AI/ML Engineer

Job Description

Build AI for autonomous vessels, ground robots, and applied products for defence, naval, and port customers. Cover perception, sensor fusion, edge deployment, simulation, and LLM-based applications. Take models from training through field trials so they run on vessels and robots, not just on benchmarks.

Key Responsibilities

  • Develop perception pipelines for detection, segmentation, tracking, and classification using camera, thermal, radar, and lidar data
  • Build sensor fusion and state estimation systems using Kalman filters, Bayesian fusion, and multi-target tracking
  • Contribute to localisation, mapping, path planning, and collision avoidance in ROS 2
  • Work on SLAM or visual-inertial odometry for GPS-denied navigation
  • Optimize and deploy models on edge hardware such as NVIDIA Jetson using TensorRT, ONNX, and quantization
  • Build data pipelines, labelling workflows, training infrastructure, and evaluation frameworks
  • Track experiments, version models and datasets, and monitor model performance after deployment
  • Build LLM applications, RAG pipelines, and agentic workflows, including fully offline and air-gapped setups
  • Contribute to AI features for digital twins, predictive maintenance, anomaly detection, and decision support
  • Work with time-series, tabular, and geospatial data where projects need it
  • Use simulators such as Gazebo, Isaac Sim, Unity-based tools, and CARLA for testing and synthetic data generation
  • Take part in field trials to collect data and validate systems in real conditions

Candidate Requirements

  • B.E./B.Tech/M.Tech in CS, IT, E&TC, AI/ML, or a related field, with 1-2 years of hands-on ML experience
  • Strong Python, with working knowledge of C++
  • Solid grounding in machine learning and deep learning fundamentals, linear algebra, probability, and statistics
  • Experience with PyTorch (or TensorFlow) and modern computer vision models such as YOLO, transformers, and segmentation models
  • Understanding of computer vision basics, including camera models, calibration, and coordinate transforms
  • At least one model deployed to production or to an edge device
  • Comfortable with Linux, Git, Docker, and REST APIs
  • Indian nationality required; background verification may apply for defence projects

Good to Have

  • ROS / ROS 2 experience
  • Point cloud processing (Open3D, PCL) or radar signal processing
  • Knowledge of planning algorithms (A*, Hybrid A*, RRT, Frenet, MPC)
  • Experience with LangChain / LangGraph, vector databases, and local LLM serving (vLLM, Ollama, llama.cpp)
  • Reinforcement learning or imitation learning for robotics
  • Publications, Kaggle work, or open-source contributions

Knowledge Requirement

  • Python / C++
  • PyTorch / TensorFlow / OpenCV
  • YOLO / Transformers / Object Detection / Tracking / Segmentation
  • Sensor Fusion / Kalman Filters / SLAM / Visual Odometry
  • Lidar / Radar / Path Planning
  • NVIDIA Jetson / TensorRT / ONNX / Edge AI
  • MLOps / Docker / Git / Linux / REST APIs
  • LLM / RAG / Generative AI / Agentic AI
  • Gazebo / Isaac Sim / CARLA / Unity
  • Anomaly Detection / Time Series / Digital Twin

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