--- title: 'Research Scientist - Vision Foundation Models at Epsilon Labs, Inc.' canonical: 'https://feeny.ai/job/research-scientist-vision-foundation-models-epsilon-labs-inc-san-francisco-mzemvmd5nd0b' type: 'job' last_seen: '2026-09-16' --- # Research Scientist - Vision Foundation Models at Epsilon Labs, Inc. - **Company:** Epsilon Labs, Inc. - **Location:** San Francisco, CA - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-08-31 - **Last confirmed live:** 2026-09-16 - **Apply:** https://jobs.ashbyhq.com/epsilon-health/374732cf-27d1-4073-81df-e4c4ed028d99 ## Job description ## About Us We're tackling one of healthcare's most critical challenges in medical imaging and diagnostics. Our company operates at the intersection of cutting-edge AI and clinical practice, building technology that directly impacts patient outcomes. We've assembled one of the industry's most comprehensive and diverse medical imaging datasets and have a proven product-market fit with a substantial customer pipeline already in place. ## Role Overview We're seeking a Research Scientist with deep expertise in vision foundation models to join our ML Research team. You'll be at the forefront of developing and deploying state-of-the-art vision models for medical imaging applications. This role focuses on pretraining and scaling vision encoders for radiology diagnosis across X-ray, CT, and MRI, with a growing emphasis on 3D volumetric modeling. You'll work with one of the largest and most diverse medical imaging datasets in the industry, pushing the boundaries of what's possible in AI-assisted diagnosis while maintaining the rigor required for clinical deployment. ## Key Responsibilities - Design, train, and scale vision foundation models for radiology applications across X-ray, CT, and MRI modalities, implementing self-supervised, contrastive, masked image modeling, and joint-embedding predictive (JEPA) frameworks. - Extend 2D pretraining recipes to volumetric CT and MR data, addressing long sequence lengths, anisotropic spacing, and multi-sequence studies. - Evaluate model performance rigorously across academic benchmarks, internal offline datasets, and live production data. - Contribute hands-on to all stages of model development including dataset curation, architecture design, distributed training, and production deployment. - Stay current with cutting-edge research in computer vision and medical imaging AI. - Drive research and technical excellence through conference publications and technical blog posts, establishing best practices for training robust medical imaging models at scale. ## Qualifications - 6+ years of academia/industry experience in computer vision/machine learning - Deep expertise in training vision encoder models at scale (e.g. ViT, ConvNeXt). Strong foundation in self-supervised pretraining, including contrastive, masked image modeling, self-distillation, and JEPA-style objectives. - Experience training on volumetric or spatiotemporal data (video, 3D medical imaging) - Track record of implementing complex models from research papers and adapting them to new domains - Proficiency in PyTorch or JAX, with experience training models on multi-GPU/distributed systems - Hands-on experience with medical imaging applications, particularly radiology (X-ray, CT, MRI) - Strong software engineering skills and ability to write production-quality code ## Preferred Qualifications - Publications at top-tier conferences (CVPR, ICCV/ECCV, NeurIPS, ICLR, MICCAI) - Experience with 3D medical image processing and retrieval tasks - Familiarity with CT and MR acquisition (windowing, multi-sequence protocols, voxel spacing) - Experience with long-context training techniques (sequence parallelism, efficient attention) - Knowledge of vision-language models and multimodal learning - Experience with model interpretability and explainability methods - Understanding of clinical evaluation metrics, clinical workflows, and healthcare data (DICOM, HL7, etc.) ## About Epsilon Labs, Inc. ## Company Overview - **One-liner**: Epsilon Health is a tech-enabled teleradiology practice that combines board-certified radiologists with proprietary AI to deliver accurate, rapid diagnostic reports. - **Entity Type**: Private (venture-backed startup, pre-Series A) - **Headquarters**: San Francisco, CA, USA - **Founded**: 2024 - **Founders**: Not publicly disclosed (key executives include Dr. Roi Bittane – Chief Medical Officer, and Rustin Rassoli – Founder/Executive; team also includes leaders from Google DeepMind, Meta, and Twitch) ## Core Business - **Primary industry**: Healthcare – Teleradiology / Medical Imaging / Health Tech - **Target customers**: B2B – Imaging centers, hospitals, health systems, and payers in the United States - **Mission**: “To make sure no diagnosis is missed, delayed, or wrong.” ## Products & Services - **Epsilon Platform (Proprietary AI + Workflow)**: A SaaS-enabled interpretation service that integrates AI models for triage, flagging critical findings, and automating busywork. Radiologists use the platform to increase speed and accuracy while reducing burnout. - **Teleradiology Services**: 24/7 remote radiology interpretation with a turnaround time of 24 hours or less; critical findings flagged immediately. Combines human expertise with AI assistance. ## Market Standing - **Valuation/Market Cap**: Not publicly available (early-stage startup) - **Key Metric**: Total funding not disclosed; backed by venture studio Atomic (based on team background). Headcount ~6 employees (as of mid-2025). - **Notable Investors/Partners**: Implied backing from Atomic; no formal funding announcement found. - **Growth Signals**: Founded in 2024, actively hiring for Research Scientist, Research Engineer, and Senior Backend Engineer roles. Addresses a massive market gap: 700 million scans/year in the US, with a radiologist shortage projected to reach 15,000 by 2030. ## Competitive Advantages - **Integrated AI + Human Workflow**: Unlike point solutions that fail in production, Epsilon builds AI directly into its practice, allowing continuous iteration across hospitals and imaging centers. - **Speed & Accuracy**: 75% of critical findings flagged immediately; reports delivered in 24 hours or less. - **Radiologist-Centric Design**: Removes administrative busywork to let radiologists focus on interpretation, reducing burnout. - **Team Depth**: Combines clinical leadership (former CMO of Envision Radiology) with top-tier ML engineering (Google DeepMind, Meta, Twitch alumni). ## Strategic Focus - **Scale the practice** to meet growing imaging demand by onboarding more radiologists and imaging center partners. - **Deepen AI capabilities** for automated triage, detection, and workflow optimization. - **Expand partnerships** with health systems and payers to improve patient outcomes and reduce costs. ## Why Work Here - **Culture**: “Radiology rebuilt from the ground up” – a mission-driven environment focused on solving a critical healthcare crisis. Emphasis on collaboration between radiologists, engineers, and technologists. - **Work Policy**: Hybrid – in-office presence in San Francisco (SOMA area) with remote flexibility for certain roles (Built In lists both “In-Office” and “Remote Workspace” options). - **Engineering Culture**: Small, high-impact team with autonomy; roles span ML infrastructure, computer vision, and backend systems. Opportunity to shape the product from an early stage. - **Perks**: Not detailed, but typical for early-stage health tech (likely equity, health benefits, and the chance to work on life-saving technology). ## Sources 1. [epsilon.health](https://www.epsilon.health/) – Company homepage and product description 2. [epsilon.health/about](https://www.epsilon.health/about) – Mission, background, and statistics 3. [epsilon.health/team](https://www.epsilon.health/team) – Leadership and engineering team 4. [builtin.com/company/epsilon-health](https://builtin.com/company/epsilon-health) – Office location, headcount, and work policy 5. [jobs.ashbyhq.com/epsilon-health](https://jobs.ashbyhq.com/epsilon-health) – Active job openings ## Other roles at Epsilon Labs, Inc. - [Software Engineer - Product](https://feeny.ai/job/software-engineer-product-epsilon-labs-inc-san-francisco-y7ttr13zgn08) — San Francisco, CA - [Software Engineer - ML Infrastructure](https://feeny.ai/job/software-engineer-ml-infrastructure-epsilon-labs-inc-san-francisco-fbhbgrb0sk47) — San Francisco, CA - [Software Engineer - Core Systems](https://feeny.ai/job/software-engineer-core-systems-epsilon-labs-inc-san-francisco-55xn9qbzrags) — San Francisco, CA - [Research Scientist - VLM Pretraining](https://feeny.ai/job/research-scientist-vlm-pretraining-epsilon-labs-inc-san-francisco-e9sv1335xj0a) — San Francisco, CA - [Research Scientist - Post-training / RL](https://feeny.ai/job/research-scientist-post-training-rl-epsilon-labs-inc-san-francisco-88p5ss3dcaga) — San Francisco, CA - [Research Engineer - Data Quality & Evals](https://feeny.ai/job/research-engineer-data-quality-evals-epsilon-labs-inc-san-francisco-bvtb488px6jv) — San Francisco, CA - [Reading Radiologists](https://feeny.ai/job/reading-radiologists-epsilon-labs-inc-remote-jr85tcf6zpp3)