ML Data Platform Engineer - Hybrid (NYC/Boston) Equity

Parisi Labs, Inc.; New York (NY); Hybrid; USD 179,000 - 242,000; Full time

Benefits offered by this job

Equity

Job summary

Parisi Labs, Inc. is hiring an ML Data Platform Engineer to make model data reliable, understandable, and reusable. You will shape data foundations for researchers and product teams, turning messy sources into durable datasets and interfaces.

The role sits at the intersection of data engineering and ML, with collaboration across researchers and engineers. The position targets hybrid work with in-person collaboration 3 days per week in New York City or Boston/Cambridge, and offers equity

Qualifications

• Experience designing, building, and operating production data systems for researchers or engineers.
• Strong programming, querying, and data-modeling skills with production-grade code.
• Understanding of time-dependent data correctness, backfills, and point-in-time data.

Responsibilities

• Build and improve ingestion, backfills, validation, and observability for high-volume data.
• Define data contracts and point-in-time semantics for model training and evaluation.
• Create reusable workflows for public and customer data sources.
• Implement quality, lineage, freshness, and access controls for trustworthy data.
• Develop efficient datasets and query interfaces for ML and product workloads.
• Diagnose failures across sources, transformations, models, and serving systems.
• Collaborate with researchers and engineers to turn data needs into reliable software.
• Decide which abstractions become shared infrastructure vs. bespoke modules.

Skills

Production data systems

Programming

Querying

Data modeling

Observability

Backfills

Collaboration

Debugging

Job description

Parisi Labs, Inc. is hiring an ML Data Platform Engineer to make model data reliable, understandable, and reusable. You will shape data foundations for researchers and product teams, turning messy sources into durable datasets and interfaces.

The role sits at the intersection of data engineering and ML, with collaboration across researchers and engineers. The position targets hybrid work with in-person collaboration 3 days per week in New York City or Boston/Cambridge, and offers equity