Robotics Enginner

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.

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.

Technical Lead – Embedded Software Application Projects

link: https://www.ziliconcloud.com/careers

ZILICONCLOUD PRIVATE LIMITED is looking for an experienced Technical Lead with 5–8 years of industry experience in Embedded Systems, IoT, AI, Cloud, and Software Engineering.

The candidate will lead Embedded, IoT, Edge AI, and Cloud projects, define system architecture, convert requirements into technical tasks, and ensure successful project execution and delivery.

Key Responsibilities

• Design modular system architectures for Embedded, IoT, Edge AI, Cloud, REST APIs, and dashboards.
• Convert requirements into clear tasks, milestones, and deliverables.
• Track project progress, manage technical risks, and ensure on-time delivery.
• Guide engineers on coding standards, Git, testing, debugging, and documentation.
• Troubleshoot issues across hardware, firmware, IoT, cloud, backend, and UI.
• Support system integration, testing, debugging, and performance improvement.
• Review technical designs, code, and test results.
• Lead prototype development, integration, technical reviews, and demonstrations.
• Mentor young engineers and explain complex technical concepts in a simple and practical way.
• 
  

Required Skills

C/C++, Python, JavaScript/TypeScript, Linux, FreeRTOS, Microcontrollers, REST APIs, MQTT, Git, Embedded Software, IoT, and system debugging.

Preferred: AWS IoT, Microsoft Azure, ThingsBoard, OpenCV, TensorFlow Lite (TFLite), React, Flutter, or FastAPI.

Education

B.E./B.Tech/M.E./M.Tech in ECE, CSE, Embedded Systems, Mechatronics, or a related field.

📍 Location: East Tambaram, Chennai, Tamil Nadu

💼 Experience: 5–8 Years

🕒 Employment Type: Full-Time

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

Senior Agentic Engineer — Ai1 Platform (Operations)

Team: Operations · Type: Full-time · Location: Fully remote (global, async-first)

Who we are

MyZone AI builds and runs Ai1 — a managed, multi-agent AI platform that gives each client their own isolated, always-on team of AI agents working across the channels and tools they already use. We're a small, AI-first, high-trust team that ships like a much bigger one. We work fully remote and async — what you ship and how clearly you write matter more than your hours.

The role

You'll join the Operations team. 

• Agentic engineering — complex agent skills and workflows, multi-agent orchestration, custom integrations, and the prompting and guardrails that make autonomous agents reliable.

What you'll do

Build agents that do real work

• Design complex, reusable skills and multi-step recipes that automate entire business processes — production automations, not demos.
• Architect multi-agent workflows: delegation, parallel execution, and agents that hand off and reassemble work.
• Build custom MCP connectors and API integrations for any tool that doesn't have one yet.
• Engineer robust prompts, human-in-the-loop controls, and built-in QA so automations are safe to run autonomously.
• Ship automations as self-contained installers that deploy across many client instances with zero rework.

Own application code end-to-end

• Own one or more services in our modular platform (Node/Express backends, React frontends) — schema, API, and UI.
• Ship features across CRM, operations, pipeline, reporting, onboarding, assessments, and chatbots.
• Contribute to our Next.js portal (Next.js 15, TypeScript, Prisma, PostgreSQL).
• Keep your components healthy: clean migrations, green CI, solid tests.

Set the bar

• Work clean: feature branches, real PRs, green CI, small changes, semantic versioning.
• Be security-conscious by default — credentials are treated like credit-card numbers; high-risk actions route through human review.
• Mentor, set patterns, and raise the team's technical level.

Who we're looking for

Must-haves

• 5+ years of professional software engineering with strong full-stack depth: Node.js / TypeScript and modern React.
• Hands-on experience building AI agents in production — tool/function calling, orchestration, memory, and evaluation. You've shipped something that uses an LLM to reliably do real work.
• Fluency with the Anthropic / Claude API (or equivalent) and real depth in prompt/context engineering.
• Strong with PostgreSQL and pragmatic API design.
• Able to own a service end-to-end and ship independently in a low-oversight, async environment.
• Excellent written communication and sound judgment around security and autonomous actions.

Bonus

• Built MCP connectors, agent frameworks, or similar orchestration layers.
• Next.js 15, Prisma, Vercel, monorepos (pnpm / Turborepo).
• Light DevOps: Linux VPS, PM2, nginx, CI.
• Used coding agents (Claude Code–style tools) to build real things.
• Integrations: Slack/Teams apps, Twilio, Google Workspace, GitHub.

How we work

Fully remote, global, async-first — no required location. Small, high-trust, and low-bureaucracy, so you'll own real work and thrive without hand-holding. Everyone here builds automations, versions their work, and maintains what they ship.

MyZone AI is an equal-opportunity employer. We hire the best person for the work, wherever they are.

The Role:

We are seeking a highly skilled Sr Embedded Software Engineer (Python & C++) to manage and improve the software development lifecycle for device firmware systems. The primary focus of this role is to ensure firmware operational reliability, fail-safe implementation, certification compliance, and robust production deployment.

This role is ideal for an engineer experienced in system-level software, firmware validation, testing automation, and production readiness — but not focused on low-level hardware design.

Experience: 6-10 years

Job Location: Hyderabad

Job Type: Permanent

CORE FOCUS AREAS

• Ensure firmware operates reliably in production environments

• Implement and validate fail-safe mechanisms and fallback logic

• Maintain certification compliance across firmware releases

• Drive robust, repeatable production deployment pipelines

• Support field debugging and OTA update validation

IDEAL CANDIDATE PROFILE

• Strong hands-on experience in Python and C++ development

• Background in system-level software and firmware validation

• Experience with testing automation and production readiness

• Comfortable working closely with embedded engineers

• Not required to have low-level hardware design expertise

KEY RESPONSIBILITIES

FIRMWARE OPERATIONAL STABILITY

• Ensure firmware operates reliably in production environments

• Implement and validate fail-safe mechanisms and fallback logic

• Monitor watchdog systems, timeout handling & safe state transitions

• Work closely with embedded engineers to validate firmware behavior

PYTHON & C++ DEVELOPMENT

• Develop firmware communication layers & device control applications

• Build diagnostic tools and test automation frameworks

• Optimize performance and memory handling in C++ applications

• Develop production-ready Python tools for deployment, logging & validation

FAIL-SAFE & SAFETY IMPLEMENTATION

• Implement safe boot validation, error recovery & redundancy logic

• Build communication retry systems & safe shutdown protocols

• Design state machines for controlled device operation

• Ensure safe-state transitions on power, comms or hardware failure

PRODUCTION DEPLOYMENT & VALIDATION

• Create secure and repeatable firmware deployment pipelines

• Implement boot image validation, signature verification & rollback

• Develop health monitoring and diagnostic utilities & CI/CD Pipelines

• Support field debugging and OTA update validation

Linux Environment

• Work in Linux-based environments for firmware development, debugging, and deployment — including shell scripting, process/service management, and system diagnostics.

• Own unit testing, integration testing & production release management

• Ensure code quality and compliance with internal standards

IoT + AI

Building the tech behind India's Reverse Vending Machines

SUCCESS METRICS

• Firmware reliability — stable, uninterrupted operation in production environments

• Fail-safe coverage — validated fallback logic, redundancy & safe-state transitions

• Linux Environment - Use Linux for development till deployment

• Deployment success rate — secure, repeatable pipelines with clean rollbacks

• Code & release quality — test coverage, code review discipline & CI/CD health

• Field performance — OTA update success and turnaround on field debugging