True Talent Solutions Partners

Machine Learning Infrastructure Engineer

San Francisco
Salary
$200,000 - $400,000 annually
Level
Mid
Work type
On-site · San Francisco
Visa
Not offered

Open. First seen 5 November 2026.

Apply on the company's site →

About the role

About the Role

Join an AI research team building large-scale models for physical systems, with weather as an initial application. You will develop the infrastructure for distributed model training and inference, helping turn large volumes of observational data into useful predictions and insights.

What You'll Do

  • Design, deploy, and maintain distributed machine learning training and inference clusters.
  • Build scalable pipelines for petabyte-scale datasets and manage model training across the machine learning lifecycle.
  • Test training approaches, including parallelization methods and numerical precision trade-offs across model sizes.
  • Profile and debug low-level GPU operations to improve performance.
  • Evaluate research and apply relevant techniques to infrastructure and training workflows.
  • Analyze training experiments, including results from ablation studies, to inform model development.

What We're Looking For

  • Two to ten years of experience building large-scale machine learning infrastructure for pretrained or foundation models.
  • Hands-on experience with compute clusters, data infrastructure, inference systems, and distributed training.
  • Strong skills in optimizing large-scale training, data, or inference workloads, including GPU performance debugging.
  • Proficiency with distributed training frameworks such as FSDP or DeepSpeed, and experience with CUDA and JAX.
  • Experience with Python, C++, Linux, NVIDIA GPUs, and cloud platforms such as GCP, AWS, or Azure.
  • Familiarity with Docker, Kubernetes, distributed task management, model serving, monitoring, logging, and observability.
  • Background in physical AI or AI for science, such as robotics, self-driving, or biology, and interest in mission-driven work.
  • A generalist approach to the machine learning lifecycle and experience delivering in fast-paced, time-sensitive environments.

Compensation & Benefits

Base salary is $200,000 to $400,000 USD annually. Visa sponsorship is not available. Relocation support is provided.

Location

On-site in San Francisco, California, United States, five days per week.

What this role asks for

Particular to this role

C++ · CUDA

Rare in True Talent Solutions Partners's other 125 open postings.

Standard for DevOps / SRE / cloud roles

AWS · Azure · Docker · GCP · Kubernetes · Linux · Python

Common in DevOps / SRE / cloud postings at any company.

Compared with True Talent Solutions Partners's other open jobs.

The team: Client Roles

This role is one of 126 open in Client Roles. 126 were posted in the last 30 days, including 6 lead roles: the team is hiring the people who run it too.

WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS

Python (73 of 126), TypeScript (47 of 126), LLM (46 of 126), React (43 of 126), Machine Learning (37 of 126), AWS (32 of 126), JavaScript (27 of 126)

OTHER ROLES ON THIS TEAM

From the team and dates on True Talent Solutions Partners's own job board.

Posting history

Reposted once since 29 October 2026: a posting for this role in San Francisco was taken down and the role was posted again.

  • 5 November 2026 – open (this posting)
  • 29 October 2026 – closed 2 November 2026

Salary context

7 other open postings titled Machine Learning Infrastructure Engineer state a salary: median USD 200,000 to USD 350,000 a year.

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