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Applied ML Engineer - Computer Vision

Prestige Staffing | United States | Today
$155,000 – $175,000/yr| full-time | remote | mid
skills: python, pytorch, computer vision, deep learning, machine learning, data acquisition, model deployment, label studio, mlops, dataset versioning, experiment tracking, inference, api
Job Title
Applied ML Engineer - Computer Vision
Pay
$155,000 - $175,000 annually
Location
Remote
Summary
An AI startup is seeking a founding Applied Machine Learning Engineer specializing in Computer Vision to lead the development of an innovative X-ray imaging product. As a key member of the team, you will drive end-to-end model development, from data acquisition to deployment, supporting a high-impact platform dedicated to product verification and quality assurance in compliance-critical environments. This role offers an exciting opportunity to shape a groundbreaking new technology in a fast-paced, startup-like setting with significant growth potential.
Requirements
  • Strong proficiency in Python and deep learning frameworks, especially PyTorch
  • Proven experience developing and deploying computer vision systems from data collection to production
  • Expertise in fine-tuning detection and segmentation models on complex, real-world datasets
  • Experience with labeling workflows and human-in-the-loop validation tools (e.g., Label Studio)
  • Ability to operate effectively in ambiguous situations and communicate technical details to non-technical stakeholders
  • Familiarity with dataset versioning, experiment tracking, and MLOps practices
Responsibilities
  • Build, iterate, and refine computer vision models for marker detection and defect identification
  • Define and implement evaluation metrics aligned with customer workflows, thresholds, and confidence thresholds
  • Conduct error analysis, derive actionable insights, and plan iterative improvements
  • Manage dataset curation, labeling guidelines, sampling strategies, and quality assurance processes
  • Establish lightweight versioning conventions for datasets and models to ensure reproducibility and traceability
  • Collaborate with customers and domain experts to clarify edge cases, constraints, and project success criteria
  • Develop reproducible training pipelines, experiment tracking, and model management systems
  • Package and deploy inference models, integrating into APIs, batch workflows, or streaming systems
Benefits
  • Be a founding engineer in a cutting-edge AI platform at the intersection of physical science and machine learning
  • Work remotely with flexible hours and unlimited PTO in a trusting, autonomous environment
  • Collaborate with a talented team of industry experts, including MDs, PhDs, and technical leaders
  • Opportunity for growth and impact in a startup environment focused on high-stakes, real-world applications

Benefits

flexible hours · unlimited pto
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