Top Tech Jobs & Startup Jobs in NYC, NY

Designs and validates electronics for robotics data-capture hardware, including schematics, PCB layouts, sensor interfaces, board bring-up, bench debugging, and system validation. Collaborates with firmware, mechanical engineering, and suppliers to improve prototypes, production designs, component qualification, and field performance. Documents measurements and design changes while addressing signal quality, timing, power consumption, and hardware-firmware integration.

Build native Android applications that connect capture hardware, guide data recording, display status, and support recovery from interruptions. Optimize video performance, memory, battery usage, responsiveness, and connectivity across Android devices. Develop diagnostics and automated workflow tests while collaborating with firmware engineers to reproduce and resolve hardware, transfer, and device-interface issues.

Train and evaluate computer vision models for embedded deployment, build efficient C++ inference pipelines, and optimize latency, memory, power, and sustained performance. Integrate models with embedded Linux, test on representative hardware and data, and investigate errors across preprocessing, inference, and system integration. Lead candidates will set architecture and evaluation standards while guiding model and software development.

Develop manufacturing processes, production-readiness and capacity plans for electronic capture hardware. Build and qualify fixtures, calibration equipment, and production tests; analyze yield, cycle-time, and failure data; improve designs for manufacturing; establish repair and rework processes; and guide suppliers through qualification, technical reviews, quality improvements, and production changes.

Build reinforcement learning environments for robotics and embodied AI research. Define tasks, observations, actions, rewards, transitions, termination conditions, and evaluation metrics. Train baseline agents, run controlled experiments, assess generalization and uncertainty, investigate failures, and identify data or environment issues. Collaborate with domain experts and engineers to develop reusable, documented research systems and benchmarks.

Build scalable physics-based simulation environments and world models for robotics and embodied AI. Develop parallel training and evaluation pipelines, calibrate simulations against real-world data, improve sim-to-real transfer, and create learned or hybrid dynamics models for prediction, planning, and control. The role requires strong simulation, robotics learning, Python, and C++ expertise, along with experimental judgment and experience building reproducible research infrastructure.

Lead scientific programs for robotics and embodied AI data generation. Develop operating plans, manage scientific partnerships, launch workflows, coordinate equipment and teams, oversee quality, throughput, schedules, and costs, and improve program performance across locations. The role requires hands-on execution, operational decision-making under uncertainty, vendor and logistics coordination, and practical scientific or laboratory fluency.

Own production online camera calibration, SLAM/VIO systems, and fleet-wide calibration drift monitoring for robotics devices. Develop video-based calibration refinement, maintain calibration databases and version history, coordinate with hardware teams on sensor parameters and synchronization, and build visualization tools for operations and research. The role requires extensive experience with SLAM, VIO, SfM, multi-sensor calibration, optimization, and scalable C++ and Python engineering. It is on-site with periodic travel to a hardware site.

Develop and own classical computer vision systems for 3D hand reconstruction, including multi-view geometry, camera calibration, temporal filtering, inverse kinematics, and physical constraints. Convert model predictions into clean, validated spatial data and maintain scalable delivery pipelines. Build QA metrics, visualizers, dashboards, and failure-analysis tools while partnering with research teams on robotics and embodied AI applications.

Develop generative and physics-based models to infer full-body human motion from egocentric and partial observations. Train motion priors, enforce physical consistency, estimate contacts and ground planes, and deliver MHR/SOMA-X outputs for production robotics pipelines. Define evaluation metrics, commission motion-capture and sensor data, implement research code, and publish results.