Description
Build and iterate on CV and perception components — detection, segmentation, pose estimation — under senior technical direction.
Implement the 3D geometry underneath — SE(3) transformations, camera models, projection, and coordinate-frame management.
Run sensor calibration (intrinsic/extrinsic, hand-eye, LiDAR–camera) and basic LiDAR processing — registration, ground segmentation, object detection.
Build and maintain egocentric data collection pipelines using cameras, depth sensors, and IMU.
Set up simulation environments and support sim-to-real experiments — domain randomisation and gap analysis.
Integrate and evaluate VLA models; assist with fine-tuning large pretrained models under guidance.
Build supporting services — REST/gRPC APIs and PostgreSQL — to expose model inference and robotics services.
Support technical discovery, demos, and proof-of-concepts alongside senior engineers and solutions leads.
Write clean, tested code and clear documentation; contribute to the team's engineering quality.
2–4 years in robotics ML, computer vision, or ML engineering.
Solid CV and perception fundamentals — detection, segmentation, pose estimation.
Working knowledge of 3D geometry — transformations, camera models, projection, coordinate frames.
Exposure to sensor calibration and/or LiDAR processing.
Some simulation experience (Isaac Sim, MuJoCo, Gazebo, or Unity Robotics Hub) — or clear eagerness to ramp.
Conceptual familiarity with VLA models and modern robot-learning approaches.
Strong Python (PyTorch); able to read research papers and turn them into working code.
Clear communicator who collaborates well on a team.
Eagerness to learn and grow toward end-to-end ownership.
API development basics (REST/gRPC, Docker) and PostgreSQL.
ROS / ROS2 exposure.
Hands-on with robot hardware (Franka, UR, Unitree, or similar).
Personal projects, open-source work, internships, or coursework in robot learning or CV.
Languages: Python (PyTorch), C# (Unity)
Perception / 3D: OpenCV, Open3D, PCL, point cloud processing
Simulation: Isaac Sim, MuJoCo, Gazebo, Unity Robotics Hub
Robotics Middleware: ROS / ROS2
Models: VLA models (RT-2, OpenVLA, π₀, Octo), ViTs, multimodal, hosted and open-source
Deployment: REST/gRPC, Docker, PostgreSQL; TensorRT / ONNX for edge
Core Areas: CV and perception, 3D geometry, calibration, LiDAR, sensor fusion, sim-to-real
Perception and robotics components shipped to spec, well-tested, and cleanly integrated.
Reliable calibration, data collection, and sim setup that others can build on.
Fast ramp on new sensors, models, and tools as engagements require.
Growing independence — moving from guided tasks toward owning components end to end.
Clean, documented code that raises the team's baseline quality.
About Company:
TELUS Digital is the customer experience transformation partner to the world's most admired brands. Our diverse team weaves data, technology, and human ingenuity to deliver differentiated customer journeys, drive operational effectiveness, and scale AI solutions with meaningful value and positive impact.
We craft real-world solutions in the moments that matter, from customer acquisition to lifelong loyalty. Enabled by our global reach - spanning 78,000 experts in 33 countries - and deep industry expertise, we help over 600 organizations make the customer experience feel effortless.
Our solutions span Data & AI, Digital Experience & IT, CX Management and Trust & Safety. At the core of our innovation is Fuel iX™, an enterprise-grade generative AI platform that helps clients safely access and optimize leading LLMs to scale their own AI from pilot to production.
Equal Opportunity Employer Statement
At TELUS Digital, we are proud to be an equal opportunity employer and are committed to creating a diverse and inclusive workplace. All aspects of employment, including the decision to hire and promote, are based on applicant's qualifications, merits, competence and performance without regard to any characteristic related to diversity.
