Senior Data Scientist

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. Working within established product and system architectures, the role contributes computer vision, sensor-fusion, localization, mapping, planning, control, and data-analysis capabilities. The position is a hands-on senior individual contributor who owns assigned technical tasks or defined work packages, collaborates with cross-functional teams, supports field validation, and provides peer guidance without holding organization-wide architecture or research leadership responsibility.

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.

REQUIRED

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.

OR

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.

DESIRED

• 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.
• Knowledge, Skills, Abilities, and Other Characteristics
• 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.