Robotics Enginner

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.

At InferQ, we are building solutions for autonomous and intelligent aerial systems. We seek a Robotic Navigation Engineer with deep technical rigor and a passion for developing mission-critical navigation, estimation, and path planning systems for UAVs. The role demands hands-on engagement across the autonomy stack. You will work at the intersection of robotics, AI, and aerospace, translating research into reliable field-deployable systems.

Key Responsibilities

• Architect and implement algorithms for joint state estimation, integrating multi-sensor inputs.
• Develop dynamic and real-time path planning solutions for UAVs.
• Create and validate flight simulations using various COTS Simulators or custom HIL/SIL test environments.
• Design and integrate advanced navigation systems.
• Work with avionics, AI, and controls teams to integrate autonomy modules on flight computers and mission systems.
• Conduct flight trials, performance evaluation, and algorithm optimization under real mission conditions.
• Support development of mission-critical autonomy frameworks for UAV systems.

Skillset/ Experience Required

• Strong foundation in linear and nonlinear state estimation and multi-sensor fusion.
• Expertise in path planning and trajectory optimization for aerial platforms.
• Proficiency in C++ / Python and ROS / ROS2 for robotic system development.
• Experience with aerospace kinematics and dynamics modeling, flight control integration, and navigation system design.
• Hands-on experience with Gazebo / X-Plane / AirSim / Unreal Engine simulators.
• Practical understanding of vision-based SLAM, visual odometry, and obstacle avoidance.
• Strong analytical and debugging skills, with a systems-engineering mindset.
• Exposure to AI-based perception systems.
• Integration of algorithms with embedded flight computers.
• Experience with HIL/SIL test setups and flight telemetry systems.
• Familiarity with DO-178C, DO-254, or other lifecycle processes is a plus.

Educational Qualification

• B.E. / B.Tech / M.Tech / Ph.D. in Aerospace, Robotics, Computer Science, Electrical, or related disciplines.
• Academic or project focus in Autonomous Systems, Estimation, Navigation, or AI-based Robotics is preferred.

Position: Guidance & Navigation Engineer

Experience: 1–3 Years

Location: Bengaluru, Karnataka

Employment Type: Full-time

About the Role

We are seeking a highly motivated Guidance and Navigation Engineer to join our autonomy and avionics team. The role involves developing, implementing, and validating state estimation, navigation, and guidance algorithms for autonomous UAVs operating in both GNSS-available and GNSS-denied environments.

The ideal candidate should have a strong foundation in estimation theory, sensor fusion, and navigation algorithms, along with hands-on experience in implementing these algorithms on embedded or real-time systems.

Key Responsibilities

• Design, develop, and optimise navigation and guidance algorithms for UAVs.
• Develop state estimation algorithms using IMU, GNSS, magnetometer, barometer, cameras, LiDAR, radar, and other onboard sensors.
• Design and implement estimation filters such as: EKF, UKF, Point-mass Filter
• Develop sensor fusion algorithms for robust localisation under degraded or denied GNSS conditions.
• Work on inertial navigation, dead reckoning, visual-inertial odometry (VIO), visual odometry (VO), and multi-sensor navigation systems.
• Develop guidance algorithms for waypoint navigation, path following, trajectory generation, and autonomous mission execution.
• Perform simulation, algorithm validation, and performance analysis using MATLAB/Simulink, Python, or C++.
• Analyse flight logs and sensor data to improve navigation accuracy and system robustness.
• Integrate navigation software with autopilots, embedded processors, and avionics systems.
• Support hardware-in-the-loop (HIL), software-in-the-loop (SIL), and field flight testing.
• Work closely with perception, controls, embedded software, and systems engineering teams.

Required Qualifications

• B.E./B.Tech/M.E./M.Tech in Aerospace Engineering, Robotics, Electronics, Electrical Engineering, Computer Science, Mechatronics, or a related discipline.
• 1–3 years of experience in navigation, estimation, robotics, autonomous systems, or UAV development.
• Strong understanding of: Linear Algebra, Probability and Statistics, Estimation Theory, Kinematics, Coordinate Systems, Control Systems,
• Experience developing estimation filters, especially EKF or UKF.
• Good understanding of IMU error modelling and inertial navigation.
• Experience with Camera, IMU Calibration and Synchronisation
• Experience with multi-sensor fusion.
• Strong programming skills in C++ and Python.
• Experience with MATLAB/Simulink for algorithm development and validation.
• Familiarity with Linux development environments.
• Experience with Git version control.

