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Mlops Engineer Remote Jobs in California (NOW HIRING)

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 ...

AbbVie

Machine Learning Engineer

San Diego, CA · On-site +1

$109K/yr

Experience with MLOps practices such as automated model deployment, model performancemonitoring ... Ability to work effectively in a remote environment using collaboration tools Preferred Experience ...

Data Piper

Databricks Architect

Pleasanton, CA · Remote

$72 - $94.50/hr

Remote 10+ years experience in data eng, data platforms & analytics, 10+ years of consulting ... Engineering Professional certification & required classes Hands-on experience in development on ...

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Mlops Engineer Remote information

What are 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 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 a remote MLOps engineer?

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:
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Mlops Engineer Remote jobs near you
Infographic showing various Mlops Engineer Remote job openings in California as of August 2026, with employment types broken down into 54% Full Time, and 46% Contract. Highlights an 100% Remote job distribution.

Machine Learning Engineer : 26-02124

Akraya Inc.

Pleasanton, CA • On-site, Remote

$55 - $60/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description


Primary Skills: Machine Learning (Expert), Python & SQL (Expert), Deep Learning & NLP (Advanced), Azure AI/ML (Advanced), MLOps & DevOps (Advanced)
Contract Type: W2 Only
Duration: 6+ Months
Location: Pleasanton, CA. Hybrid/Remote (Must Support PST Hours)
Pay Range:$55 - $60 on W2
Job Summary:
We are seeking an experienced Machine Learning Engineer to design, develop, deploy, and optimize scalable machine learning solutions for enterprise applications. The ideal candidate will have strong expertise in supervised and unsupervised learning, deep learning, natural language processing (NLP), and cloud-based AI platforms, with hands-on experience deploying production-ready ML models using Azure and MLOps best practices.
Key Responsibilities:
  • Design, develop, train, and deploy machine learning models for predictive analytics and intelligent automation.
  • Build and optimize supervised and unsupervised learning models to solve complex business problems.
  • Develop deep learning solutions using neural networks and NLP techniques.
  • Create data pipelines for feature engineering, model training, validation, and inference.
  • Deploy, monitor, and maintain ML models using Azure cloud services and MLOps best practices.
  • Collaborate with Data Scientists, Data Engineers, and business stakeholders to translate requirements into scalable AI solutions.
  • Optimize model performance, accuracy, scalability, and reliability through continuous experimentation and tuning.
  • Develop reusable Python libraries, APIs, and automation scripts for ML workflows.
  • Implement CI/CD pipelines and DevOps practices for model deployment, versioning, and lifecycle management.
  • Document technical designs, model architectures, and deployment processes while following enterprise development standards.
Must-have Skills:
  • 5+ years of experience developing and deploying Machine Learning solutions.
  • Strong expertise in Supervised and Unsupervised Machine Learning Algorithms.
  • Hands-on experience with Neural Networks and Natural Language Processing (NLP).
  • Advanced programming skills in Python, SQL, and R.
  • Experience with machine learning frameworks including TensorFlow, Keras, and PyTorch.
  • Strong experience with Microsoft Azure AI/ML services and cloud-based model deployment.
  • Hands-on knowledge of DevOps and MLOps practices, including CI/CD pipelines and model lifecycle management.
  • Experience with data preprocessing, feature engineering, model evaluation, and hyperparameter tuning.
  • Strong analytical, problem-solving, and communication skills.
  • Ability to work independently while collaborating with cross-functional technical teams.
Nice-to-have Skills:
  • Experience with Azure Machine Learning, Azure Databricks, or Azure OpenAI Services.
  • Familiarity with containerization technologies such as Docker and Kubernetes.
  • Experience building REST APIs for ML model serving.
  • Knowledge of Git, version control, and automated deployment pipelines.
  • Experience working in Agile/Scrum environments and enterprise AI initiatives.
ABOUT AKRAYA
Akraya is an award-winning IT staffing firm consistently recognized for our commitment to excellence and a thriving work environment. Most recently, we were recognized Stevie Employer of the Year 2025, SIA Best Staffing Firm to work for 2025, Inc 5000 Best Workspaces in US (2025 & 2024) and Glassdoor's Best Places to Work (2023 & 2022)!
Industry Leaders in Tech Staffing
As Talent solutions provider for Fortune 100 Organizations, Akraya's industry recognitions solidify our leadership position in the IT staffing space. We don't just connect you with great jobs, we connect you with a workplace that inspires!
Join Akraya Today!
Let us lead you to your dream career and experience the Akraya difference. Browse our open positions and join our team!
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About Akraya

Sourced by ZipRecruiter

Akraya is an award-winning IT staffing firm and the staffing partner of choice for many leading companies across the US. Akraya was recently voted as a 2021 Best Staffing Firm to Temp for by Staffing Industry Analysts and voted by our employees and consultants as a 2022 Glassdoor Best Places to Work.

Industry

Recruiting and staffing services

Company size

11 - 50 Employees

Headquarters location

Santa Clara, CA, US

Year founded

2001

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