Atomic Machines
MLOps Engineer
Emeryville, California · Senior
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odds of building a lasting career here
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
$21,187 more — $221,187 — moves this role to Level IV and 4 lottery entries. That figure is inside the range the employer already advertised.
Based on the DOL prevailing wage for this occupation and worksite, a base salary of $221,187 would place this position at wage Level IV. That figure is within the posted range, and I'd like to target it. This role classifies under "Software Developers" for prevailing-wage purposes.
DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · San Francisco-Oakland-Fremont, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
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Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
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About the role
- We are seeking an MLOps Engineer to join our AI and Modeling & Simulation org within the Data Engineering and Analytics team.
- This is a DevOps-leaning MLOps role centered on the model feedback loop: connecting production signals and expert feedback back to training so models improve as the system operates.
- We are looking for senior-level candidates who can take meaningful ownership of production ML infrastructure.
Responsibilities
- Build and evolve the MLOps platform and CI/CD: Own the path from experiment to production, including experiment tracking, model registry, packaging, automated training and retraining, deployment, and safe rollout and rollback.
- Operate model serving infrastructure: Build reliable, scalable batch, streaming, and real-time inference for models and digital twins supporting design, process control, scheduling, and inspection.
- Build ML data and feature pipelines: Turn machine telemetry, process and knowledge graphs, images, time-series, agentic conversations, and other production data into contextualized, model-ready datasets and features.
- Maintain ML data infrastructure: Support feature-store capabilities and a lakehouse foundation using Apache Iceberg on S3, with strong data quality, lineage, versioning, and reproducibility.
- Close the model feedback loop: Build model observability and human-in-the-loop systems that capture production signals and expert corrections, version them as ground truth, and feed them into evaluation and retraining workflows.
- Create paved roads for ML development: Develop standardized tooling and workflows that enable Data and AI engineers to move quickly while maintaining production reliability and reproducibility.
- Drive technical ownership: Identify infrastructure, reliability, and scalability challenges and drive solutions from design through production.
- Collaborate across disciplines: Work with Process, Chemical, Materials, Simulation, Software, Data, and AI engineers to define deployment, serving, and data-collection requirements.
- To help our recruiting team manage application volume and respond to candidates more efficiently, Atomic Machines may use AI-assisted tools.
Requirements
- Proficiency in Python and SQL.
- Hands-on experience with MLflow or similar tooling for experiment tracking, model registry, and model lifecycle management.
- Experience with S3, lakehouse technologies such as Apache Iceberg, and workflow orchestration tools such as Airflow or Dagster.
- Familiarity with manufacturing systems, sensors, process automation, or other physical-world data systems.
- Bachelor's or Master's degree in Computer Science, Data Engineering, Data Science, or a related STEM field, or equivalent practical experience.
Skills
- connecting production signals and expert feedback back to training so models improve as the system operates.
- Strong DevOps fundamentals, including CI/CD, containers, Kubernetes, cloud infrastructure, and infrastructure-as-code.
- Strong problem-solving skills, attention to data quality and reliability, and clear technical communication.
Compensation
- $200,000 - $250,000 USD
Benefits
- 5+ years of relevant industry experience building production software, infrastructure, data, or machine learning systems.
- Proven experience building and operating machine learning systems in production, with a strong MLOps/DevOps orientation.
Company info
- Founded by Jeff Holden - serial entrepreneur, ex-Amazon SVP and Uber's first Chief Product Officer - the company has raised $250 million to date.
- About The Role: We are seeking an MLOps Engineer to join our AI and Modeling & Simulation org within the Data Engineering and Analytics team.
- We are looking for senior-level candidates who can take meaningful ownership of production ML infrastructure. The scope and seniority of the role will be shaped by the candidate's experience, technical depth, and demonstrated impact.
- More senior candidates will have opportunities to shape architecture, technical direction, and engineering practices across the ML platform.
Equal opportunity
- Atomic Machines is an equal opportunity employer that values diversity and does not discriminate based on characteristics protected by applicable law.
- To request an accommodation, contact rc@atomicmachines.com.
This listing is sourced directly from Atomic Machines's careers page and normalized into a canonical job model.