
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
We are seeking a highly skilled Qt/QML Engineer to design and develop advanced GUIs for aerospace applications. The role requires working closely with system architects, avionics software engineers, and mission systems experts to create reliable, intuitive, and real-time UI for mission-critical systems such as UAV ground control stations, and cockpit displays.
Key Responsibilities
- Design, develop, and maintain high-performance UI applications using Qt/QML (Qt Quick, QML, C++).
- Translate system requirements into responsive, interactive, and user-friendly interfaces.
- Integrate UI components with real-time data streams from avionics systems, UAVs, or mission control software.
- Collaborate with aerospace engineers to ensure compliance with DO-178C, or MIL-STD guidelines where applicable.
- Optimise application performance for low-latency visualisation in mission-critical environments.
- Implement data visualisation (raster and vector maps, telemetry, flight parameters, mission planning overlays).
- Write clean, testable, and maintainable code while adhering to aerospace software standards.
- Work with cross-functional teams (system engineers, hardware engineers, test teams) to validate UI against operational requirements.
- Support debugging, simulation, and testing activities, including hardware-in-the-loop (HIL) setups.
Required Qualifications
- Bachelor’s / Master’s degree in Computer Science, Software Engineering, or related field.
- 1-3 years of experience in developing Qt/QML-based applications (Qt Quick, QML, Qt Widgets).
- Strong proficiency in C++ (11/14/17) and object-oriented programming.
- Experience integrating UI with real-time data sources (TCP/IP, UDP, serial, CAN, DDS, etc.).
- Knowledge of multithreading, performance optimisation, and memory management.
- Familiarity with aerospace/automotive domain software practices or mission-critical systems.
- Good understanding of UX principles for operator consoles and mission planning systems.
- Strong problem-solving, debugging, and communication skills.
Desirable Skills
- Experience with GIS/Mapping libraries (OpenSceneGraph, Cesium, Marble, etc.).
- Knowledge of OpenGL, Vulkan, or 3D visualisation frameworks.
- Exposure to DO-178C or aerospace software compliance.
- Familiarity with UAV ground control software (QGroundControl, Mission Planner, etc.) or similar mission systems.
- Experience with Linux and cross-platform development (Windows/Linux).
- Scripting knowledge in Python for tooling and automation.
- Background in defence, aerospace, automotive or embedded systems domain.
What We Offer
- Opportunity to work on cutting-edge aerospace and defence technologies.
- Collaborative and innovation-driven work culture.
- Exposure to real-world avionics and mission systems.
- Growth opportunities in autonomy, AI/ML for aerospace, and avionics UI systems.
We are looking for a Python Backend Developer to design, build, and maintain scalable backend services and APIs. The role involves working with modern Python frameworks, databases (SQL and NoSQL), and building well-tested, production-grade systems.
You will collaborate closely with frontend developers, AI/ML engineers, and system architects to deliver reliable and high-performance backend solutions.
Key Responsibilities
- Design, develop, and maintain backend services using Python
- Build and maintain RESTful APIs using FastAPI
- Design efficient data models and queries using MongoDB and SQL databases (PostgreSQL/MySQL)
- Ensure high performance, security, and scalability of backend systems
- Write unit tests, integration tests, and API tests to ensure code reliability
- Debug, troubleshoot, and resolve production issues
- Follow clean code practices, documentation, and version control workflows
- Participate in code reviews and contribute to technical discussions
- Work closely with cross-functional teams to translate requirements into technical solutions
Required Skills & Qualifications
Technical Skills
- Strong proficiency in Python
- Hands-on experience with FastAPI
- Experience with MongoDB (schema design, indexing, aggregation)
- Solid understanding of SQL databases and relational data modelling
- Experience writing and maintaining automated tests
- Unit testing (e.g., pytest)
- API testing
- Understanding of REST API design principles
- Familiarity with Git and collaborative development workflows
Good to Have
- Experience with async programming in Python (async/await)
- Knowledge of ORMs/ODMs (SQLAlchemy, Tortoise, Motor, etc.)
- Basic understanding of authentication & authorisation (JWT, OAuth)
- Exposure to Docker / containerised environments
- Experience working in Agile/Scrum teams
What We Value
- Strong problem-solving and debugging skills
- Attention to detail and commitment to quality
- Ability to write testable, maintainable, and well-documented code
- Ownership mindset and willingness to learn
- Teamwork
What We Offer
- Opportunity to work on real-world, production systems
- Technically challenging problems and ownership of components
- Collaborative engineering culture
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 recruiter has not been active on this job recently. You may apply but please expect a delayed response.
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.
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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