Machine Learning Engineer | AI Startup | NYC

Primis is partnered with a well-funded, early-stage AI startup in NYC building intelligent fraud detection software.

ARR is growing fast, they have enterprise logos, and they're backed by strong institutional investors. Small team, real ownership, meaningful equity.

They're hiring a Machine Learning Engineer to help build the data infrastructure and models that power their fraud detection platform.

What you'll work on:

• Build and maintain the data infrastructure powering fraud detection: ingestion pipelines, data model design, and the storage and orchestration layers tying it all together

• Develop, train, and deploy machine learning models to identify fraud patterns, score risk, and surface network-level signals

• Work directly with operations and leadership to turn real investigative expertise into data products

What we're looking for:

• 2-5 years of experience spanning data engineering, data science, and machine learning; comfortable flexing across the stack

• Proficiency in Python and SQL, with experience across the modern data stack: orchestration (Airflow, Dagster, Prefect), transformation (dbt, Spark), warehousing and query engines (Snowflake, BigQuery, Redshift, Athena, Databricks), and cloud platforms (AWS, GCP, Azure)

• Strong statistical and analytical foundation, with experience training and deploying ML models in production (Scikit-learn, PyTorch)

• Comfortable with limited structure and real ownership on a small, fast-moving team

• Strong communicator, able to explain design tradeoffs and model performance to both technical and non-technical stakeholders

• Bonus points for experience with LLM workflows and agentic applications (LangChain/LangGraph, Anthropic/OpenAI), or graph/network analysis, anomaly detection, entity resolution, or fraud/risk work

Interested? Please apply for more info!

ADVERT DISCLAIMER
Research indicates that men will apply to a role when they only meet 50-60% of the descriptions, however, when looking at women and other minority groups, they can look for up to a 99% match in order to apply to a role. If you feel you are a fit for our role, please still apply - don't worry if you don't tick every single box. We'd still love to hear from you. We encourage underrepresented talent to apply to all our roles and support accessibility needs.