Machine Learning Engineer, Infrastructure
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Sign up to see compensation estimateThe Opportunity:
Our client, a category-defining AI platform company based in the San Francisco Bay Area, is seeking a
Machine Learning Engineer (Infrastructure)
to help build the next generation of AI-powered product experiences.
In this highly impactful role, you’ll design and scale the foundational ML infrastructure that enables generative AI systems and large-scale model deployment in production. This is a unique opportunity to work at the core of a rapidly growing AI product, building the systems that allow applied machine learning innovation to move quickly, reliably, and at scale.
What You’ll Be Doing:
- Design, build, and optimize scalable ML systems and data pipeline infrastructure that power AI-driven product capabilities.
- Develop and maintain production-grade training, evaluation, experimentation, and model serving frameworks.
- Partner closely with applied ML engineers to enable efficient iteration, deployment, and monitoring of models in production.
- Write high-quality, maintainable, and well-tested code across backend and infrastructure layers.
- Improve reliability, observability, and performance of distributed ML workflows in a fast-growing environment.
- Collaborate cross-functionally with product and engineering teams to solve complex AI challenges.
- Contribute to engineering culture through mentorship, technical leadership, and best practice development.
What You’ll Need To Be Successful:
- 2–5 years of professional software engineering experience.
- Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related technical field.
- Demonstrated experience designing and shipping production systems, ideally within AI/ML infrastructure (pipelines, model training, serving systems, experimentation platforms, etc.).
- Strong programming skills in languages such as Python, Go, Java, or C++.
- Solid understanding of distributed systems, scalability, and performance optimization.
- Comfort operating in a fast-paced, highly collaborative environment.
- Ownership mindset with the ability to independently drive both tactical execution and longer-term infrastructure improvements.
- Experience with, or strong interest in, generative AI and large-scale machine learning systems.
Compensation Expectations:
$175,000 – $270,000 + Equity.