Preferred Skills

• Experience with Visual-Inertial Odometry (VIO), Visual Odometry (VO), or SLAM with loop closure techniques
• Knowledge of factor graph optimisation (GTSAM, Ceres Solver, g2o, etc.).
• Experience with ROS/ROS2.
• Familiarity with PX4 or ArduPilot.
• Experience working with embedded Linux or ARM-based processors.
• Understanding of UAV flight dynamics and autopilot architectures.
• Experience with flight data analysis and debugging.
• Exposure to airborne software development processes and coding standards (e.g., MISRA C++).

Personal Attributes

• Strong analytical and problem-solving skills.
• Ability to work independently on challenging technical problems.
• Good communication and documentation skills.
• Passion for robotics, autonomous systems, and aerospace technologies.
• Willingness to participate in field trials and flight testing.

This role offers the opportunity to work on cutting-edge UAV autonomy technologies from algorithm development through real-world flight validation.

About us

MyRico builds personal AI agents for enterprise, the copilots and digital employees that make humans more productive. The MyRico agents sit at the intersection of enterprise memory, high-end security, and an ever-expanding set of capabilities. We're a small team shipping fast, and the product is live with real customers today.

The role

Full-time · Bangalore

You'll own the systems that make an autonomous agent trustworthy in production. This is not just prompt engineering, and it's not model training - it's that and all the engineering layers in between: model steering, memory architecture, orchestration design, latency optimization, deterministic vs non-deterministic systems tradeoff, deployment, and operator tooling.

Concretely, the kind of work you'd have done here last week would include enhancing agent memory systems, runtime and scheduling reliability and predictability, adding new capability and tools to deployed agents, operator tools, live system debugging and benchmarking various models for price, latency and quality. And that is just last week. We are a small nimble startup rapidly working to address customer needs in this growing space, so things change rapidly.

What we're looking for

• More than 7 years of software engineering, with real production ownership of distributed or stateful systems - you've been paged for something you built and made it not happen again.
• Strong understanding of LLM based native app building, combining classic and model driven applications to get the best of both. You've built on LLMs beyond demos: agent frameworks, tool use, context management, eval fixtures, and you know why "it worked in the transcript" isn't evidence.
• Python and shell in production settings; comfortable in TypeScript/Node. You write boring, testable code and prefer the standard library to a new dependency.
• Systems taste: append-only logs, idempotent reconciliation, fold-the-events state machines, and read-only debugging surfaces feel like home.
• Evidence discipline: tests before features, claims backed by quoted observations, decisions written down.

Nice to have

• Experience running the combination of multi-tenant and single-tenant / on-prem-style fleets with ability to handle per-customer isolation, upgrade paths, migration compatibility in both setups.
• Security instincts for products that touch highly sensitive data and systems, including things like executives' email, calendars, and messages: least privilege, loopback-only services, secrets that never hit a log.
• You already orchestrate AI coding agents in your own workflow and have opinions about where they break.

How we work

Small team, high trust, written decisions. Designs get adversarial review before code; PRs get automated review driven to zero open findings; features aren't done until verified on a live system. AI agents do a large share of the implementation, your leverage is judgment: framing the problem, freezing the right design, and knowing when the machine is wrong.

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 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

Job Description – Mechatronics Engineer

Position

Mechatronics Engineer

Experience

2 years

Location

Bengaluru, India

About the Role

We are looking for a hands-on Mechatronics Engineer with approximately 2 years of experience to work on the development and integration of intelligent electro-mechanical systems.

The role involves a combination of electronics system assembly and testing, sensors and actuators, control algorithms, estimation algorithms, embedded implementation, system configuration, and hardware-software integration. The ideal candidate should be comfortable working across the boundary between mechanical, electrical, embedded software, and algorithms.

Key Responsibilities

1. System Assembly & Integration

• Assemble and integrate electro-mechanical systems, sensors, actuators, embedded computers, controllers, and associated electronics.
• Perform wiring, connection, sensor installation, and basic electrical integration.
• Support integration of cameras, IMUs, GNSS, encoders, motors, servos, and other sensors/actuators.
• Configure systems for laboratory, ground, and flight testing.
• Troubleshoot hardware, electrical, communication, and integration issues.

