Robotics Engineer

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.

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.

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 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

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.

Core Responsibilities

Operational Tools Architecture & Feature Planning 

• Own the feature roadmap for operational tools — Odoo, Redmine, GitHub, and adjacent systems — from business-process discovery through design, planning, and phased delivery 
• Serve as the subject-matter expert on how business processes (deal onboarding, delivery, support, finance, engineering operations) map onto tool capabilities, and where the gaps are 
• Design cross-tool workflows and integrations so that work items, code, and business records flow between systems as one coherent operational fabric 

Agentic Implementation & Modernization 

• Design agent-operable surfaces on each tool: typed, secure APIs, Model Context Protocol (MCP) servers, and webhook-driven automation that let AI agents read, create, and resolve operational work safely 
• Lead incremental modernization of legacy tool deployments — upgrading versions, retiring brittle customizations, and replacing manual processes with agentic workflows without disrupting live operations 
• Optimize agentic loops that operate on the tools for cost, speed, and integrity, with guardrails, audit trails, and human-in-the-loop checkpoints where they matter 

Plugin & Extension Engineering 

• Architect and build Redmine plugins in Ruby on Rails, Odoo modules, and GitHub Apps/Actions that extend the products cleanly rather than forking them 
• Engineer enhancements to be upgrade-safe across product versions — tracking upstream releases, isolating customizations behind stable interfaces, and planning migration paths 
• Prioritize contract-first API design between human intent, agent execution, and the underlying tools 

Governance & Quality Control 

• Act as the architectural reviewer for changes to Central tooling, including AI-generated pull requests and agent-authored configuration 
• Mandate testing and characterization coverage around customizations so upgrades and agentic changes land deterministically 
• Establish operational standards — access, data integrity, observability — for agents acting inside business-critical systems 

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 — able to translate how a business runs into how a tool should behave 
• 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 
• Commitment to clean, tested, production-grade systems — including when the author of the code is an agent 

Preferred Qualifications 

• Python and Odoo module development experience; PostgreSQL fluency 
• Experience modernizing or migrating legacy tool deployments across major versions 
• Background in SaaS transformation, scale-up, or PE-backed environments 

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.