Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Tailor your resume to this ML Data Platform Engineer role.
Rezi rewrites your resume against Parisi Labs, Inc.'s job description. Free.
Tailor your resume to this ML Data Platform Engineer role.
Rezi rewrites your resume against Parisi Labs, Inc.'s job description. Free.
Don't guess if your resume is good enough.
See how it scores against the ML Data Platform Engineer posting at Parisi Labs, Inc. — free, in seconds.
Don't guess if your resume is good enough.
See how it scores against the ML Data Platform Engineer posting at Parisi Labs, Inc. — free, in seconds.
About the Role
We are looking for an ML Data Platform Engineer to make the data behind our models, products, and customer deployments dependable, understandable, and easy to use. This role sits where data engineering meets machine learning. You will turn messy, changing real-world sources into durable datasets and interfaces that researchers and engineers can trust. Your work will support both public data and customer-authorized operational data. The goal is to make each new model, product capability, and data source faster to bring online without compromising correctness. You will own the shared data foundations, working with the applied-AI engineer on model requirements and the product engineer on application needs.
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.
Requirements
- 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.
Location
- New York City
- Boston/Cambridge
Work Type
- Hybrid
Salary/Compensations
- $175,000–$245,000 USD
Benefits
- Meaningful early-company equity
About the Company
- Parisi Labs is building foundational world models for physical industry. We are developing models that learn how complex physical systems behave and reuse that understanding across forecasts, scenarios, and operational decisions.
- Energy is our first proving ground. We combine historical and live data with operational context, bringing together machine learning research, data infrastructure, and software engineering to turn advances in modeling into useful technology for energy operators.
- We are a small technical team working directly with the founders on our core models, systems, and products.