2. Electronics Testing & Validation

• Develop and execute test procedures for electronic and mechatronic subsystems.
• Perform functional testing, sensor validation, actuator testing, and system-level testing.
• Use laboratory equipment such as oscilloscopes, multimeters, power supplies, electronic loads, and logic analysers.
• Analyse test data and identify hardware, firmware, sensor, or integration issues.
• Maintain test records, test reports, and issue/defect logs.

3. Control & Estimation Algorithms

• Implement and integrate control algorithms for electro-mechanical systems.
• Work with PID, state-space, feedback control, actuator control, and related control techniques.
• Implement estimation algorithms such as complementary filters, Kalman filters, EKF/UKF, or sensor fusion algorithms.
• Perform sensor calibration, parameter estimation, filtering, and system identification.
• Tune control and estimation parameters based on laboratory and flight-test data.

4. Embedded Implementation

• Implement algorithms on embedded processors and real-time computing platforms.
• Interface sensors and actuators using protocols such as UART, SPI, I²C, CAN, RS-232/485, Ethernet, etc.
• Develop or modify embedded C/C++ code for system integration.
• Debug hardware-software interaction and real-time issues.
• Support optimisation and deployment of algorithms on resource-constrained embedded systems.

5. Configuration & Version Management

• Maintain configuration of hardware, firmware, software, sensors, and system parameters.
• Maintain configuration-controlled parameter files, calibration data, firmware versions, and test configurations.
• Use Git or equivalent version-control systems for software and configuration management.
• Maintain proper traceability between hardware configuration, software version, test results, and system performance.
• Support controlled release of system configurations for testing and demonstrations.

6. System Testing & Field Trials

• Participate in system-level integration, laboratory testing, HIL/SIL testing, and field/flight trials.
• Prepare test setups and test cases based on system requirements.
• Collect and analyse telemetry, sensor, actuator, and performance data.
• Diagnose failures during integration and testing and work with the engineering team to resolve them.
• Support verification and validation activities for production-grade systems.

Required Skills

• B.E./B.Tech/M.Tech in Mechatronics, Electronics, Electrical, Instrumentation, Mechanical Engineering, or a related discipline.
• Approximately 2 years of relevant industry/project experience.
• Strong hands-on experience with electronics system assembly, integration, and testing.
• Understanding of sensors, actuators, motors, servos, and embedded systems.
• Good understanding of control systems and estimation/filtering techniques.
• Experience implementing algorithms in C/C++ and/or Python.
• Familiarity with microcontrollers, embedded processors, and real-time systems.
• Working knowledge of communication protocols such as CAN, UART, SPI, I²C and Ethernet.
• Experience using laboratory test equipment such as oscilloscopes and multimeters.
• Familiarity with Git and configuration/version management.
• Ability to read schematics, datasheets, interface specifications, and technical documentation.
• Strong debugging and problem-solving skills.
• Willingness to work hands-on with hardware and participate in field/flight testing.

Good to Have

• Experience with UAVs, robotics, autonomous systems, gimbals, or avionics.
• Experience with IMU, GNSS, magnetometer, barometer, encoder, camera, or other navigation sensors.
• Experience with EKF/UKF, sensor fusion, visual-inertial estimation, or inertial navigation.
• Familiarity with MATLAB/Simulink.
• Experience with PX4, ArduPilot, ROS/ROS2, or similar platforms.
• Experience with HIL/SIL testing.
• Basic understanding of real-time operating systems.
• Experience with hardware bring-up and PCB-level debugging.
• Familiarity with engineering standards, configuration management, and structured V&V processes.

Desired Attributes

• Hands-on engineer who enjoys working with both hardware and software.
• Comfortable moving between mechanical assembly, electronics, algorithms, and embedded implementation.
• Strong debugging mindset with an ability to systematically isolate problems.
• Good understanding of engineering fundamentals rather than dependence on pre-built libraries or tools.
• Able to work independently on assigned modules while collaborating closely with multidisciplinary teams.
• Comfortable working in a fast-paced R&D environment involving prototyping, testing, iteration, and field trials.
• Strong documentation and communication skills.

