      Develop scalable and effective machine-learning models and optimisation strategies to solve business problems across advertising, pricing and listings

·      Define and lead science initiatives from problem framing through production deployment in a high-ambiguity environment

·      Identify and build the sequential feedback loops that make decisions improve over time

·      Design evaluation frameworks to measure the quality and business impact at scale

·      Work closely with engineering, analytics and product teams to take models from experimentation into production

What We're Looking For

·      4+ years in Applied ML/AI, Data Science. Masters or PhD in a quantitative field is a plus

·      Deep proficiency in Python, SQL, statistics and data analysis

·      Hands-on experience developing, deploying and maintaining the end-to-end lifecycle of machine-learning models

·      Experience with LLMs, fine-tuning, AI agents, optimisation or sequential decision systems is a strong plus

·      Exposure to ecommerce, marketplaces, advertising or pricing data is valuable but not essential

·      Strong problem-solving and communication skills; ML research experience is a plus

WHY KILY

Kily is already working with leading brands including ITC, Unilever, Mondelez, Coca-Cola and Lenovo, and has recently raised an INR 30 crore ($3.1 mn) Seed round led by Sorin Investments, with participation from Razorpay and Wyser Capital. You'll have the opportunity to build a foundational AI system from an early stage - one designed not merely to generate insights, but to autonomously drive real-world business

outcomes.

Do you want to own the PMIC, PLL, and PCIe buffer architectures that ship in millions of vehicles? Do you want to build and lead the team solving India's toughest automotive power and clocking challenges?

Role: Head of Engineering

Level Five Cartronics | Fabless Automotive Semiconductor Design

Location: MG Road, Bengaluru, Karnataka, India (On-site)

About Us

Founded by serial Entrepreneurs, Level Five Cartronics is a fabless semiconductor design company headquartered in Bengaluru, building automotive-grade Power Management ICs (PMICs), high-precision oscillators, and high-performance phase-locked loops (PLLs) for the next generation of vehicle electronics. Our portfolio centres on low-EMI power delivery — including spread-spectrum EMI suppression — and low-jitter clocking and interface solutions for safety-critical solutions and infotainment systems. We design DC-DC converters, LDOs, and clock distribution networks (including low-jitter PCIe Gen 4, 5, and 6 buffers) in CMOS and BCD high-voltage processes across the 55nm, 90nm and 180nm nodes. We own our products end to end, from architecture through silicon characterization and productization, as part of India's growing fabless semiconductor ecosystem.

The Role

We are looking for a hands-on Head of Engineering, based at our Bengaluru headquarters, to lead our analog/mixed-signal design organization. This is a senior leadership position for an engineer who has personally taken complex automotive power, clocking, and high-speed interface products from concept to high-volume production — and who can build, mentor, and scale the cross-functional team that does it again and again.

You will set the technical direction for our PMIC, oscillator, PLL, and PCIe buffer roadmaps, own design quality and tape-out readiness, and partner closely with characterization, product, and test engineering to ensure every product meets stringent automotive reliability, jitter, and EMC requirements.

What You'll Do

1. Lead and grow the analog/mixed-signal design, layout, and verification teams across multiple product lines, based out of our Bengaluru engineering center.

2. Own the technical architecture and execution of automotive-grade PMICs, DC-DC converters, LDOs, low phase noise Fractional-N phase-locked loops (PLLs), and low-jitter PCIe Gen 4, 5, and 6 buffers.

3. Target high-speed interface applications by driving low phase noise PLL architectures explicitly optimized for PCIe Gen 4, 5, and 6 standards.

4. Drive designs across CMOS and BCD high-voltage processes at 55nm, 90nm and 180nm, from specification through tape-out and qualification.

5. Set and enforce design methodology, review gates, and tape-out criteria; review schematics, layout, and verification plans personally where it matters.

6. Partner with characterization engineers on lab bring-up, silicon debug, and correlation of measured results to simulation.

7. Work side by side with product engineers on productization, test development, yield, and sustaining.

8. Build and lead cross-functional teams; recruit, develop, and retain top analog and layout talent in India's semiconductor talent market.

9. Be a technical authority and final escalation point for difficult design and silicon issues.

What You'll Bring

- Minimum of 12 years (preferably more) of experience in analog/mixed-signal design, layout, and productization.

- Demonstrated track record of taped-out databases and shipping full products in volume, not just isolated blocks.

- Deep expertise across the full flow: schematic design, layout, and lab characterization (understanding how each one constrains the others).

