About this role
About the company
Our client is a fast-growing technology company.
The role
Raydar is recruiting for this role on behalf of our client. Apply machine learning in a live production environment, improving models that handle sensitive text and other data types. The work involves studying model weaknesses, preparing training data, running experiments and releasing measurable gains. It is a high-ownership position within a small, in-person engineering team.
What you'll do
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Own a production model end to end, including retraining, failure analysis and release of measurable accuracy improvements.
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Design and scale data labeling approaches, including active learning and LLM-assisted review.
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Extend existing capabilities to new data types such as audio, video and tabular data.
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Combine rules-based methods, classical ML, fine-tuning and LLM techniques to solve entity recognition and resolution problems, choosing the approach based on evidence.
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Build evaluation benchmarks and experiment tooling so that improvements move from discovery to production faster and more repeatably.
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Requirements
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What we're looking for
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3+ years of experience releasing and improving machine learning models in production.
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Strong Python software engineering skills, with experience in production-grade code rather than only exploratory notebooks.
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Experience working with AWS.
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Track record of investigating why a model underperforms on unfamiliar inputs, curating training data and lifting both precision and recall.
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Background in natural language processing, ideally with text extraction or entity-focused tasks.
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Experience expanding labeling throughput or adapting models to additional data types, plus familiarity with fine-tuning transformer models and inference optimization.
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Startup experience and a clear record of career progression.
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Bonus points
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STEM undergraduate degree from a highly ranked US university.
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Benefits
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Compensation and benefits
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Base salary: USD 250,000 to 330,000 per year
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Equity
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Health, dental and vision coverage
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Paid time off and company holidays
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Wellness benefits
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Location and work model
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New York, NY, United States
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On-site, 5 days per week in office
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Full-time