Lead Machine Learning Engineer

Job Title: Lead Machine Learning Engineer (Computer Vision)
Location: Washington, DC (Hybrid – 1 day/week in office)

Note:
Applicants must possess a minimum of 7 years of hands-on experience in production (non-research focused) environments, excluding internships, to be considered for this position. Prior leadership or mentorship experience is strongly preferred.

Company Overview
Each year, over 4 million people die from complications following surgery. At the Surgical Data Science Collective (SDSC), a mission-driven nonprofit, we’re changing that. We harness the power of machine learning and computer vision to analyze surgical video and provide actionable feedback to improve surgical technique and outcomes. Our vision is to make surgery safer and smarter through technological innovation, and we’re looking for exceptional talent to help us do it.

Position Summary

We are seeking a Lead Machine Learning Engineer with deep expertise in computer vision and deep learning, and a proven ability to drive complex projects from ideation to deployment. This is a hands-on leadership role, combining technical excellence with strategic thinking and team collaboration. You’ll help define our technical roadmap, mentor engineers, and lead the development of algorithms and systems that analyze surgical video at scale.

You’ll work closely with our Director of Machine Learning and cross-functional teams of researchers, engineers, and clinical partners to turn real-world surgical video into breakthrough insight and feedback tools. You'll also play a critical role in translating research and experimentation into production-ready systems, helping bring ML models into real-world use as core features of our surgical analytics platform.

Key Responsibilities

• Lead the design and development of state-of-the-art computer vision and ML algorithms focused on surgical video analysis.

• Mentor and guide a small team of engineers while contributing directly to code and system architecture.

• Architect and optimize data pipelines, model training workflows, and inference systems for high-volume video data.

• Collaborate with researchers and clinicians to translate user needs and scientific advances into robust technical solutions.

• Own the technical design and implementation of CV/ML systems, from prototype to production deployment.

• Lead efforts to productize ML models, ensuring scalability, performance, and seamless integration with core product features.

• Continuously evaluate and integrate emerging technologies, models (e.g., ViTs), and tools to elevate SDSC’s capabilities.

• Contribute to and review technical documentation and help establish engineering best practices across the team.

Minimum Qualifications

• 7+ years of professional experience in machine learning and computer vision, including production-level model deployment.

• Proven leadership experience — team mentorship, technical lead roles, or ownership of complex projects.

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related technical field.

• Deep experience with Python, OpenCV, and deep learning frameworks such as PyTorch, TensorFlow, or Keras.

• Strong understanding of modern neural network architectures (CNNs, RNNs, LSTMs, ViTs) for image and video analysis.

• Demonstrated experience bringing ML models into production as part of a product or system, not just in research or prototype phases.

• Hands-on experience with MLOps tools like ClearML and Weights & Biases, and cloud platforms such as AWS (SageMaker, Lambda).

• Experience designing scalable CV/ML pipelines, managing large datasets, and optimizing model performance.

• Familiarity with modern software development practices (version control, CI/CD, testing, containerization, etc.).

Nice to Haves

• Experience with Vision Transformers (ViTs) or multimodal learning systems.

• Background in medical imaging or working in regulated healthcare environments.

• Prior experience at startups or in fast-paced, early-stage product environments.

• Exposure to video compression, real-time streaming pipelines, or edge deployment.

Why Join Us?

• Join a mission-driven nonprofit dedicated to making surgery safer on a global scale.

• Work on challenging, high-impact ML problems with real clinical relevance.

• Enjoy competitive salary, 401(k), health insurance, and flexible work arrangements.

• Be part of a collaborative, creative, and inclusive environment where your contributions matter.

About us: The Surgical Data Science Collective (SDSC) is a nonprofit on a mission to unlock the power of surgical data. We bring together surgeons, scientists, and engineers to turn surgical videos into searchable, data-rich tools. Using AI, we help uncover insights that improve technique, sharpen decision-making, and elevate patient care. From smarter metrics to secure video libraries, we give surgical teams the tools to ask better questions—and find better answers. Because when surgeons get better, patients do too.