or apply directly on Atomic Machines's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 20 days Atomic Machines's roles stay open a median of 45 days
- Reposted
- No
- Salary listed
- No 0% of Atomic Machines's roles list one
- Ghost-job risk at Atomic Machines
- high 17 stale, 3 reposted of 27 open
- Hiring momentum
- 43 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-09-17
Measured from postings appearing on and disappearing from Atomic Machines's own greenhouse board since 2026-08-03. Full hiring picture for Atomic Machines.
About this role
As an MLOps Engineer at Atomic Machines, you will be responsible for building and maintaining the infrastructure that transitions AI and machine learning models from experimentation to reliable production. Your role will involve developing the MLOps platform, operating model serving infrastructure, and creating data pipelines while collaborating with cross-functional teams to ensure the models improve through continuous feedback and retraining.
- benefits
- 1/5
- freshness
- 4/5
- career value
- 4/5
- role clarity
- 5/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Atomic Machines as an employer.
What you need
- 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
- Strong DevOps fundamentals, including CI/CD, containers, Kubernetes, cloud infrastructure, and infrastructure-as-code
- 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
Nice to have
- Experience with feature stores, human-in-the-loop systems, active learning, or data-labeling infrastructure
- Robotics or robotic automation experience, including sensors, vision systems, or robotics data
- Experience operating ML systems in manufacturing or other physical-world environments
- Experience building internal tools for expert feedback, labeling, model evaluation, or model interaction
- Experience designing shared ML infrastructure or platforms used across multiple teams or applications
What you get
- Equity and benefits
Worth weighing
- Salary range is $200,000 — $250,000 USD
- Role open across multiple levels, which may affect team dynamics and expectations
- Focus on DevOps-oriented MLOps may limit exposure to other areas of machine learning
Summarised from Atomic Machines's posting. Read the full original.
Listed by Atomic Machines on their greenhouse job board, last confirmed open on 2026-09-17. PitchMeAI is not the employer.
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