Lead and mentor a team of software engineers building scalable machine learning infrastructure.
Define and own the multi-quarter technical strategy for data generation, orchestration, and distributed training.
Represent the Scalable ML team in org-level planning and architecture decisions, resolving cross-team tradeoffs on shared infrastructure.
Latitude AI is building the future of Ford's autonomy roadmap, developing a fully in-house hands-free ADAS platform. As a Ford Motor Company subsidiary, it operates independently like a technology startup with engineering centers in Pittsburgh, Dearborn, and Palo Alto.
Design high-performance training platform components including orchestration, observability, and performance tuning.
Deliver end-to-end ML pipelines from dataset curation to training, validation, and deployment.
Drive technical direction across ML Platform, Infrastructure, Autonomy, and Safety teams.
Stack is developing revolutionary AI and advanced autonomous systems for safer, more reliable, and efficient operations, focusing on autonomous trucking. The Stack team brings decades of experience in real-world systems and is committed to a culture of inclusion, entrepreneurship, and innovation.
Design and implement state-of-the-art ML models and training pipelines for robotics.
Develop efficient data/training strategies and evaluation frameworks for rapid experimentation.
Collaborate with engineering to optimize training infrastructure and deployment.
We're revolutionizing real-world automation by making robotic systems accessible to everyone. Our AI-powered platform brings software automation to physical spaces, and we're a small startup team working across the stack to solve customer problems.
Build and improve computer vision and 3D perception models that detect and assess infrastructure from LiDAR and imagery.
Develop LLM-powered products like agentic workflows, MCP servers, and AI copilots for customer tools.
Own models end-to-end, from data and training through evaluation, deployment, and monitoring in production.
Cyvl is a Physical AI company building purpose-built sensors, computer vision, and AI to turn every drive into current data for infrastructure. We're a fast-moving Boston startup with 500+ cities using our platform, and a culture of ownership, intensity, and care.
Develop and train ML models for learned behavior systems using imitation and reinforcement learning.
Write production-quality ML code for training, evaluation, and inference in the autonomy stack.
Collaborate with teams to test and integrate learned behavior models across diverse driving environments.
Torc is an autonomous vehicle technology company that develops software for automated trucks, with a goal to transform freight movement. Now a part of the Daimler family, the company fosters a collaborative, energetic, and team-focused culture.
Build the component layer around our layout synthesis engine, including API contracts, services, and evaluation gates.
Turn model retraining into a one-command job with built-in benchmarks and readable results for the whole team.
Own latency and cost budgets for learned capabilities and partner with infrastructure engineers on MLOps and deployment.
Higharc is a VC-backed startup that is changing how new homes are designed and built using spatial AI and generative floor plan technology. The company is fully remote, has raised over $175M, and values flexibility, collaboration, and asynchronous deep work.
Develop deep learning models for feature matching, depth estimation, pose estimation, and image-to-map localization.
Own data preparation and supervision strategies, including dataset curation, labeling workflows, and quality checks.
Collaborate with state estimation and deployment engineers to integrate learned measurements into VIO and terrain-relative navigation systems.
This company builds autonomous systems that can understand motion and localize themselves when GPS is unavailable. Its engineering team works remotely, collaborating across deep learning, computer vision, and state estimation.
Develop and evaluate deep learning models for feature detection, matching, depth estimation, and visual localization.
Own data preparation, training workflows, and evaluation of learned components for vision-based navigation.
Partner with state estimation and deployment engineers to integrate and optimize models for onboard systems.
Shield AI is a venture-backed defense-tech company developing intelligent systems to protect service members and civilians, with products like Hivemind autonomy software and V-BAT aircraft. It has offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, actively supporting operations worldwide.
Own the architectural evolution of the operator foundation model, designing transformer variants for spatial domains and scaling distributed training beyond 45TB datasets.
Architect trillion-voxel inference systems that balance memory, compute, and communication with production-grade stability.
Ship expanded operator capabilities into production, increasing simulation throughput by 100x across global, multi-entity deployments.
Vinci builds operator intelligence infrastructure that modern hardware programs rely on, with a single foundation model deployed across industries on realistic production workloads. They are a Series A company with 45TB+ of physics data, running billion-voxel inference inside Tier-1 semiconductor environments.