Robotics Hardware Engineer

Job Responsibilities:

We are seeking a highly skilled and motivated Robotics Engineers with a strong focus

on ROS2 development to join our dynamic team. As a Robotics Engineer, you will be

responsible for designing, developing, and implementing advanced robotic systems and

applications using the Robot Operating System 2 (ROS2). You need to develop the

behavioral and control systems, including planning and navigation needed for

autonomous robots. This role requires a deep understanding of robotic software

architecture, proficiency in ROS2, and experience with hardware integration and real

time systems and expertise in URDF (Unified Robot Description Format).

Key Responsibilities :

Design and Development:

 Develop robust and scalable robotic applications using ROS2. Implement

software for various robotic systems, ensuring high performance and reliability.

 Hand-on with developing ROS2 nodes, Services/Clients, Publishers/Subscriber.

 Lead and develop path/motion planning algorithms that include route planning,

trajectory optimization, decision making, and open space planning. Good

understandings of Robot dynamics, kinematics and modeling.

System Integration :

 Integrate sensors, actuators, and other hardware components with robotic

systems. Ensure seamless communication between hardware and software

layers. Experienced on integration with perception sensors such as IMU, GPS,

Stereo Cameras, Lidar, Radar, and various other sensors.

URDF Modeling :

 Create and maintain accurate URDF models for robotic systems. Ensure models

accurately represent the physical configuration and kinematics of the robots.

Algorithm Implementation :

 Implement and optimize algorithms for perception, localization, mapping,

navigation, and control.

Simulation and Testing :

 Utilize simulation tools to test and validate robotic systems in virtual

environments like Gazebo, Rviz2 and Unity.

Perform rigorous testing in real-world scenarios to ensure system robustness.

Documentation : Create and maintain comprehensive documentation for system architecture,

design decisions, algorithms, and user guides.

Research and Development :

 Stay updated with the latest advancements in robotics and ROS2, and URDF.

Contribute to the continuous improvement of development processes and tools.

All candidates must have at least a Bachelor’s degree in a related field(Computer

Engineering, Electronics/Electrical Engineering, Electronics and Communication

Engineering, Robotics or similar).

Advanced degrees are a plus.

Embedded Systems / Firmware Engineer

Key Responsibilities

• Develop embedded firmware for IoT and connected devices using C/C++.
• Work on RTOS, bare-metal programming, memory management, device drivers, and communication protocols.
• Develop and integrate drivers/interfaces for cameras, motors, sensors, and vision systems.
• Work with Python and Shell scripting for development and automation.
• Apply basic AI/ML and computer vision concepts to embedded applications.
• Collaborate on electrical and mechanical design, hardware integration, testing, and debugging.

Required Skills

• C, C++, Python, Shell Scripting
• Embedded Systems & Firmware
• IoT, RTOS, Bare Metal
• Memory Management & Device Drivers
• Communication Protocols
• Camera, Motor & Vision Systems
• Basic AI/ML understanding
• Electrical & Mechanical Design understanding

Job Title: Software/Hardware Engineer (IIT/NIT)

Location: Bangalore

Website: https://www.zeuron.ai

Experience: 1-5Years

CTC: 6-10 LPA

No Freshers

About the Company

Zeuron.ai is a Bangalore-based deep-tech startup founded in 2019, focused on building brain-inspired computing and AI-driven healthcare solutions. The company combines neuroscience, AI, and gaming to create innovative digital therapeutics and neurotechnology platforms for improving brain health, rehabilitation, and overall well-being.

The role

Zeuron.ai is looking for hands-on software engineers who can turn an incomplete brief into reliable, usable software. You will work as an individual contributor, make sound technical decisions and take responsibility for the quality of what you deliver.

AI coding tools will be part of the workflow. We expect you to understand the underlying software well enough to build and debug without an LLM, then use AI to accelerate implementation, exploration and verification. You remain accountable for the result.

What you will own

• End-to-end delivery: clarify requirements, break work into achievable steps, implement features, test them, deploy them and respond to issues after release.

• Product decisions: understand the user problem, question unclear requirements and explain trade-offs between speed, quality, complexity and maintainability.

• Reliable software: investigate defects, identify root causes and improve error handling, performance and usability.

• Engineering continuity: maintain readable code, useful documentation and clear handovers so that others can run, understand and extend your work.

Engineering expectations

We value demonstrated building ability, technical reasoning and sound judgement. Tool familiarity should be supported by evidence of software you have actually delivered.

