Inferigence Quotient
https://inferq.comAbout
Deep Tech Startup Focusing on Autonomy and Intelligence for Unmanned Systems. Guidance and Navigation, AI-ML, Computer Vision, Information Fusion, LLMs, Generative AI, Remote Sensing
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Jobs at Inferigence Quotient
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.
The selected candidate is required to fine tune LLM models, train them in distributed mode using SLURM framework, perform the necessary data engineering, training process monitoring and tuning, analysis, and documentation.
Python
NodeJS (Node.js)
Docker
Javascript3-5 years of experience as full stack developer with essential requirements on the following technologies: FastAPI, JavaScript, React.js-Redux, Node.js, Next.js, MongoDB, Python, Microservices, Docker, and MLOps.
Experience in Cloud Architecture using Kubernetes (K8s), Google Kubernetes Engine, Authentication and Authorisation Tools, DevOps Tools and Scalable and Secure Cloud Hosting is a significant plus.
Ability to manage a hosting environment, ability to scale applications to handle the load changes, knowledge of accessibility and security compliance.
Testing of API endpoints.
Ability to code and create functional web applications and optimising them for increasing response time and efficiency. Skilled in performance tuning, query plan/ explain plan analysis, indexing, table partitioning.
Expert knowledge of Python and corresponding frameworks with their best practices, expert knowledge of relational databases, NoSQL.
Ability to create acceptance criteria, write test cases and scripts, and perform integrated QA techniques.
Must be conversant with Agile software development methodology. Must be able to write technical documents, coordinate with test teams. Proficiency using Git version control.
Python
Deep Learning
Machine Learning (ML)
C++AI based systems design and development, entire pipeline from image/ video ingest, metadata ingest, processing, encoding, transmitting.
Implementation and testing of advanced computer vision algorithms.
Dataset search, preparation, annotation, training, testing, fine tuning of vision CNN models. Multimodal AI, LLMs, hardware deployment, explainability.
Detailed analysis of results. Documentation, version control, client support, upgrades.
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