Robotics Engineer at Inferigence Quotient · Bengaluru (Bangalore) · 1 - 3 years · ₹6L - ₹12L / yr · Bootstrapped · Posted 19 Sep 2026
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.

About Inferigence Quotient
Similar jobs (10)
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.
Role: Software Developer
Employment Type: Full Time
Location: Gurugram, India
Educational Qualification: BE/BTech/ M.Tech / MS in Software Engineer
Work Experience: 6-8+ years of relevant work experience
Role Description:
Design and develop software for satellite systems, including onboard flight software and ground segment applications, ensuring reliability and real-time performance. Collaborate with hardware, AOCS, and mission teams to implement, test, and integrate software across the mission lifecycle. Support verification, validation, and in-orbit operations for robust and mission-critical performance.
Responsibilities & Duties:
- Design, develop, and maintain onboard flight software (FSW) and ground segment applications for satellite missions
- Develop real-time, embedded software for spacecraft subsystems (AOCS, EPS, payload, communication)
- Implement software in languages such as C/C++, Python, and embedded C for high-reliability systems
- Design software architecture, modules, and interfaces aligned with system requirements and mission objectives
- Develop drivers and low-level firmware for hardware interfaces (SPI, I2C, UART, CAN, SpaceWire, Ethernet)
- Work with real-time operating systems (RTOS) such as FreeRTOS or equivalent
- Implement communication protocols for telemetry, telecommand, and data handling
- Collaborate with hardware, AOCS, RF, and systems teams for seamless hardware-software integration
- Develop simulation tools, test scripts, and automation frameworks using Python or MATLAB
- Perform software verification and validation (V&V), including unit testing, integration testing, and system testing
- Develop and execute Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) test environments
- Perform code reviews, static analysis, and debugging to ensure reliability and performance
- Optimize software for real-time performance, memory usage, and fault tolerance
- Implement fault detection, isolation, and recovery mechanisms
- Support integration, system testing, and environmental testing (EMI/EMC, thermal vacuum, vibration)
- Develop and maintain technical documentation (design documents, interface control documents, test reports)
- Participate in design reviews (SRR, PDR, CDR, TRR) and technical discussions
- Support launch operations, commissioning, and in-orbit software updates and anomaly resolution
- Utilize version control and collaboration tools such as Git
- Work within structured development processes (Agile/Waterfall/Sprint) and configuration management systems
- Troubleshoot software and system-level issues and perform root cause analysis
Desirable Skills & Certifications:
- Strong proficiency in C/C++ and Python for embedded and system-level software development
- Experience with real-time operating systems such as FreeRTOS or equivalent RTOS platforms
- Familiarity with spacecraft communication protocols (UART, SPI, I2C, CAN, SpaceWire, Ethernet) and telemetry/telecommand systems
- Experience in Software-in-the-Loop (SIL), Hardware-in-the-Loop (HIL), and simulation-based verification
- Knowledge of space software standards and practices (ECSS, NASA, ISRO, MISRA C guidelines)
- Proficiency in version control and development workflows using Git and CI/CD practices
- Understanding of embedded systems, firmware development, and hardware-software integration
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.
Position Title: Real-Time Computer Vision & Edge AI Engineer (Founding Engineering Team / Core LLD)
Reporting Structure: High-Level AI Architect (Principal ML Scientist, Google)
Domain: Sub-16ms Edge AI, 3D Pose & Shape Estimation (SMPL-X), TensorRT C++ Inference, Zero-Copy Systems
Performance Benchmark: Hard locked 60 FPS (<16.6 ms total frame budget) on dedicated RTX hardware
1. Position Overview & Architecture
We are building a proprietary, ultra-low-latency spatial computing platform centered on high-fidelity 100% 3D Digital Twin architecture and real-time human digitization.
In this role, you will serve as the Low-Level Design (LLD) Core AI Engineer, working directly alongside a Lead AI Scientist from Google. Your primary mandate is to solve complex surface occlusion and volumetric estimation challenges by building an ultra-fast C++ inference pipeline. This system must accurately regress a subject's true underlying 3D body shape and skeletal pose directly from a live camera feed. You will deploy models that extract parametric data (SMPL-X shape/pose parameters) and bridge these joint rotations seamlessly into our Vulkan graphics engine via shared GPU memory.
System Architecture:
● Hardware Camera Ingestion: (V4L2 / GStreamer / CUDA)
↓ Raw RGB Frames (Zero CPU Copy)
● Edge AI Inference: (TensorRT / ONNX C++ API for 3D Pose Tracking, Kinematic Anchoring, SMPL-X Shape)
↓ 3D Skeletal Transforms & Shape Parameters
● Zero-Copy Shared Memory: (CUDA-Vulkan Bridge feeding directly into OpenRigLogic / MetaHuman Engine)
2. Key Responsibilities & Deliverables
A. Real-Time 3D Pose & Shape Estimation
● Deploy and optimize state-of-the-art 3D human body reconstruction models (e.g., Shapy, SMPLify-X, CLIFF) to accurately regress the user's underlying skeletal structure and body volume, effectively bypassing unpredictable surface topologies and complex environmental occlusions.