Software fundamentals

• Programming: practical fluency in at least one programming language, with an understanding of data structures, control flow, modularity and common complexity trade-offs.

• Applications and services: understand how interfaces, APIs, business logic and data storage interact. Be able to trace a failure across these boundaries.

• Data: work with databases, reason about data models and queries, and handle validation, consistency and errors appropriately.

• Development workflow: use Git confidently, review changes, manage dependencies and keep development and deployment instructions reproducible.

• Testing and debugging: reproduce failures, form hypotheses, inspect logs and isolate causes. Test important behaviour and edge cases rather than relying on a successful demo.

• Security and reliability: recognise basic risks around authentication, access control, secrets, input handling and third-party dependencies.

Build independently. Use AI effectively.

• Without LLMs: write and modify code, diagnose defects, explain design choices and use documentation to solve unfamiliar problems independently.

• With AI coding tools: frame tasks clearly, supply relevant context, use generated suggestions selectively and inspect the resulting changes.

• Verify before accepting: check correctness, integration, security and maintainability. Recognise invented APIs, fragile assumptions and plausible-looking code that does not solve the actual problem.

• Protect information: use approved tools and handle credentials, proprietary code and user data responsibly.

Evidence we want to discuss

Be prepared to walk through a project you contributed to: the problem, your specific contribution, important technical decisions, a difficult bug and how you verified the result. Public repositories or demos are useful where available; do not share confidential material from previous employers.

Ownership, growth & applying

How you will work

• Act as an owner: follow through on agreed deliverables, raise blockers early and communicate progress with concrete evidence.

• Work with the team: collaborate with product and engineering colleagues, accept review constructively and explain technical choices clearly.

• Learn with purpose: pick up unfamiliar tools when the problem requires them, while keeping the solution proportionate to the need.

• Grow through contribution: begin with hands-on individual-contributor responsibility, with potential to take on broader product or team responsibility as delivery, judgement and collaboration develop.

What strong performance looks like

Working features that meet agreed requirements; clear reasoning about implementation; defects investigated systematically; code that others can maintain; and AI-assisted work whose quality you can explain and verify.

Eligibility and compensation

Experience: 1-5 years of hands-on software development experience only.

Freshers are not considered.

Locations: Bengaluru and Belagavi.

Annual CTC : 6-10 LPA

The offer will depend on experience, interview performance and growth potential.

What to expect in the assessment

Be prepared for a discussion of your previous work, a practical coding or debugging task without LLM assistance, and an assessment of how you use AI coding tools and verify their output. We will also discuss product judgement, ownership and collaboration.

About the Role

We are seeking a hands-on Tech Lead to design, build, and integrate AI-driven systems that automate and enhance real-world business workflows. This is a high-impact role for someone who enjoys full-stack ownership — from backend AI architecture to frontend user experiences — and can align engineering decisions with measurable product outcomes.

You will begin as a strong individual contributor, independently architecting and deploying AI-powered solutions. As the product portfolio scales, you will lead a distributed team across India and Australia, acting as a System Integrator to align engineering, data, and AI contributions into cohesive production systems.

Example Project

Design and deploy a multi-agent AI system to automate critical stages of a company’s sales cycle, including:

• Generating client proposals using historical SharePoint data and CRM insights
• Summarizing meeting transcripts
• Drafting follow-up communications
• Feeding structured insights into dashboards and workflow tools

The solution will combine RAG pipelines, LLM reasoning, and React-based interfaces to deliver measurable productivity gains.

Key Responsibilities

• Architect and implement AI workflows using LLMs, vector databases, and automation frameworks
• Act as a System Integrator, coordinating deliverables across distributed engineering and AI teams
• Develop frontend interfaces using React/JavaScript to enable seamless human-AI collaboration
• Design APIs and microservices integrating AI systems with enterprise platforms (SharePoint, Teams, Databricks, Azure)
• Drive architecture decisions balancing scalability, performance, and security
• Collaborate with product managers, clients, and data teams to translate business use cases into production-ready systems
• Mentor junior engineers and evolve into a broader leadership role as the team grows

Ideal Candidate Profile

Experience Requirements

• 5+ years in full-stack development (Python backend + React/JavaScript frontend)
• Strong experience in API and microservice integration
• 2+ years leading technical teams and coordinating distributed engineering efforts
• 1+ year of hands-on AI project experience (LLMs, Transformers, LangChain, OpenAI/Azure AI frameworks)
• Prior experience in B2B SaaS environments, particularly in AI, automation, or enterprise productivity solutions

Technical Expertise

• Designing and implementing AI workflows including RAG pipelines, vector databases, and prompt orchestration
• Ensuring backend and AI systems are scalable, reliable, observable, and secure
• Familiarity with enterprise integrations (SharePoint, Teams, Databricks, Azure)
• Experience building production-grade AI systems within enterprise SaaS ecosystems

Hands-on plugin and extension engineering (Ruby on Rails first), and agentic AI implementation. Please apply only if you have worked with Ruby on rails along with redmine, odoo.

