Senior Staff Machine Learning Platform Engineer

United States Digital Space LLC; United States; Hybrid; USD 295,000 - 406,000; Full time

Job summary

United States Digital Space LLC is hiring a Senior Staff Machine Learning Platform Engineer to own the ML platform vision and drive cross‑functional initiatives that accelerate data science at scale.

You will define architecture, establish standards for MLOps, and mentor teams while leveraging Databricks, Unity Catalog, Spark, and MLflow to build scalable pipelines across multiple data science workloads.

Qualifications

• 10-12 years of experience building and improving large-scale ML or data platforms.
• Degree (preferably graduate level) in CS, Engineering, Statistics, or a related field.
• Deep expertise in Databricks lakehouse architecture, including governance via Unity catalog, orchestration via Workflows, and cost optimization
• Proven ability to design systems that support multiple data science teams and production workloads
• Strong background in distributed systems, ML infrastructure, and cloud architecture.
• Demonstrated technical leadership across teams and orgs; ability to influence without authority
• Experience integrating LLM workflows into enterprise platforms is a plus
• Previous contributions to open source ML Infrastructure projects or research publications is a very strong plus

Responsibilities

• Define and drive the long-term architecture of the company’s ML platform including training, inference, feature management, governance
• Establish company-wide standards for code quality, testing, MLOps (CI/CD), experimentation, model lifecycle management, and observability
• Lead adoption and advanced use of Unity Catalog, multi-workspace strategies, and data/ML mesh patterns
• Architect highly scalable ML workflows using Spark, Delta Lake, and MLflow
• Optimize performance, reliability, and cost of the ML platform
• Evaluate and integrate emerging Databricks features
• Stay ahead of the curve by engaging with the latest developments in machine learning and AI
• Serve as senior ML technical advisor to the company’s data science and production engineering teams
• Represent the company at ML conferences and meetups
• Mentor ML engineers and raise the overall bar for Machine Learning at the company

Skills

ML Platform

Distributed systems

Leadership

Cloud architecture

Data governance

Education

Degree in CS/Engineering/Statistics

Tools

Databricks

Unity Catalog

MLflow

Kubernetes

Spark

Python

SQL

Job description

About the company

the company is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At the company, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive.

We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.

Note:

This role can also be performed remotely for candidates located in Arizona, California, Colorado, Connecticut, District of Columbia, Florida, Georgia, Idaho, Illinois, Indiana, Kentucky, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, Ohio, Oregon, Pennsylvania, Rhode Island, Tennessee, Texas, Utah, Virginia, Washington, or Wisconsin.

About this role

As the Senior Staff Machine Learning Platform Engineer, you will own the technical vision and evolution of the company’s ML platform. You will set standards, influence org-wide architecture, and lead complex, cross-functional initiatives that unlock data science velocity at scale. This role will also be key to adapting ML workflows to take advantage of modern AI productivity tools. You won’t just build models, you will architect the systems that allow those models to help tens of thousands of small retailers compete and grow their local businesses.

What You Will Do

• Define and drive the long-term architecture of the company’s ML platform including training, inference, feature management, governance

• Establish company-wide standards for code quality, testing, MLOps (CI/CD), experimentation, model lifecycle management, and observability

• Lead adoption and advanced use of Unity Catalog, multi-workspace strategies, and data/ML mesh patterns

• Architect highly scalable ML workflows using Spark, Delta Lake, and MLflow

• Optimize performance, reliability, and cost of the ML platform

• Evaluate and integrate emerging Databricks features

• Stay ahead of the curve by engaging with the latest developments in machine learning and AI

• Serve as senior ML technical advisor to the company’s data science and production engineering teams

• Represent the company at ML conferences and meetups

• Mentor ML engineers and raise the overall bar for Machine Learning at the company

What it takes

• 10-12 years of experience building and improving large-scale ML or data platforms.

• A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field.

• Deep expertise in Databricks lakehouse architecture, including governance via Unity catalog, orchestration via Workflows, and cost optimization

• Proven ability to design systems that support multiple data science teams and production workloads

• Strong background in distributed systems, ML infrastructure, and cloud architecture.

• Demonstrated technical leadership across teams and orgs; ability to influence without authority

• Experience integrating LLM workflows into enterprise platforms is a plus

• Previous contributions to open source ML Infrastructure projects or research publications is a very strong plus

Tech Stack

the company uses a modern cloud based tech stack. For this role, you’ll want to be proficient with the following:

CategoryTechnologiesLanguages

Python, SQL, Kotlin

ML Frameworks

PyTorch, PySpark, MLFlow

Big Data & Processing

Spark, Kafka, Databricks, Snowflake, Fivetran, Iceberg, Unity Catalog, Datadog, Airflow, Cockroach DB, MySQL

Cloud & Infrastructure

AWS, S3, SageMaker, Kubernetes, Docker, GitHub Actions, Terraform

Generative AI

Claude Sonnet 4.5, ChatGPT 5.2

Salary Range

California: the pay range for this role is $295,000 to $405,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

**Hybrid the company employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday).* Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting.*

Why you’ll love working at the company

• Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.

• Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day.

• Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours.

• Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work.

• Belonging: We're intentional about building an environment where every the company employee has equal access to opportunities, growth, and success.

the company was founded in 2017 by a team of early product and engineering leads from Square. We’re backed by some of the top investors in retail and tech including: Y Combinator, Lightspeed Venture Partners, Forerunner Ventures, Khosla Ventures, Sequoia Capital, Founders Fund, and DST Global. We have headquarters in San Francisco and Kitchener-Waterloo, and a global employee presence across offices in Toronto, London, and New York. To learn more about the company and our customers, you can read more on our blog.

the company provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression.

the company