● Extract mathematically stable shape parameters (β) and pose parameters (θ) to drive the skeletal hierarchy of a high-fidelity digital avatar.
B. Edge Inference Pipeline (TensorRT)
● Translate Python-based research models into production-grade C++ inference engines using NVIDIA TensorRT and ONNX Runtime.
● Implement INT8/FP16 quantization, layer fusion, and custom CUDA plugins to ensure the entire AI inference pass executes within a strict <10 ms budget per frame.
C. Temporal Smoothing & Anti-Jitter Kinematics
● Implement highly optimized temporal filters (Kalman filters, One-Euro filters, optical flow tracking) in native C++ to eliminate all high-frequency jitter from the output joint rotations before they reach the graphics engine.
● Ensure kinematic constraints (e.g., fixed bone lengths) are strictly maintained to prevent the digital asset from stretching or warping dynamically.
D. Zero-Copy Ingestion & Engine Synchronization
● Build hardware-accelerated video capture pipelines using V4L2 or GStreamer to ingest raw camera frames directly into GPU memory.
● Bridge the output coordinate data and transformation matrices to the graphics team using POSIX shared memory and CUDA-Vulkan interop (VK_KHR_external_memory_fd), eliminating CPU staging overhead.
3. Technical Qualifications & Tech Stack
● Core Programming: Production-level Modern C++ (C++17/20), Python (strictly for model training/validation), and CUDA C/C++.
● AI & Acceleration Frameworks: NVIDIA TensorRT, ONNX Runtime (C++ API), PyTorch.
● Computer Vision Libraries: OpenCV (CUDA backend), MediaPipe C++ bindings.
● Mathematical Foundations: 3D Kinematics, Matrix Transformations, Quaternions/Euler angles, statistical body modeling (SMPL/SMPL-X architecture).
● Systems Architecture: Low-latency memory management, multi-threading (std::jthread, lock-free queues), SIMD vectorization.
4. Relevant Projects & Demonstrable Experience (Preferred)
Candidates will be preferred if they present functional codebases, GitHub repositories, or thesis work covering:
● Real-Time Body Fitting / Pose Estimation: Practical experience deploying 3D human pose or shape reconstruction models on live video feeds.
● TensorRT / C++ Deployment: Demonstrable experience stripping a PyTorch model out of Python and running it natively in C++ using TensorRT or ONNX, ideally with custom CUDA layers or INT8 calibration.
● High-Throughput Vision Pipelines: Built a C++ video processing pipeline that aggressively minimizes latency and avoids memory garbage collection pauses.
● Kinematics & Smoothing: Applied mathematical filters to raw sensor or AI data to produce smooth, mechanically accurate 3D rotations.
5. Compensation & Engagement Structure
● Compensation: ₹1,50,000 to ₹2,00,000/month
● Mentorship: Direct architectural guidance, algorithm review, and technical leadership from a Principal ML Scientist at Google.
● Hardware: Dedicated high-end workstation equipped with discrete NVIDIA RTX hardware.
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.
We are building an advanced, AI-driven multi-agent software system designed to revolutionize task automation and code generation. This is a futuristic AI platform capable of:
✅ Real-time self-coding based on tasks
✅ Autonomous multi-agent collaboration
✅ AI-powered decision-making
✅ Cross-platform compatibility (Desktop, Web, Mobile)
We are hiring a highly skilled **AI Engineer & Full-Stack Developer** based in India, with a strong background in AI/ML, multi-agent architecture, and scalable, production-grade software development.
### Responsibilities:
- Build and maintain a multi-agent AI system (AutoGPT, BabyAGI, MetaGPT concepts)
- Integrate large language models (GPT-4o, Claude, open-source LLMs)
- Develop full-stack components (Backend: Python, FastAPI/Flask, Frontend: React/Next.js)
- Work on real-time task execution pipelines
- Build cross-platform apps using Electron or Flutter
- Implement Redis, Vector databases, scalable APIs
- Guide the architecture of autonomous, self-coding AI systems
### Must-Have Skills:
- Python (advanced, AI applications)
- AI/ML experience, including multi-agent orchestration
- LLM integration knowledge
- Full-stack development: React or Next.js
- Redis, Vector Databases (e.g., Pinecone, FAISS)
- Real-time applications (websockets, event-driven)
- Cloud deployment (AWS, GCP)
### Good to Have:
- Experience with code-generation AI models (Codex, GPT-4o coding abilities)
- Microservices and secure system design
- Knowledge of AI for workflow automation and productivity tools
Join us to work on cutting-edge AI technology that builds the future of autonomous software.
