Head of Spatial AI

BitsBody develops next-generation computational modeling and simulation technologies to optimize engineering design and analysis workflows for spatial AI applications.

The Opportunity

We’re seeking an entrepreneurial, high-ownership individual contributor to drive the core engineering, development, and deployment of our Generative AI platform, an integral component of our medical technology solutions for anatomical modeling and simulation (M&S).

This role is ideal for a hands-on builder with a proven ability to design, train, and productionize multimodal generative machine learning (ML) pipelines, build robust backend infrastructure and APIs, and develop an interactive 3D web interface that visualizes model outputs in real time.

If you’re passionate about building a spatial AI company from the ground up, leveraging AI to solve critical problems, and have a track record of deploying complex AI systems, we want to hear from you.

Primary Title

Head of Spatial AI

Location & Work Type

San Jose, CA | Full-Time | Hybrid

Roles & Responsibilities

• Foundational Spatial AI Engineering: Architect and optimize multimodal, cross-domain, end-to-end pipelines by training multi-scale vision and spatiotemporal foundation models while integrating language model conditioning where appropriate.

• API & Backend Infrastructure: Containerize models and expose robust, low-latency APIs for generative inference workloads.

• Production Deployment: Productionize models as cloud services; implement model versioning, CI/CD, automated testing, and cloud-native deployment pipelines.

• Model Lifecycle Management: Implement post-deployment monitoring, drift detection, A/B testing, and automated retraining workflows to maintain performance and safety.

• 3D Modeling & Simulation: Implement and validate geometry pipelines (meshes, SDFs, implicit fields), ensure simulation readiness, and integrate downstream finite element analysis (FEA) workflows.

• Full-Stack 3D Platform Development: Architect and build a responsive, high-performance 3D web frontend and interactive workspace that visualizes real-time ML computations.

• Integrated Tooling: Embed volumetric viewers and mesh editors with analysis toolsets for both medical images and polygonal meshes.

• Strategic Alignment: Collaborate closely with the technical team to validate system-level behavior and translate anatomical modeling and simulation research into stable, production-ready enterprise applications.

• Post-Funding Operations: Establish engineering frameworks and architectural foundations to recruit and lead the core Spatial AI engineering team as the company scales.

Required Skills & Qualifications

• Education & Experience: Bachelor's degree (B.S./B.E./B.Tech) in Computer Science, Data Science, Machine Learning, Computer Vision, or a related quantitative field with 10+ years of progressive experience; or a Master's degree (M.S./M.E./M.Tech) with 8+ years of relevant experience; or a Ph.D. with 4+ years of relevant experience. Candidates must demonstrate hands-on experience developing data-intensive web applications involving spatial AI and production-grade deployment.

• Multimodal & Geometric ML Modeling: Experience building and training probabilistic generative models for 3D computer vision and spatial geometry, including normalizing flows, diffusion models, VAEs, NeRFs/implicit fields, and Gaussian Splatting, alongside NLP architectures such as Transformers, BERT, and T5 for image-to-3D and text-to-3D pipelines.

• Core Technical Stack: Expert-level proficiency with high-performance computing technologies, including:

  • Backend / AI (Python): PyTorch, PyTorch3D, PyTorch Geometric, Deep Graph Library (DGL), MONAI, and familiarity with TensorFlow, TensorFlow3D, TensorFlow Graphics, TensorFlow GNN, and Graph Net.

  • Frontend / Graphics (JavaScript/TypeScript): Three.js, React Three Fiber, Babylon.js, WebAssembly (Wasm), WebGL, and WebGPU, with experience streaming large volumetric datasets and dense geometric meshes.

• Backend & APIs: Experience building scalable APIs using FastAPI, GraphQL, gRPC/Protocol Buffers, WebSockets, and WebRTC, with supporting technologies including Celery, Redis, PostgreSQL, and object storage for large 3D datasets.

• Production DevOps: Experience containerizing GPU workloads with Docker and deploying scalable infrastructure using Kubernetes and Helm on AWS or GCP (EKS/GKE, S3/Cloud Storage, IAM).

• Model Serving & Inference: Experience with NVIDIA Triton, ONNX Runtime, TorchServe, or custom FastAPI/gRPC inference stacks, including model quantization and inference optimization.

• Performance Engineering: Familiarity with CUDA, cuDNN, NCCL, distributed training, profiling, and optimization for large-scale volumetric models.

• 3D Tooling & Data Libraries: Experience with PyDicom, SimpleITK/ITK, NiBabel, Open3D, Trimesh, MeshLib, Kaolin, or equivalent libraries.

• Security & Compliance: Understanding of PHI handling, DICOM security, and HIPAA-aware engineering practices.

• Execution: Ability to work independently, thrive in ambiguity, and build systems from the ground up.

Preferred Qualifications

• Startup Experience: Experience as a founder or early technical employee at a pre-seed through Series A startup.

• C++ Performance Optimization: Experience developing and optimizing C++ kernels for medical imaging and geometry processing (e.g., ITK, VTK, OpenCASCADE, Manifold3D).

• Biomechanical Simulation: Experience with CT/MRI preprocessing, segmentation, registration, physics-based simulation engines (OpenSim, FEA), and geometry/CAE toolchains.

• Research Contributions: Peer-reviewed publications or meaningful open-source contributions in machine learning, computer vision, or 3D geometry.

Equity & Compensation

All equity grants and stock options follow a standard four-year vesting schedule with a one-year cliff, consistent with venture-backed startup practices.

Two compensation pathways are available:

Option 1: Pre-Funding

Join as Co-Founder & Head of Spatial AI before the company's first institutional funding round.

• Equity-only compensation initially

• Meaningful co-founder-level ownership

• Clear path to salary and benefits following successful fundraising

Option 2: Post-Funding

Join as Head of Spatial AI after the company raises institutional funding.

• Competitive salary and benefits

• Senior-level stock option package

• Candidates pursuing this option will be considered only if no qualified candidate is selected for Option 1.

Benefits & Culture Highlights

• Mission-driven, high-velocity, high-ownership environment

• Direct influence over product strategy and technical architecture

• Opportunity to build category-defining spatial AI technology from the ground up

• Culture centered on transparency, intellectual rigor, and responsible innovation

• Collaborative team spanning medicine, engineering, science, and commercialization

• Post-funding benefits include:

  • Health insurance

  • Dental insurance

  • Vision insurance

  • Retirement benefits

  • Paid family leave

Contingency Disclaimer

This position is contingent upon a successful background check. Role responsibilities may evolve based on company growth and funding status. Any compensation beyond equity or stock options is contingent upon the successful completion of an outside funding round.

No Third-Party Recruiters

We do not accept resumes, inquiries, or outreach from third-party recruiters, staffing agencies, or talent consultants.

U.S. Work Authorization

Applicants must have permanent authorization to work for any employer in the United States. Visa sponsorship, including H-1B sponsorship, is not available for this position.

Skills

DICOM • Computer Vision • WebAssembly • Python • DevOps • Spatial Modeling • FastAPI • TypeScript • React