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Mlops Engineer Remote Jobs in California (NOW HIRING)

Mercor

MLOps Engineer - AI Trainer

San Francisco, CA · Remote

$70 - $110/hr

Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams to close knowledge gaps and improve AI model performance in MLOps , training infrastructure, and ML ...

FieldAI

Senior Software Engineer, MLOps

Irvine, CA · On-site +1

$131K - $173K/yr

We are seeking a skilled and motivated Senior MLOps Engineer to join our engineering team. In this ... Also, while we enjoy being together on-site, we are open to exploring a hybrid or remote option.

FieldAI

Senior Software Engineer, MLOps

Irvine, CA · On-site +1

$131K - $173K/yr

We are seeking a skilled and motivated Senior MLOps Engineer to join our engineering team. In this ... Also, while we enjoy being together on-site, we are open to exploring a hybrid or remote option.

Sedgwick

Senior Engineer - LLMOps & MLOps

Los Angeles, CA · On-site +1

$112K - $154K/yr

... Engineer - LLMOps & MLOps Role Overview This is a high-stakes, execution-focused role within the ... remote #LI-TS1 Sedgwickis an Equal Opportunity Employer and a Drug-Free Workplace. If you're ...

Mercor

ML Systems Engineer - AI Trainer

San Francisco, CA · Remote

$70 - $110/hr

Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams to close knowledge gaps and improve AI model performance in MLOps , training infrastructure, and ML ...

Redfish Recruiting

Hands-on AI/MLOps: model deployment, monitoring, CI/CD for AI/ML, experiment tracking, and ... Fully remote, work from home environment * Employee Share Option Plan * Flexible working hours

Biohub

Staff HPC Engineer

San Francisco, CA · On-site +1

... remote dev, containerization, MLOps workflows). What You'll Bring Essential * Bachelor's or ... Strong scripting/programming skills (Python, Bash) and familiarity with version control (Git)

DocuSign

Sr. Data Platform Engineer

San Francisco, CA · On-site +1

$134K - $161K/yr

Stay current on Snowflake releases, the modern data stack, BI tooling, AI/ML, MLOps, and generative ... Employee divides their time between in-office and remote work. Access to an office location is ...

DocuSign

Senior Software Engineer

San Francisco, CA · On-site +1

$144K - $190K/yr

... RAG, MLOps, Python * Drive root cause analysis and implement long-term solutions for production ... Employee divides their time between in-office and remote work. Access to an office location is ...

DataRobot

Agentic AI Intern

San Francisco, CA · Remote

... engineers to focus on higher-order problems. This is a fully remote position. The program runs ... Use the DataRobot platform - including AutoML, GenAI tooling, and MLOps capabilities - to design ...

DataRobot

Agentic AI Intern

San Francisco, CA · Remote

... engineers to focus on higher-order problems. This is a fully remote position. The program runs ... Use the DataRobot platform - including AutoML, GenAI tooling, and MLOps capabilities - to design ...

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Mlops Engineer Remote information

What are some common challenges faced by remote MLOps Engineers, and how can they be addressed?

Remote MLOps Engineers often encounter challenges related to communication and collaboration, especially when coordinating with data scientists, developers, and operations teams across different time zones. To overcome these challenges, it's essential to establish clear documentation practices, utilize collaborative platforms for workflow management, and schedule regular virtual meetings to ensure alignment. Additionally, maintaining strong version control and automated CI/CD pipelines helps streamline model deployment and monitoring, reducing friction caused by remote coordination. Building proactive communication habits and leveraging cloud-based tools can significantly improve efficiency and team cohesion.

What is the difference between Mlops Engineer Remote vs Data Engineer?

AspectMlops Engineer RemoteData Engineer
Required CredentialsBachelor's in CS, Data Science, or related; experience with cloud platforms and ML toolsBachelor's in CS, Data Engineering, or related; strong SQL and ETL skills
Work EnvironmentRemote, collaborative teams, cloud-based infrastructureRemote or on-site, data pipelines, cloud or on-premises systems
Industry UsageTech, AI, ML-focused companiesFinance, healthcare, tech, and other data-driven industries

While both roles involve working with data and cloud platforms, Mlops Engineers focus on deploying and maintaining machine learning models in production, often working remotely with ML-specific tools. Data Engineers primarily build and manage data pipelines and infrastructure. The roles overlap in cloud experience and data handling but differ in their core focus areas.

What does an MLOps Engineer do, especially in a remote role?

An MLOps Engineer is responsible for streamlining and automating the deployment, monitoring, and management of machine learning models in production environments. Working remotely, they collaborate with data scientists, software engineers, and IT teams using cloud-based tools to ensure that ML models are scalable, reliable, and maintainable. Their tasks often include setting up CI/CD pipelines for ML workflows, managing model versioning, and monitoring model performance over time. Remote MLOps Engineers leverage communication and project management tools to stay aligned with distributed teams and ensure seamless operations.

What are the key skills and qualifications needed to thrive as an MLOps Engineer (Remote), and why are they important?

To thrive as an MLOps Engineer, you need a solid background in machine learning, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, and cloud platforms such as AWS or Azure, as well as certifications in cloud services or DevOps, are highly valuable. Strong problem-solving, collaboration, and communication skills help you bridge the gap between data science and operations teams in a remote setting. These competencies are crucial for building scalable, reliable machine learning systems that deliver real-world value efficiently.
What are the most commonly searched types of Mlops Engineer jobs in California? The most popular types of Mlops Engineer jobs in California are:
What are popular job titles related to Mlops Engineer Remote jobs in California? For Mlops Engineer Remote jobs in California, the most frequently searched job titles are:
What job categories do people searching Mlops Engineer Remote jobs in California look for? The top searched job categories for Mlops Engineer Remote jobs in California are:
What cities in California are hiring for Mlops Engineer Remote jobs? Cities in California with the most Mlops Engineer Remote job openings:
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Infographic showing various Mlops Engineer Remote job openings in California as of July 2026, with employment types broken down into 57% Full Time, and 43% Contract. Highlights an 100% Remote job distribution.
MLOps Engineer - AI Trainer

MLOps Engineer - AI Trainer

Mercor

San Francisco, CA • Remote

$70 - $110/hr

Full-time

Posted 3 days ago

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: JAX Expert
Type: Contract
Compensation: $70–$110/hour
Location: Remote
Commitment: 40 hours/week

Role Responsibilities

  • Guide research and engineering teams to close knowledge gaps and improve AI model performance in MLOps, training infrastructure, and ML framework-level topics.
  • Design challenging, domain-relevant tasks and write accurate, well-structured solutions to MLOps and ML systems problems.
  • Evaluate MLOps tasks and solutions and provide clear, written technical feedback.
  • Develop guidelines and detailed rubrics/evaluation frameworks to assess training pipeline design, distributed systems reasoning, and kernel-level optimization across tasks.
  • Collaborate with other subject matter experts to ensure consistency and accuracy in training data.

Qualifications

Must-Have

  • 2+ years of dedicated professional experience in ML infrastructure, MLOps, or ML systems engineering at a recognized, top-tier organization.
  • Hands-on production experience with JAX at scale.
  • Experience writing or optimizing custom GPU kernels using Pallas or Triton.
  • Demonstrable career progression.
  • Ability to engage reliably for at least 40 hours/week during weekdays.
  • Strong written communication skills and the ability to explain complex technical decisions clearly.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.


#hiringmercor