AuxoAI is hiring a Senior Applied AI Engineer to design and deploy production-grade computer vision systems that operate reliably in real-world environments.
This role focuses on building end-to-end visual intelligence systems, combining deep learning, classical computer vision techniques, and multimodal models. It is not limited to model training and requires strong ownership of system design, deployment, and real-world performance.
You will work on systems that perform perception, understanding, and reasoning over visual data, and integrate these capabilities into larger AI platforms and agent-based workflows.
You will also work on problems where existing approaches may not be sufficient, and will be expected to combine deep learning, geometric methods, and multimodal reasoning to build robust, production-grade systems.
Location – Mumbai / Bangalore / Hyderabad / Gurgaon (Hybrid – 3 days per week in office)
Responsibilities:
- Design and deploy computer vision systems for tasks such as:
- Object detection, segmentation, and tracking
- Scene understanding and structured perception
- Video understanding and temporal reasoning
- Build and optimize models using architectures such as:
- CNNs (ResNet, EfficientNet)
- Vision Transformers (ViT, Swin, DeiT)
- Detection/segmentation models (YOLO, DETR, Mask R-CNN)
- Develop multimodal systems combining vision and language:
- CLIP-style models
- Vision-language models (VLMs)
- Visual grounding and captioning systems
- Implement algorithms for:
- Multi-object tracking (SORT, DeepSORT, ByteTrack)
- Feature matching and representation learning
- Temporal modeling (RNNs, Transformers for video)
- Apply geometric and classical computer vision methods where relevant:
- Camera calibration
- Epipolar geometry
- Pose estimation
- 3D reconstruction or depth estimation
- Optimize systems for:
- Low-latency, real-time inference
- Throughput and scalability
- Edge and distributed deployment
- Design and build data pipelines for:
- Annotation workflows
- Dataset curation
- Synthetic data generation
- Integrate vision systems into:
- Multimodal AI pipelines
- Agent-based systems
- Decision-making workflows
Requirements:
- 5+ years of experience building computer vision systems in production environments
- Strong experience with deep learning frameworks (PyTorch / TensorFlow)
- Hands-on experience with:
- Detection, segmentation, or tracking systems
- Model training, fine-tuning, and evaluation
- Strong understanding of:
- Representation learning
- Loss functions (contrastive loss, focal loss, etc.)
- Evaluation metrics (mAP, IoU, precision/recall)
- Experience building and deploying end-to-end vision systems, not just training models
Candidates whose primary experience is limited to academic projects or model experimentation without real-world deployment may not be a fit for this role.
Nice to Have:
- Experience with multimodal systems (vision + language)
- Familiarity with models such as:
- CLIP, BLIP, Flamingo, or similar
- Experience with 3D vision:
- NeRFs
- SLAM
- Point clouds
- Experience with video understanding:
- Action recognition
- Event detection
- Experience building data engines:
- Active learning
- Hard negative mining
- Experience working with large-scale datasets and distributed training pipelines
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
Position: Computer Vision Engineer
Experience: 2–3 Years
Location: Bengaluru, Karnataka
Employment Type: Full-time
About the Role
We are seeking a highly motivated Computer Vision Engineer to join our autonomy and avionics team. The role involves developing, implementing, and validating computer vision models and algorithms and pipelines for UAVs operating in both GNSS-available and GNSS-denied environments.
The ideal candidate should have a strong foundation in theory of deep learning and machine learning, strong understanding of electromagnetic spectrum, imaging fundamentals, camera principles, and mathematical concepts with hands-on experience in implementing these algorithms on embedded or real-time systems.
Key Responsibilities
- Design, develop, and optimise AI Models
- Make custom CNNs/ modify existing CNNs to suit specific problems at hand
- Handle end-to-end training flow
- Implement end to end inference pipelines on standard PCs as well as on embedded systems
- Understand performance benchmarks and assess the accuracy and inference times
- Implement traditional image processing algorithms
- Factor the code to leverage underlying hardware architecture
- Prune the networks for efficiency
- Integrate the system within the application framework using C++
- Work closely with perception, controls, embedded software, and systems engineering teams.
Required Qualifications
- B.E./B.Tech/M.E./M.Tech in Computer Science and Engineering, Electronics, ECE, Mechatronics, or a related discipline.
- 2–3 years of experience in relevant area
- Strong understanding of: Linear Algebra, Probability and Statistics, AI-ML-DL fundamentals, Image processing, Camera Functioning
- Strong programming skills in C++ and Python.
- Experience with MATLAB for algorithm development and validation.
- Familiarity with Linux development environments.
- Experience with Git version control.
Preferred Skills
- Experience with Camera, IMU Calibration and Synchronisation
- Experience with multi-sensor fusion.
- Experience working with NVIDIA devices
- Experience on FPGA will be an added advantage
- Full understanding of Git functionality
- 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 solving challenging problems
- Willingness to participate in field trials and flight testing.
- Team playwe







