Expect to flex across concurrent client engagements, each with its own goals, constraints, and regional considerations. Bringing deep expertise in robotics and embodied AI, you’ll guide clients through large-scale data collection, field deployments, and program design — and build the perception systems, data pipelines, and model integrations that deliver them.
Internally, you’ll act as the vital bridge between client vision and execution—partnering with Commercial, Solutions, Operations, and Quality to translate ambitious goals into well-run programs across multiple accounts worldwide. As the senior robotics presence in-region, you’ll be the first point of contact and engineering expertise for robotics solution and project requests originating in the US and EU, coordinating with our India/APAC team to move solutions from blueprint to production across time zones.
Strong experience in machine learning, computer vision, technical solutions engineering is required.
WHAT SUCCESS LOOKS LIKE
Clients will see our Sr. Robotics Applied AI Engineer as a genuine and trusted advisor, not a vendor resource — someone whose input shapes program design before problems occur. Internally, Commercial, Solutions, Operations, and Quality all treat this role as the technical anchor point for robotics engagements, and client programs consistently meet the outcomes they were scoped to deliver. Beyond the advisory anchor, this person also ships working perception and robotics systems: US/EU requests route through them early, feasibility is assessed before commitment, and cross-region handoffs to India/APAC stay clean under load.
RESPONSIBILITIES
Strategic Client Advisory & Co-Design: Act as the primary robotics subject-matter advisor in client conversations — assessing what a client is trying to achieve and recommending the approach, equipment, and program design most likely to get them there, rather than defaulting to a standard offering (co-design & iterate).
Hands-on Solution Build: Design and build the CV and perception systems — detection, segmentation, pose estimation — on the 3D geometry underneath (SE(3), camera models, projection, coordinate frames), and own sensor calibration and fusion (intrinsic/extrinsic, hand-eye, LiDAR–camera) and LiDAR processing.
Data Pipelines & Models: Design egocentric data-collection pipelines (head/wrist cameras, depth, IMU) for robot learning; evaluate, integrate, and fine-tune VLA models under data and compute constraints; and build supporting services (REST/gRPC, PostgreSQL) to expose model inference and robotics services.
Outcome-Based Scoping: Partner with clients to define success up front, then shape program scope, staffing models, and equipment needs around that outcome — pushing back where a client's initial ask won't get them the result they want.
Robotics Domain Leadership: Bring deep knowledge of the robotics and Embodied-AI landscape (hardware, data collection, simulation, and emerging models) to turn technical trends into actionable client solutions.
Technical Bridge & Scoping Alignment: Serve as the connective layer between client technical requirements and our internal delivery teams — ensuring what's scoped with the client is translated into specifications Operations, Solutions, and Quality can actually execute, and that internal technical constraints or trade-offs are surfaced back to the client accurately and early.
Commercial Support & Development: Identify and help shape new robotics-related opportunities within existing and prospective client accounts, acting as technical credibility in front of clients alongside Commercial.
Field Execution & Technical feedback loop: Own real-time technical feedback on equipment, calibration, and field performance during pilots and live programs, escalating issues before they affect client-facing quality, timelines, or SLA standards.
QUALIFICATIONS
Background in robotics, mechatronics, robotics engineering, or a closely related technical field.
Experience in robotics machine learning, computer vision, or technical solutions engineering, with a track record of shipping to production.
Demonstrated client-facing or presales experience on robotics, automation, or embodied-AI programs, combined with strong hands-on build/deploy experience — this role both advises and ships.
Strong computer vision and perception (detection, segmentation, pose estimation, optical flow) and 3D geometry (SE(3), camera models, projection, coordinate frames).
Sensor calibration and fusion, including LiDAR–camera, plus LiDAR processing; and sim-to-real experience (Isaac Sim, MuJoCo, Gazebo, or Unity Robotics Hub).
Conceptual grasp of VLA architectures and the current SOTA landscape; strong Python (PyTorch), able to read and implement research papers.
Strong working knowledge of current robotics and embodied-AI industry trends, data collection methods, and deployment models.
Proven ability to translate technical detail into business-relevant recommendations for non-technical stakeholders.
Comfortable operating cross-functionally across Commercial, Solutions, Operations, and Quality teams.
Experience supporting global or multi-region client engagements preferred.
Hands-on experience with multi-camera systems, including calibration, synchronization, and tracking.
Solid grounding in computer vision fundamentals — object detection, pose estimation, segmentation, sensor fusion — and their application to robotic perception.
Ability to read and critically interpret state-of-the-art technical reports published by frontier labs developing general-purpose humanoid and non-humanoid robots.
Willingness and ability to travel to data collection sites (globally) as needed to support engagements.
TECHNICAL STACK
Python (PyTorch) · OpenCV, Open3D, PCL · Isaac Sim, MuJoCo, Gazebo, Unity Robotics Hub · ROS/ROS2 · VLA models (RT-2, OpenVLA, π₀, Octo), ViTs, multimodal · REST/gRPC, Docker, PostgreSQL; TensorRT/ONNX for edge.
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