- Hands-on design of DC-DC converters and LDOs in CMOS and BCD high-voltage processes.

- Expertise in clocking and interfaces: deep understanding of low phase noise design, Fractional-N PLL architectures, and low-jitter PCIe Gen 4, 5, and 6 clock buffers/drivers.

- Experience with PMICs, oscillators, and spread-spectrum / EMI suppression techniques.

- Strong working knowledge of the 55nm, 90nm and 180nm process nodes.

- Extensive experience with Cadence EDA tools across the design and verification flow.

- Mixed-signal behavioral modeling in Verilog (Verilog/Verilog-AMS).

- Proven history of working closely with characterization and product engineers through bring-up and ramp.

- Demonstrated success building, leading, and recruiting cross-functional engineering teams.

Nice to Have

- Automotive qualification experience (AEC-Q100, ISO 26262 / functional safety awareness).

- Strong EMC/EMI design and measurement background.

- Experience scaling an engineering organization in a fabless environment, ideally within India's semiconductor ecosystem.

Why Level Five Cartronics

You'll own real products in a fast-moving automotive market, work across the full design-to-silicon flow, and shape the engineering culture of a growing fabless company based in Bengaluru — one of India's leading semiconductor design hubs. If you've built power, clocking, and high-speed interface products that ship in cars and you want to lead the team that builds the next ones, we'd like to talk.

Level Five Cartronics is an equal opportunity employer.

We're building in a market that hit $47B in 2026 and is on track to hit $107.5B by 2028 and we're not chasing that opportunity from the sidelines. Our founding team brings marketing expertise from Kotak and Amazon paired with deep AI chops, we were selected as one of just 20 startups by Google, and we already have paying customers like Kotak and Myntra using the product in production. Join us early and help build the infrastructure that turns AI marketing adoption (already at 88%) into real, scaled results for customers who are already paying for it, not case studies.

Founding Product Engineer, Applied AI

Location: Mumbai • Hybrid • Reports to: CTO

WHAT THIS ROLE ACTUALLY IS

Weve built a multi-agent AI system for marketing. It works well out of the box but every client (their data, workflows, brand rules, compliance constraints, output preferences) is different. Generic doesnt ship results. Customised does.

This role is the bridge: you sit between our agent architecture and the client’s reality. You understand both deeply, and you make the agents do what each specific client needs them to do.

Think Palantir Forward Deployed Engineer, but for AI agents. An engineer who owns product outcomes end-to-end.

WHAT YOU'LL DO

Day-to-day split: roughly 60% in Codex and Claude Code shipping customisations, 40% in client rooms understanding what to ship next.

• Customise the agents. Tune prompts, build new agent capabilities, configure workflows, wire up integrations. Codex and Claude Code are your primary IDEs. You ship working code, not specs for someone else to build.
• Own client outcomes end-to-end. From discovery to live deployment, you are the person responsible for whether the agents actually solve the client’s problem. No PM-engineer handoff to hide behind.
• Problem-solve in real time. Client says “the output tone is off for our brand” or “the research agent is missing X data source” — you diagnose, fix, and redeploy, usually within days.
• Hold your own on creative. When a CMO says “this doesn’t feel right,” you can question intelligently — is it the prompt, the input brief, the brand guidelines themselves, or the client’s own confusion? Most engineers reach for the prompt. The good ones diagnose first.
• Feed learnings back to core product. Anything that gets customised 3+ times becomes a platform feature. You decide what graduates.
• Build the playbook. As we scale from 10 to 50 to 100 clients, the customisation patterns you create become the foundation others work from.

WHAT YOU NEED

• Real engineering chops. You can read a codebase, write production code, debug agent failures, and ship to live clients. AI tools are your accelerant, not your crutch.
• Comfort with agents as a system. You understand how LLMs fail, why prompts drift, what context engineering means, when to use tools vs. fine-tuning, why eval harnesses matter. If “MCP,” “tool use,” and “agent harness” feel like jargon, this isn’t the role.
• Client-facing instincts. Comfortable in a room with a CMO, an enterprise IT head, and a junior brand manager — and you can switch register for each in the same meeting. If client calls feel like tax to you, don’t apply.
• Some creative literacy. You don’t need to be a designer. You do need to be able to tell the difference between “this output is technically broken” and “this output is technically fine but creatively wrong” — and chase the right thread.
• Bias toward shipping. A working hack today beats a clean design next quarter.

