ML Data Platform Engineer - Foundation Data for Models

Parisi Labs; New York (NY); Hybrid; USD 175,000 - 245,000; Full time

Benefits offered by this job

Equity

Job summary

Parisi Labs is seeking an ML Data Platform Engineer in the United States (NYC or Boston/Cambridge) to make data behind models, products, and deployments dependable and usable. You will turn real-world sources into durable datasets and interfaces used by researchers and engineers.

You will own data foundations, define data contracts, and build reusable workflows for public and customer-authorized sources, ensuring quality, lineage, and access controls across systems.

Qualifications

• A record of designing, building, and operating production data systems that researchers or engineers depend on.
• Strong programming, querying, and data-modeling skills, with the ability to write maintainable, tested production software.
• An understanding of time-dependent data correctness, including backfills, revisions, freshness, and point-in-time availability.
• Experience supporting ML training and evaluation, or similarly demanding data-intensive product workloads.
• The ability to design practical data contracts, validation, observability, and access controls without overbuilding the platform.
• Strong debugging and collaboration skills, including the ability to trace failures across systems and explain data limitations clearly.

Responsibilities

• Build and improve ingestion, backfills, validation, and observability for high-volume, time-dependent data.
• Define clear data contracts and point-in-time semantics for model training, evaluation, and product use.
• Create reusable workflows for bringing public and customer-authorized sources into the system.
• Build quality, lineage, freshness, and access controls that make data trustworthy in repeated use.
• Develop efficient datasets and query interfaces for machine-learning and product workloads.
• Diagnose whether failures originate in source data, transformations, model inputs, or serving systems.
• Work with researchers and engineers to turn recurring data requirements into reliable software rather than manual projects.
• Decide which abstractions should become shared infrastructure and which should remain purpose-built.

Skills

Production data systems

Programming

Data modeling

Time-dependent data correctness

ML data support

Debugging and collaboration

Job description

Parisi Labs is seeking an ML Data Platform Engineer in the United States (NYC or Boston/Cambridge) to make data behind models, products, and deployments dependable and usable. You will turn real-world sources into durable datasets and interfaces used by researchers and engineers.

You will own data foundations, define data contracts, and build reusable workflows for public and customer-authorized sources, ensuring quality, lineage, and access controls across systems.