Responsibilities

• Design agent-operable surfaces on each tool: typed, secure APIs, Model Context Protocol (MCP) servers, and webhook-driven automation
• Architect and build Redmine plugins in Ruby on Rails, Odoo modules, and GitHub Apps/Actions
• Engineer enhancements to be upgrade-safe across product versions 

Required Qualifications 

• 10+ years in software engineering, business-systems architecture, or platform engineering, with deep SME knowledge of operational tools such as Odoo, Redmine, GitHub, or comparable ERP/ITSM/DevOps platforms 
• Expert-level proficiency in Ruby on Rails, including production experience building or maintaining Redmine plugins or comparable Rails-based extensions 
• Strong command of business processes across delivery, support, and operations
• Practical agentic development experience: MCP, LLM tooling, AI-assisted automation, or agent-orchestrated workflows in production 
• Proven track record building plugins, modules, and extensions that survive product version upgrades, with disciplined API and integration design 

ROLE SUMMARY:

An experienced, hands-on engineering role owning the electrical and electronics hardware content of motor-drive and sensor systems. The Electrical / Electronics / Instrumentation Engineer is responsible for power distribution and motor-drive power-stage design, sensor interface boards, and taking boards through EMI/EMC compliance, with full ownership of schematic capture and layout from concept to fab-ready.

RESPONSIBILITIES:

• Design power distribution and the motor-drive power stage (gate drives, current sense, H-bridge/inverter stages)
• Implement supervised discrete-line circuitry per IF-08 ICD requirements
• Design sensor interface boards (resolver, encoder, analog/digital signal conditioning)
• Take boards through EMI/EMC compliance for MIL-STD-461
• Own schematic capture and layout in Altium or KiCad end-to-end, from concept to fab ready.

REQUIRED QUALIFICATIONS

• B.E./B.Tech/M.E./M.Tech. in Electrical, Electronics & Communication, Electronics & Instrumentation, or any other relevant field.
• 4-8 years of relevant experience.

KEY COMPETENCIES

• Hands-on power electronics: gate driver design, current sensing, protection circuitry
• Analog signal conditioning for sensor front-ends (resolver, encoder, LVDT-class signals)
• Practical EMI/EMC design experience, ideally against MIL-STD-461 or equivalent (automotive/industrial EMC also considered)
• Strong Altium or KiCad skills — layout discipline for power + mixed-signal boards.
• Prior work on ICD-driven or interface-controlled discrete I/O circuitry
• Defence, aerospace, or automotive electronics background

About Naicos

Naicos, a fast-paced startup, builds AI-native products for algorithmic commerce: the future of how e-commerce runs. Our first products are already live with paying customers, and we are shipping new ones continuously.

Your Role

You will drive the research behind our imaging products, finding approaches to hard, unsolved problems in product and apparel imagery that work at production scale. You will run the experiments, prove what is viable, and hand a working approach to the engineering team.

Who We Are Looking For

•     Total experience: 3 years or more, with a strong research orientation

•     Deep learning frameworks in Python: PyTorch or TensorFlow

•     Image processing in Python: OpenCV, Pillow, scikit-image

•     Working knowledge of diffusion and other image generation models

We are looking for a strong research or research-student profile: someone who investigates, experiments and proves an approach, working closely with the AI Architect. Someone who is driven to build solutions, not just desk research.

AI Skills and Experience

•     Computer vision: classical CV alongside deep learning.

•     Segmentation, image-to-image translation, geometry and lighting; 

•     Generative imaging: diffusion models, conditioning and control, fine-tuning and LoRA,

•     Reads academic papers, judges what is reproducible, and turns one into a working prototype in days

Good to have

•     3D and rendering; published research or open-source contributions; model optimisation for inference cost

Research and innovative problem solving

•     Comfortable where there is no known answer, and defines the approach yourself

•     Solves problems inventively rather than reaching for the biggest model; many results come from classical image processing, fitment and geometric transformation

Other Relevant Skills and Experience

•     Designs experiments: baselines, measurable success criteria, honest reporting of negative results

•     Explains findings to a non-research audience and guides engineers to production

