Turing is looking for an Applied Research Engineer to help build robust, high-quality datasets that fuel modern perception, SLAM, and manipulation models for AI systems.
Requirements
- 3–5 years of hands-on experience in robotics, applied ML, or computer vision, ideally with some exposure to real-world sensor data or annotation workflows.
- Strong understanding of robotics concepts such as perception pipelines, SLAM, or sensor fusion.
- Familiarity with basic ML training and evaluation, particularly for computer vision or multi-modal data tasks.
- Ability to read and synthesize ML research papers relevant to robotics.
- Experience with tools such as ROS, CVAT, Roboflow, or custom labeling platforms.
- Some exposure to model fine-tuning (e.g., with PyTorch, TensorFlow, or Hugging Face).
Responsibilities
- Help define and evolve labeling schemas for robotic perception tasks, including: 2D/3D detection and segmentation, Grasp and manipulation point annotations, Scene affordances and human-robot interaction, Sensor fusion (e.g., aligning RGB + LiDAR + IMU).
- Align annotation strategies with key robotics benchmarks and downstream model use cases (e.g., RL, imitation learning, vision-based control).
- Fine-tune and evaluate small ML models (e.g., lightweight vision or language models) for targeted robotics tasks.
- Perform basic experiments to assess data effectiveness and model improvement.
- Contribute to quality control processes—build checklists, gold sets, and feedback loops that ensure consistent, scalable labeling outcomes.
- Collaborate with ML, robotics, and data labeling teams to turn model and benchmark requirements into clear, actionable data specs.
- Write clear documentation and present technical updates to collaborators and stakeholders.
Other
- Strong communication skills and a collaborative mindset are critical for success.
- Excellent written and verbal communication skills—comfortable translating technical needs across disciplines.
- Amazing work culture (Super collaborative & supportive work environment; 5 days a week)
- Awesome colleagues (Surround yourself with top talent from Meta, Google, LinkedIn etc. as well as people with deep startup experience)
- Competitive compensation
- Flexible working hours
- Full-time remote opportunity
