Senior ML Engineer - Tabular Foundation Models in Production

FDE Times; New York (NY); Remote; USD 180,000 - 240,000; Full time

Job summary

Prior Labs is seeking a senior ML engineer to drive end-to-end deployments of our tabular foundation models with enterprise customers in New York and beyond.

You will own projects from initial scoping through production rollout, working closely with customer data science teams to ensure value is realized and documented. The role offers high autonomy, rigorous engineering standards, and opportunities to influence product direction.

Qualifications

• 3+ years building and deploying ML systems in production.
• Strong Python programming skills and ML model development.
• Experience with PyTorch and scikit-learn; transformer/foundation-model know-how.
• Proven cloud deployment (AWS, GCP, or Azure) into production.
• Mature customer instinct and ability to drive outcomes.

Responsibilities

• Integrate: Embed our foundation models into customer platforms, cloud environments, and ML pipelines.
• Do the Data Science: Frame the problem on real, messy data, engineer features, model it, and benchmark against baseline.
• Own Delivery: Carry use cases end-to-end - from first conversation to a reliable, documented production solution.
• Partner Deeply: Work with customer data science and ML teams as a peer, earn trust and accelerate adoption.
• Tailor & Optimize: Customize models for diverse use cases, balancing performance, latency, scale, and cost.
• Close the Loop: Turn deployment insights into prioritized feedback for model and product roadmap.
• Set the Standard: Establish deployment patterns as we scale our offerings.

Skills

Python

PyTorch

scikit-learn

Transformer models

Foundation models

Tabular ML

Cloud deployment

Tools

AWS

GCP

Azure

Job description

Prior Labs is seeking a senior ML engineer to drive end-to-end deployments of our tabular foundation models with enterprise customers in New York and beyond.

You will own projects from initial scoping through production rollout, working closely with customer data science teams to ensure value is realized and documented. The role offers high autonomy, rigorous engineering standards, and opportunities to influence product direction.