YOU'LL THRIVE HERE IF

• You’re an engineer who realised products live or die on customisation, not architecture.
• You’ve been frustrated by being kept away from customers.
• You like building with AI tools and want a role where that’s the job, not a side experiment.
• You like marketing as a domain — or you’re willing to fall in love with it.

YOU WON'T THRIVE HERE IF

• You want to optimise systems in a corner with headphones on.
• You think client calls are below your pay grade.
• You think AI is overhyped (we don’t).
• You need a fully scoped ticket queue and weekly sprint rituals.

We're building in a market that hit $47B in 2026 and is on track to hit $107.5B by 2028 and we're not chasing that opportunity from the sidelines. Our founding team brings marketing expertise from Kotak and Amazon paired with deep AI chops. We were selected into Google's AI Accelerator program, and we already have paying customers like Kotak and Myntra using the product in production.

Join us early and help build the infrastructure that turns AI marketing adoption (already at 88%) into real, scaled results for customers who are already paying for it, not case studies.

Role Name: Founding Product Manager, Applied AI

Location: Mumbai • Hybrid •

Reports to: CTO

WHAT THIS ROLE ACTUALLY IS

Weve built a multi-agent AI system for marketing. It works well out of the box but every client (their data, workflows, brand rules, compliance constraints, output preferences) is different. Generic doesn’t ship results. Customised does.

This role is the bridge: you sit between our agent architecture and the client’s reality. You understand both deeply, and you make the agents do what each specific client needs them to do.

You’re a PM who knows the spec-to-engineer handoff is where products die. So you don’t hand off. You open Claude Code or Codex and ship the change yourself.

WHAT YOU'LL DO

Day-to-day split: roughly 60% on client work, product judgment, and shaping what to ship — 40% directly in Codex and Claude Code shipping it.

·      Own client outcomes end-to-end. From discovery to live deployment, you are the person responsible for whether the agents actually solve the client’s problem.

·      Translate ambiguity into working systems. Clients don’t know what they want until they see it. You probe, prototype, demo, iterate — without waiting for an engineer to be free.

·      Customise the agents yourself. Tune prompts, build new agent capabilities, configure workflows, wire up integrations. Codex and Claude Code do the heavy lifting; your product judgment does the steering.

·      Diagnose creative problems sharply. When a CMO says “this doesn’t feel right,” you can question intelligently — is it the prompt, the input brief, the brand guidelines themselves, or the client’s own confusion? Most PMs nod and forward to engineering. The good ones diagnose first, then fix.

·      Feed learnings back to core product. Anything that gets customised 3+ times becomes a platform feature. You decide what graduates.

·      Build the playbook. As we scale from 10 to 50 to 100 clients, the customisation patterns you create, become the foundation others work from.

WHAT YOU NEED

·      Real product judgment. You can hear “we need a dashboard” and figure out the actual problem is “the marketing director doesn’t trust the agent’s decisions yet.” You’ve done this before, in a role where the outcome was on you.

·      Hands-on technical ability. You don’t need a CS degree, but you must be able to read code, write code with AI tools, debug, and ship. If you’ve never opened Claude Code or Codex and built something real, this role isn’t for you. Coding is part of the daily job, not an occasional adventure.

·      Comfort with agents as a system. You understand how LLMs fail, why prompts drift, what context engineering means, when to use tools vs. fine-tuning, why eval harnesses matter. If “MCP,” “tool use,” and “agent harness” feel like jargon, this isn’t the role.

Client-facing instincts. Comfortable in a room with a CMO, an enterprise IT head, and a junior brand manager — and you can switch register for each in the same meeting.

·      Creative literacy. You don’t need to be a designer. You do need to be able to tell the difference between “this output is technically broken” and “this output is technically fine but creatively wrong” — and chase the right thread.

·      Bias toward shipping. A working hack today beats a clean design next quarter.

YOU'LL THRIVE HERE IF

·      You’re a PM who realised the engineer handoff is where your products die.

·      You’ve quietly learned to ship in Claude Code or Cursor on the side because you got tired of waiting.

·      You want a role where coding ability is upside, not heresy.

·      You like marketing as a domain — or you’re willing to fall in love with it.

YOU WON'T THRIVE HERE IF

·      You want to write strategy decks more than you want to ship features.

·      You think “PM doesn’t code” is a principle worth defending.

·      You think AI is overhyped (we don’t).

·      You need a fully scoped backlog and weekly sprint rituals.