Typical Technology Environment

Sensors & Actuators: IMU, GNSS, magnetometer, encoders, cameras, motors, servos

Embedded: Microcontrollers, ARM processors, embedded Linux/RTOS

Algorithms: PID, state estimation, Kalman filtering, sensor fusion, system identification

Programming: C/C++, Python, MATLAB/Simulink

Testing: Oscilloscope, logic analyser, multimeter, power supply, HIL/SIL

This is a hands-on R&D engineering role suited for an engineer who wants to work on complete intelligent systems rather than a narrowly defined mechanical or electronics function. The engineer will contribute across assembly → integration → algorithm implementation → configuration → testing → debugging → field validation, with particular emphasis on UAV and autonomous-system applications.

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

AuxoAI is hiring a Senior Applied Scientist to design and deploy production-grade AI agents capable of structured reasoning, planning, and decision-making.

This role focuses on building reasoning and decision systems using planning algorithms, search methods, and optimization techniques, rather than chatbot or RAG-style application development. The ideal candidate will design intelligent agent architectures that combine LLM-based reasoning with classical planning, search algorithms, and optimization techniques, operating reliably in real-world environments with constraints around latency, cost, uncertainty, and limited context windows.

You will work on advanced AI systems that power autonomous workflows, decision engines, and tool-driven agent ecosystems.

You will also work on problems where existing architectures may not be sufficient, and will be expected to experiment with new approaches that combine machine learning, graph algorithms, and classical AI techniques to build reliable, production-grade systems.

Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)

Responsibilities:

• Design and architect modular AI agent frameworks incorporating skill decomposition, tool orchestration, and persistent state tracking.
• Implement planning and search algorithms such as Monte Carlo Tree Search (MCTS), beam search, A search, heuristic search, and graph-based planning approaches* to support complex decision-making tasks.
• Develop decision-making loops that balance trade-offs between exploration vs. exploitation, cost vs. accuracy, and latency vs. reasoning depth.
• Build structured memory systems including episodic memory stores, semantic memory layers, and vector-based memory with optimized retrieval strategies.
• Design tool-calling architectures with strong execution validation, retry mechanisms, and failure recovery strategies.
• Develop evaluation frameworks to measure agent performance using task success metrics, rollout simulations, and multi-sample validation approaches.
• Improve agent performance through techniques such as distillation, synthetic trajectory generation, prompt compression, and context pruning.
• Deliver production-ready agent systems that meet operational requirements around reliability, cost efficiency, throughput, and observability.

Requirements

• 3-10 years of experience building machine learning or AI systems in production environments.
• Strong experience implementing search or planning algorithms beyond basic use cases, including tree search or heuristic-based planning approaches.
• Hands-on experience with Monte Carlo Tree Search (MCTS) or related decision-making frameworks.
• Strong understanding of state-space representations, heuristic design, and decision boundary trade-offs.
• Experience building or extensively customizing agent frameworks for real-world applications.
• Hands-on experience designing tool-use or function-calling architectures under practical system constraints.
• Strong Python engineering skills with a focus on scalable and reliable system design.
• 
  

Candidates whose primary experience is limited to RAG pipelines, prompt engineering, or chatbot frameworks without deeper algorithmic or systems work may not be a fit for this role.

Nice to Have:

• Experience with reinforcement learning techniques such as policy gradients, value estimation, or reward modeling.
• Experience building multi-agent or collaborative agent systems.
• Experience designing evaluation frameworks for agent robustness and reliability.
• Experience optimizing LLM inference pipelines for latency, throughput, and cost efficiency.
• Familiarity with distributed task orchestration systems and large-scale AI workflow management.

Power Electric Vehicles with embedded software for battery management and autonomous driving.

What you'll do:

• Develop BMS algorithms (SOC/SOH estimation)
• Implement CAN bus communication protocols
• Code motor control algorithms (FOC, sensorless)
• Build ADAS features (ultrasonic parking, vision)
• HIL testing with Vector tools
• Optimize for automotive-grade reliability (AUTOSAR)

What we need:

• C/C++, Embedded Linux/RTOS
• Microcontroller experience (STM32, NXP)
• Control systems or automotive interest
• Debugging skills (oscilloscopes, logic analyzers)

Future-proof skills:

• Work on actual EV prototypes
• Portfolio for Tata, Mahindra EV teams
• Automotive cybersecurity exposure