Overview

The Senior Data Scientist (Computer Vision, Robotics and Autonomy) will develop, test, and deploy machine learning, perception, and autonomy solutions for inspection, navigation, intervention, and related operational needs.

Responsibilities

• Develop, test, and integrate computer vision and robotic-perception components for detection, classification, tracking, inspection, measurement, and scene understanding under guidance from product or technical leads.
• Implement and evaluate sensor-fusion methods using cameras, sonar, lidar, radar, inertial sensors, depth sensors, and vehicle telemetry within defined system interfaces.
• Contribute to visual, sonar, and multi-sensor SLAM, localization, mapping, calibration, state-estimation, and uncertainty-management capabilities for challenging environments.
• Implement and evaluate path, trajectory, task, and behavior-planning methods, including obstacle avoidance and motion-control interfaces, for defined operational scenarios.
• Apply suitable deep-learning, reinforcement-learning, imitation-learning, or human-in-the-loop techniques to scoped problems using agreed validation criteria and safety controls.
• Prepare and maintain datasets through collection, annotation, quality checks, synthetic-data generation, augmentation, experiment execution, and performance analysis.
• Use established simulation and verification workflows for software-in-the-loop, hardware-in-the-loop, scenario-based, sim-to-real, and field testing.
• Convert allocated customer and system requirements into component designs, interfaces, implementation tasks, tests, and traceable engineering evidence.
• Own defined technical tasks or work packages and contribute to architecture and design reviews by identifying implementation risks and recommending practical mitigations.
• Develop proof-of-concept implementations and prototypes, then help mature approved concepts into maintainable, testable, production-quality components.
• Optimize and deploy algorithms on edge and real-time computing platforms within agreed accuracy, latency, throughput, power, reliability, and hardware constraints.
• Collaborate with software, systems, controls, electrical/electronics, mechanical, test, and operations teams to integrate assigned autonomy capabilities into complete products.
• Assess selected third-party and open-source components, documenting technical trade-offs, licensing considerations, integration risks, and findings for review.
• Maintain awareness of relevant research and engineering practices and recommend applicable improvements to assigned products or work packages.
• Share technical knowledge, review work, support less-experienced colleagues, communicate progress and risks, and contribute to technical reports, demonstrations, proposals, and customer discussions.

Qualifications

• Bachelor’s degree in computer science, Data Science, Artificial Intelligence, Machine Learning, Robotics, Electrical/Electronics Engineering, Software Engineering, or a related engineering field, with five or more years of relevant professional experience in computer vision, robotics, autonomous systems, or applied machine learning.
• Master’s degree in computer science, Data Science, Artificial Intelligence, Machine Learning, Robotics, Electrical/Electronics Engineering, Software Engineering, or a related engineering field, with three or more years of relevant professional experience in computer vision, robotics, autonomous systems, or applied machine learning.
• Strong programming skills in Python and C++, with sound object-oriented design, software engineering, debugging, testing, and version-control practices.
• Hands-on experience with computer vision, image processing, deep learning, and 3D perception using frameworks or libraries such as OpenCV, PCL, PyTorch, TensorFlow, ONNX, or equivalent technologies.
• Practical experience in robotic perception, multi-sensor fusion, visual or sonar SLAM, localization, mapping, calibration, state estimation, or navigation.
• Knowledge of path planning, trajectory generation, task and behavior planning, obstacle avoidance, motion control, and autonomous decision-making.
• Experience with reinforcement learning, imitation learning, offline reinforcement learning, human-in-the-loop learning, or RLHF is desirable where relevant to robotics and autonomy.
• Experience with ROS or ROS 2 and robotics simulation environments such as Gazebo, NVIDIA Isaac Sim, MATLAB/Simulink, or comparable tools.
• Experience with synthetic data, scenario generation, software-in-the-loop or hardware-in-the-loop testing, sim-to-real transfer, field validation, and safety-oriented verification of autonomy functions.
• Experience deploying optimized AI and robotics workloads to edge accelerators and real-time systems, such as NVIDIA Jetson, GPUs, embedded Linux platforms, or equivalent hardware.
• Working knowledge of Linux and Windows, CI/CD, containers, MLOps or DevOps practices, model versioning, experiment tracking, and reproducible deployment.
• Experience with Azure Machine Learning or comparable cloud AI/ML services is desirable.
• Strong foundation in linear algebra, geometry, optimization, probability, statistics, estimation theory, and numerical methods.
• Ability to implement defined technical approaches, evaluate alternatives within an assigned scope, identify technical risks, and communicate design rationale and results to technical and non-technical stakeholders.
• Experience with subsea, offshore, inspection, intervention, mobile robotics, remote operations, or other safety- and reliability-critical systems is an advantage.
• Ability to analyze situations accurately, utilizing a variety of analytical techniques in order to make well informed decisions
• Ability to effectively prioritize and execute tasks in a high-pressure environment
• Skill to gather, analyze and interpret data
• Ability to determine and meet customer needs
• Ensures that others involved in a project or effort are kept informed about developments and plans
• Knowledge of communication styles and techniques
• Ability to establish and maintain cooperative working relationships
• Skill to prioritize workflow in a changing work environment
• Knowledge of applicable data privacy practices and laws
• Strong analytical and problem-solving skills.
• Knowledge, Skills, Abilities, and Other Characteristics