•     Git and reproducible experiment tracking (Weights & Biases, MLflow or similar)

Educational Qualification

•     BE / B.Tech / ME / M.Tech in Computer Science

•     BE / B.Tech / ME / M.Tech in any discipline with proven Computer Vision coursework or work

•     MSc / MS in Computer Science, Maths, Statistics or Computer Vision

•     PhD in Computer Vision or Machine Learning: an advantage, not a requirement

•     Reputed Tier 1 university preferred

About Company

We are building general-purpose autonomous robots for US construction to tackle rising costs, safety risks, and labour shortages. Our modular, multi-trade platform combines purpose-built hardware with real-time site intelligence to navigate complex environments and execute tasks with precision. Trained in high-fidelity simulation and already deployed on live sites, our robots deliver 5x faster execution, 250%+ margin expansion, and significant cost savings.

About the Role

We are looking for a versatile, hands-on software engineer to join our growing team. You will work across embedded Linux systems, networking stacks, robotic middleware, and cloud-connected services. This role demands strong fundamentals, intellectual curiosity, and the ability to learn quickly — not just familiarity with buzzwords.

On-site, Bengaluru

Responsibilities

• Design and implement robot boot-up sequences and service orchestration to ensure reliable, deterministic system bring-up.
• Configure and manage Linux networking — TCP/IP stack, HTTP, iptables, ARP, DHCP, DNS — for robot-to-cloud and inter-robot communication.
• Own CI/CD pipelines using ArgoCD, GitHub Actions, and containerized workflows to ship software to robots.
• Manage Docker-based deployment and runtime environments on robot and cloud infrastructure.
• Write and maintain system administration tooling and bash scripts for fleet management and diagnostics.
• Collaborate closely with robotics, perception, and application teams to integrate platform capabilities.
• Establish and enforce best practices around Git workflows, branching strategies, and code review.
• Lead and mentor a small platform engineering team — set technical direction, conduct code reviews, and drive execution.

Requirements

All candidates must demonstrate solid, hands-on competency in every item listed below.

• Linux systems programming in C
• File I/O — read, write, seek, memory-mapped files
• Multi-threading — pthreads, mutexes, condition variables, thread safety
• Socket communication — TCP/UDP sockets, select/poll/epoll
• Basic data structures & algorithms — stack, heap, queue, linked list
• General comprehension ability — reading technical manuals, datasheets, and RFCs
• Python scripting
• Bash scripting
• Git — CLI usage, branching, merging, rebasing, conflict resolution
• Standard UML diagrams — flowchart, sequence diagram, deployment diagram
• Windowless text editor — vim, nano, or equivalent

Strong Advantage

• C++ programming — C++17, OOP, templates, STL
• Common network protocols — DHCP, ARP, TCP, UDP, DNS
• Network configuration — routers, switches, VLANs, subnetting
• Server-client application architecture
• P2P vs. centralised communication — DDS vs. MQTT
• Database management — SQL vs. NoSQL, schema design
• Network security — checksums (CRC, MD5, SHA), public-key encryption, digital signatures
• ROS2 framework — pub/sub, services, actions, lifecycle nodes, DDS transport
• CMake build system — targets, find_package, CTest integration
• Docker — Dockerfiles, docker-compose, remote image registries

Must-haves (non-negotiable)

• Strong Linux systems programming in C — multi-threading (pthreads), socket communication (TCP/UDP, epoll), and file I/O
• Hands-on experience with CI/CD pipelines (ArgoCD, GitHub Actions) and Docker-based deployments
• Networking expertise — TCP/IP stack, DHCP, DNS, iptables, inter-device communication
• Proficiency in Python and Bash scripting for fleet management and diagnostics
• ROS2 experience (pub/sub, DDS, lifecycle nodes) is a strong advantage

About Us

We believe the future of software development is AI-native — where engineers operate at a higher level of abstraction and quality remains non-negotiable. 

Incubyte is a software craft consultancy where the “how” of building software matters as much as the “what”.  

We partner with companies of all sizes, from helping enterprises build, scale, and modernize to early-stage founders bring their ideas to life. 

Our engineers operate in an AI-native development model, using AI as a collaborator across the SDLC to accelerate development while upholding the discipline of software craftsmanship. Guided by Software Craftsmanship and Extreme Programming practices, we build reliable, maintainable, and scalable systems with speed, without compromising quality. If this way of building software resonates with you, we’d like to talk. 

Our Guiding Principles 

These principles define how we work at Incubyte. They are non-negotiable. 

