Robotics Engineer
Upload My Resume
Drop here or click to browse · PDF, DOCX, DOC, RTF, TXT
Requirements
• 8+ years of total experience as a seasoned technologist with cross-functional operational experience. • 5+ years in Robotics Learning with deep hands-on experience training and deploying machine learning models for robotics (Imitation Learning, RL, or VLA architectures). • 3+ Years of cross-functional & commercial experience in which you have "bridged the gap" between research and product sales (e.g., Applied Scientist, Technical Lead, or Solutions Architect). • Expert proficiency in Python. You must be capable of writing production-grade ML code, custom data loaders, and evaluation pipelines from scratch. • Deep proficiency in PyTorch or JAX. Experience implementing and debugging complex deep learning architectures. • Direct hands-on experience training, fine-tuning, or evaluating advanced robotics policies. Specifically, familiarity with Diffusion Policies or VLA architectures. • Proficiency with ROS (Robot Operating System). You must understand message passing, node architecture, and how to interface with hardware drivers. • Experience manipulating standard robotics data formats. You understand the structure of "trajectory" data (state-action pairs). • Strong grasp of 3D spatial mathematics (quaternions, coordinate frames, transformations) essential for manipulating robot kinematics and camera data. • Entrepreneurial mindset required: ability to own end-to-end solutions, including technical execution, customer engagement, cost/ROI tradeoff analysis, and value communication to technical and non-technical stakeholders. • You know exactly what makes a dataset valuable when building advanced robotics foundational models. • You are comfortable explaining technical constraints to Sales teams, Product Managers, or external clients. • Experience with NVIDIA Isaac Sim, Unity, MuJoCo, or Genesis. Ideally, you have built custom benchmark environments or generated synthetic datasets. • Experience setting up distributed training workflows on cloud clusters and using experiment tracking tools like Weights & Biases (W&B). • Experience using Vision-Language Models (VLMs) and other tools to automatically label or annotate large datasets. • Ability to read and debug C++ code is a plus (useful for troubleshooting hardware drivers or legacy ROS nodes), but production coding in C++ is not required. • Experience deploying models to edge compute devices (e.g., NVIDIA Jetson) or directly onto robot controllers. • Compensation: $156,000 to $202,500+ and Equity
Responsibilities
• 1. Data Strategy & Productization (Short-Term Focus) • Design "Off-the-Shelf" Solutions: Leverage your experience to define specifications for high-value dataset products (e.g., "The definitive bi-manual manipulation dataset for household objects"). You will dictate the requirements to our Sim, Teleop, and Motion Capture teams to ensure they capture the right data. • Design "Off-the-Shelf" Solutions: • Commercial Engagement: Partner with the Sales team as a key technical authority. You will translate customer pain points (e.g., "Our model fails on transparent objects") into well defined data solutions. • Commercial Engagement: • Quality Definition: Move beyond basic QA (resolution, frame rate) to semantic QA. Define what "high-quality" data looks like for model learning. • Quality Definition: • 2. Model Evaluation & Gap Analysis (The Technical Core) • Build the "Eval" Loop: Establish workflows to train and fine-tune open-source Robotics Foundation Models (e.g., OpenVLA, Octo, RT-X) on our data. You will empirically prove that Turing’s data improves model performance. • Build the "Eval" Loop: • Agentic Gap Analysis: Develop automated workflows to analyze datasets for coverage gaps. Use this analysis to provide high-value insights to customers (e.g., "Your model is failing because your training distribution lacks diverse lighting conditions—here is the synthetic data to fix it"). • Agentic Gap Analysis: • 3. The Future: "End-of-Cycle" Optimization (Long-Term Focus) • Benchmark-as-a-Service: Lead the development of virtual and physical benchmarking environments to test customer policies. • Benchmark-as-a-Service: • The Optimization Loop: Build a full-cycle service where Turing: (1) Benchmarks a client's model, (2) Identifies performance gaps, (3) Translates gaps into data requirements, and (4) Delivers the data to close the loop. • The Optimization Loop: • Establish a New Business Unit: Scale these capabilities into a dedicated "Benchmarking & Optimization" business unit. You will help build this new pillar, recruiting the team, defining the product solution, and driving the monetization strategy. • Establish a New Business Unit:
Benefits
• Help Launch Business Unit: a 0-to-1 opportunity to help build a new business unit within Turing. • Help Launch Business Unit: • Define Industry Standards: Architect off-the-shelf datasets that will fuel the robotics ecosystem, setting the benchmark for Physical AI data quality. • Define Industry Standards: • Own the Evaluation Loop: Lead the critical feedback loop that validates data quality, proving empirically how specific attributes drive model performance. • Own the Evaluation Loop: • Values: • Values: • We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. • We are client first • We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection • We work at Start-Up Speed: • We are Al forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. • We are Al forward: • Advantages of joining Turing: • 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