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Applied ML Engineer - Computer Vision

Prestige Staffing

New York, NY

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JOB DETAILS
SALARY
JOB TYPE
Full-time
SKILLS
Analysis Skills, Application Programming Interface (API), Artificial Intelligence (AI), Computer Vision, Data Collection, Data Sets, Deep Learning, Machine Learning, Metrics, Physical Science, Python Programming/Scripting Language, Quality Assurance, Quality Assurance Methodology, Radiography, Startup, Team Player, Traceability, Training Data Sets, Work From Home
LOCATION
New York, NY
POSTED
22 days ago
JobID: 53684Job TitleApplied ML Engineer - Computer VisionPay$155,000 - $175,000 annuallyLocationRemoteSummaryAn 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 practicesResponsibilities 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 systemsBenefits 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#LI-TG1#LI-Remote

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Prestige Staffing