Relentless Pursuit of Quality with Pragmatism 

  We build high-quality systems without losing sight of delivery. 

Extreme Ownership 

  We take responsibility end-to-end for decisions, execution, and outcomes. 

Proactive Collaboration 

  We collaborate closely, challenge each other, and solve problems together. 

Active Pursuit of Mastery 

  We continuously improve our craft and raise our bar. 

Invite, Give, and Act on Feedback 

We seek, give, and act on feedback to get better every day. 

Ensuring Client Success 

We act as trusted partners and focus on real outcomes, not just output. 

Experience Level

This role is ideal for engineers with total 3+ years of experience with a proven track record of shipping complex projects successfully.

An experienced individual contributor and leader who thrives in large, complex projects with widespread impact.

What You’ll Do as a Software Craftsperson 

• Design and build high-quality, maintainable systems using disciplined engineering practices such as TDD, continuous refactoring, and pair programming 
• Operate in an AI-native development model, using AI as a collaborator to explore architecture and design, accelerate development, and continuously improve systems while applying strong judgment to ensure that speed never compromises quality 
• Take end-to-end ownership of outcomes from problem understanding and system design to implementation, deployment, and operation in production 
• Make thoughtful design decisions that balance simplicity, scalability, and long-term maintainability in real-world systems 
• Maintain a high bar for engineering quality through rigorous testing, code reviews, and continuous feedback 
• Investigate and resolve production issues, and implement systemic improvements to prevent recurrence 
• Work directly with clients, navigate ambiguity, and translate business problems into well-designed technical solutions 
• Contribute to improving team practices, tooling, and systems to raise the overall quality and effectiveness of engineering 

Requirements

What You’ll Bring 

• 3+ years of experience building high-quality, production systems (flexible based on demonstrated capability) 
• Strong fundamentals in software engineering, including object-oriented design, system design, and testing practices such as TDD 
• Demonstrated ability to build simple, maintainable, and scalable systems with a focus on long-term reliability 
• Proficiency in one or more modern technologies, Python, PHP, JavaScript, or TypeScript, with the ability to learn new technologies quickly 
• Deep experience working with Git in collaborative environments, including managing shared codebases, conducting code reviews, and maintaining a high bar for quality 
• Ability to operate effectively in an AI-native workflow using AI as a collaborator to explore solutions and accelerate development, while applying strong judgment to ensure correctness, quality, and maintainability 
• Clear thinking and strong problem-solving ability, with the capacity to break down complex problems into simple, well-structured solutions 
• A strong sense of ownership — you take responsibility for outcomes, care deeply about quality, and are not comfortable shipping work that does not meet your standards.

Benefits

Life at Incubyte 

We are a remote-first company with structured flexibility. Teams commit to shared rhythms during core hours, ensuring smooth collaboration while maintaining autonomy. Twice a year, we come together in person for a co-working sprint and once a year for a retreat - with all travel expenses covered. 

Our environment is built for crafters: pairing, refactoring, experimenting with AI, and pushing the boundaries of software excellence. We are all lifelong learners, and our work is our passion. 

Perks

• Dedicated learning & development budget. 
• Sponsorship for conference talks. 
• Comprehensive medical & term insurance. 
• Employee-friendly leave policies. 
• Home Office fund 
• Medical Insurance

Product Engineer — Role Summary

We are looking for a Product Engineer to build user-facing products that combine AI capabilities with practical applications. You will work at the intersection of software engineering and AI, developing autonomous, agent-driven systems that solve complex educational and research problems.

Key Responsibilities:

• Product Development: Design, build, and deploy production-ready applications powered by LLMs and AI agents.
• Data Engineering: Build scalable ETL/ELT pipelines to process structured and unstructured data, including text and audio, for RAG and model fine-tuning.
• Agentic Workflows: Develop multi-step AI agents with tool calling, APIs, databases, search, reasoning, and memory.
• Rapid Prototyping: Turn ideas and research concepts into interactive, production-ready applications.
• AI Integration: Use frameworks such as LangChain, LlamaIndex, AutoGen, or custom orchestrators to integrate AI into scalable systems.
• User Experience: Transform raw AI outputs into reliable, intuitive, and responsive user experiences.
• Collaboration: Work closely with ML researchers and data engineers to integrate custom and fine-tuned models.
• Observability: Monitor agent behavior, manage edge cases, reduce hallucinations, and improve reliability in production.

The ideal candidate combines strong software engineering, AI/LLM expertise, data engineering, and product thinking, with the ability to take an AI concept from prototype to production.