Senior Applied AI Engineer
Sully.ai
Distributed SystemsPyTorchTensorflowTypeScriptVoIP
Senior Machine Learning Engineer
RepeatMD
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteJob Level
Senior
Tech Stack
AWSAzureCloudGoogle Cloud Platform.NETPythonPyTorchReactTensorflow
About the role
- You’ll design and optimize computer vision models that transform real patient images into realistic, medically accurate “after” results.
- You’ll work closely with product, design, and medical experts to train, fine-tune, and deploy models that help people make confident, informed decisions about their appearance and well-being.
- Evaluate and benchmark state-of-the-art models (segmentation, detection, SDXL/diffusion, LLM-based classifiers).
- Select the best architectures balancing accuracy, inference speed, efficiency, and fairness.
- Develop generative models for before/after treatment previews, ensuring realism, inclusivity, and clinical credibility.
- Design inference pipelines optimized for low latency and high throughput.
- Use model compression, quantization, and distillation to reduce compute costs while maintaining accuracy.
- Leverage AWS (Lambda, Step Functions, SageMaker, GPU pipelines) or equivalent to build cloud-scale systems.
- Build quality-control systems (blur detection, orientation/rotation correction, lighting checks).
- Implement multi-candidate generation + ranking for robustness.
- Ensure identity consistency and similarity verification across generated images.
- Develop fallback algorithms for resilience under failure modes.
- Package models for deployment into production at scale, with proper versioning and monitoring.
- Build CI/CD pipelines for continuous training, testing, and deployment.
- Define and track key performance metrics (latency, throughput, drift, fairness, user satisfaction).
- Work with product, engineering, and clinical teams to align on accuracy, safety, and inclusivity goals.
- Stay up-to-date with research, and bring the best of academia and industry into production.
- Act as a thought partner in shaping responsible AI practices within the product.
- Mentor a small pod of ML and Platform engineers as hiring ramps.
Requirements
- Master's/PhD in Computer Science, Machine Learning, or equivalent practical experience
- 5+ years of experience in applied ML, with a focus on computer vision and generative models
- Strong track record with segmentation, detection, and diffusion-based generative models (SDXL, Stable Diffusion, etc.)
- Deep expertise in optimizing ML for scalability and efficiency (quantization, pruning, distillation)
- Strong engineering background: Python, PyTorch/TensorFlow, clean production code
- Hands-on experience deploying ML at scale in AWS/GCP/Azure
- Proven ability to balance speed, accuracy, and cost in real-world deployments
- Comfort reading and integrating with a .NET and React stack via clean service contracts.
Benefits
- Medical, Dental, Vision, and 401k through Justworks
- Stock options
- Parental leave (12 weeks maternity, 4 weeks paternity)
- Annual performance reviews
- Professional development budget (conferences, courses, publications)
- Flexible working arrangements, collaborative culture, and a mission-driven environment
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
computer visiongenerative modelssegmentationdetectionSDXLdiffusionquantizationpruningdistillationPython
Soft skills
mentoringcollaborationcommunicationproblem-solvingthought leadership
Certifications
Master's in Computer SciencePhD in Machine Learning
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