Senior Machine Learning Engineer, AI Infra

United States Digital Space LLC; Bellevue (CA); On-site; USD 209,000 - 245,000; Full time

Benefits offered by this job

Health insurance

Equity ownership

401k matching

Catered meals

Mental health benefits

Job summary

United States Digital Space LLC is seeking a Senior Software Engineer for the AI Infrastructure team in Menlo Park, CA and Bellevue, WA. You will own architecture, build scalable ML platform components, and partner with ML practitioners to accelerate model development and deployment.

You will mentor engineers, shape technical strategy, and ensure reliable, observable systems powering our AI products in production.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, or a related technical field.
• Proven ability to own and deliver complex platform systems end-to-end, from architecture to production.
• Deep expertise in model serving, distributed systems, and production ML workflows at scale.

Responsibilities

• Lead the architecture and end-to-end delivery of scalable systems for deploying, monitoring, and managing ML models in production
• Own the technical direction for key platform areas — including model serving, the feature store, and ML observability infrastructure
• Drive cross-functional partnerships with ML practitioners, data engineers, and applied AI teams to streamline workflows
• Evolve and scale our feature store to support efficient, low-latency feature retrieval across real-time and batch use cases
• Define and implement robust observability standards for model performance, data pipelines, and feature freshness across the ML platform
• Manage and optimize cloud compute resources (CPU/GPU) on AWS to support cost-effective, high-throughput training and inference at scale
• Contribute to technical strategy and roadmap discussions, and help mentor engineers on the team through design reviews and hands-on guidance

Skills

ML infrastructure

Distributed systems

Python

C++

Model serving

TensorFlow

PyTorch

Kubeflow

SageMaker

Vector search

Education

Bachelor's degree in CS/CE/related

Advanced degree a plus

Tools

TensorFlow Serving

Ray

Kubeflow

SageMaker

Elasticsearch

Qdrant

ChromaDB

Job description

Join us in building the future of finance.

Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading.

About the team + role

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. the company isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.

The AI Infrastructure team’s mission is to provide a robust, agile, and centralized AI platform — empowering teams across the company. We partner deeply across Data, Platform, and Product Engineering to define how AI gets built and run at the company — and we hold a high bar for reliability, scalability, and craft. If you’re energized by platform work that multiplies the output of an entire organization, this team is for you!

As a Senior Software Engineer on the AI Infrastructure team, you’ll be a technical anchor on our ML platform — owning the architecture and end-to-end delivery of foundational systems that power model development, deployment, and observability across the company. You’ll lead the design of complex platform capabilities including our feature store, model serving layer, and training infrastructure, while partnering closely with ML practitioners to ensure these systems accelerate their work rather than slow it down. You’ll bring senior-level judgment to ambiguous technical problems, contribute to the team’s technical strategy, and help mentor engineers earlier in their careers. Your work will directly shape how every AI product at the company gets built, scaled, and maintained in production.

This role is based in our Menlo Park, CA and Bellevue, WA office(s), with in-person attendance expected at least 3 days per week.

At the company, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams.

What you’ll do

• Lead the architecture and end-to-end delivery of scalable systems for deploying, monitoring, and managing ML models in production

• Own the technical direction for key platform areas — including model serving, the feature store, and ML observability infrastructure — from design through long-term reliability

• Drive cross-functional partnerships with ML practitioners, data engineers, and applied AI teams to streamline workflows, reduce friction, and accelerate experimentation

• Evolve and scale our feature store to support efficient, low-latency feature retrieval across real-time and batch use cases

• Define and implement robust observability standards for model performance, data pipelines, and feature freshness across the ML platform

• Manage and optimize cloud compute resources (CPU/GPU) on AWS to support cost-effective, high-throughput training and inference at scale

• Contribute to technical strategy and roadmap discussions, and help mentor engineers on the team through design reviews and hands‑on guidance

What you bring

• 6+ years of software engineering experience, with meaningful depth in ML infrastructure, data engineering, or model operations

• Demonstrated ability to own and deliver complex platform systems end-to-end, from architecture to production

• Deep expertise in model serving, distributed systems, and production ML workflows at scale

• Strong proficiency in Python, C++, or similar languages, and hands‑on experience with ML frameworks such as TensorFlow or PyTorch

• Solid knowledge of modern ML infrastructure tooling (e.g., Ray, Kubeflow, SageMaker, TensorFlow Serving, Triton)

• Hands‑on experience with large-scale search systems, including embedding models, vector databases, and distributed retrieval engines using platforms such as Qdrant, ChromaDB, or Elasticsearch with dense vector search capabilities

• Experience influencing technical direction across teams and mentoring engineers at varying levels

• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field; advanced degree a plus

What we offer

• Challenging, high-impact work to grow your career

• Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching

• Top Tier benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents

• Access to the the company Employee Fund that gives eligible US employees the opportunity to invest in a private employee fund that provides exposure to the company Ventures funds.

• Access to the best AI tools on the market and continuous AI skill-building for every employee, technical or not.

• Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more

• Employer-paid life & disability insurance, fertility benefits, and mental health benefits

• Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!

• Exceptional office experience with catered meals, events, and comfortable workspaces.

In addition to the base pay range listed below, this role is also eligible for bonus opportunities + equity + benefits.

Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands. The expected base pay range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones. For other locations not listed, compensation can be discussed with your recruiter during the interview process.

Base Pay Range:

Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC)

$209,000—$245,000 USD

Zone 2 (Denver, CO; Westlake, TX; Chicago, IL)

$184,000—$216,000 USD

Zone 3 (Lake Mary, FL; Clearwater, FL; Gainesville, FL)

$163,000—$191,000 USD

Click here to learn more about our Total Rewards, which vary by region and entity.

If our mission energizes you and you’re ready to build the future of finance, we look forward to seeing your application.

the company provides equal opportunity for all applicants, offers reasonable accommodations upon request, and complies with applicable equal employment and privacy laws. Inclusion is built into how we hire and work—welcoming d