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Mlops Engineer Remote Jobs in California (NOW HIRING)

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

Senior Machine Learning Engineer

Brisbane, CA · On-site +1

$147K - $194K/yr

... remote. What you'll do: * Implement and refine DL pipelines on distributed computing platforms ... Experience cultivating MLOps and ML infrastructure best practices, especially around reliability ...

Databricks Architect

Pleasanton, CA · On-site +1

$72 - $94.50/hr

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

Solutions Engineer, NeoCloud

San Jose, CA · On-site +1

$229K - $299K/yr

While this position is remote, candidates should be located in or willing to relocate to the San ... Familiarity with AI workloads, large language models (LLM), and MLOps tools * Automation tooling ...

Solutions Engineer, NeoCloud

San Francisco, CA · On-site +1

$229K - $299K/yr

While this position is remote, candidates should be located in or willing to relocate to the San ... Familiarity with AI workloads, large language models (LLM), and MLOps tools * Automation tooling ...

Solutions Engineer, NeoCloud

San Jose, CA · On-site +1

$229K - $299K/yr

While this position is remote, candidates should be located in or willing to relocate to the San ... Familiarity with AI workloads, large language models (LLM), and MLOps tools * Automation tooling ...

Collaborate with product and engineering to establish our MLOps foundation * Take new models from ... Remote-first flexibility with a collaborative team culture. Opportunity to scale with a mission ...

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Support, even from afar, with our remote assistance. Regular salary reviews? You betcha! Ready to ...

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Support, even from afar, with our remote assistance. Regular salary reviews? You betcha! Ready to ...

Data Engineering Manager

Pasadena, CA · On-site +1

$172K - $206K/yr

Founded in 2006, Spokeo has built a dedicated, remote-first team with an average tenure of 6.9 ... Familiarity with MLOps to help design, automate, and streamline the entire lifecycle of ML models.

Founded in 2006, Spokeo has built a dedicated, remote-first team with an average tenure of 6.9 ... Familiarity with MLOps to help design, automate, and streamline the entire lifecycle of ML models.

Sr. Data Scientist

San Francisco, CA · Remote

$162K - $238K/yr

Strong understanding of feature engineering, model evaluation, and MLOps. * Ability to ... remote Notice of Collection and Use of Personal Information for California Residents: California ...

Product Manager; Data

Truckee, CA · Remote

$140K - $150K/yr

... engineers build from - Comfort working in a fully remote, fast-paced startup environment PREFERRED QUALIFICATIONS - Background in machine learning and MLOps with experience building production ...

Showing results 41-60

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:
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:
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

AbbVie

San Diego, CA • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 16 days ago


AbbVie rating

8.7

Company rating: 8.7 out of 10

Based on 100 frontline employees who took The Breakroom Quiz

14th of 86 rated pharmaceutical


Job description

Company Description

About AbbVie

At Allergan Aesthetics, an AbbVie company, we develop, manufacture, and market a portfolio of leading aesthetics brands and products. Our aesthetics portfolio includes facial injectables, body contouring, plastics, skin care, and more. Our goal is to consistently provide our customers with innovation, education, exceptional service, and a commitment to excellence, all with a personal touch. For more information, visit https://global.allerganaesthetics.com/. Follow Allergan Aesthetics on LinkedIn.

Job Description

Responsibilities

  • Own small to medium components of machine learning systems from technical designthrough implementation and delivery
  • Translate technical requirements into high-quality, maintainable code and deliver workstreamsaccording to plan
  • Build and maintain data pipelines and feature engineering workflows to support machinelearning and AI solutions
  • Design, train, evaluate, and refine machine learning models with minimal supervision, applyingsound statistical and engineering practices
  • Implement ML solutions that can be deployed into production environments as microservices,APIs, batch jobs, or streaming components
  • Support production monitoring efforts by helping define and implement metrics for modelperformance, data drift, anomalies, and retraining triggers
  • Collaborate with Data Engineers, Software Engineers, Data Scientists, Product partners, andbusiness stakeholders to deliver project objectives
  • Understand system design, data models, and technical artifacts well enough to contribute toimplementation decisions and tradeoffs
  • Follow governance, documentation, coding, and source control standards consistently
  • Demonstrate flexibility and proactively support teammates with day-to-day responsibilities asneeded
  • Clearly document and communicate work progress, technical decisions, and outcomes totechnical and non-technical audiences
Qualifications

Required Experience & Skills

  • Completed BS, MS, or PhD in Computer Science, Mathematics, Statistics, Data Science,Engineering, Operations Research, or other quantitative field
  • 3+ years of practical experience building, evaluating, scaling, and deploying machine learning pipelines with Python
  • Strong programming skills in Python and solid understanding of core computer scienceprinciples
  • Experience with data manipulation frameworks such as Pandas and PySpark
  • Experience with machine learning libraries such as scikit-learn, HuggingFace,TensorFlow/Keras, PyTorch, or MLlib
  • Experience with MLOps practices such as automated model deployment, model performancemonitoring, data drift detection
  • Working knowledge of SQL and relational data structures
  • Ability to design, train, and evaluate machine learning models using standard best practicessuch as model selection, validation, bias/variance tradeoffs, and performance assessment
  • Familiarity with batch and streaming data pipeline concepts such as ETL, ELT, and stream processing
  • Experience working with cloud environments, preferably AWS
  • Familiarity with technologies such as APIs, microservices, Docker, and Kubernetes
  • Strong interpersonal, verbal, and written communication skills
  • Ability to work effectively in a remote environment using collaboration tools

Preferred Experience & Skills

  • Knowledge in domains such as recommender systems, fraud detection, personalization, and marketing science
  • Experience with managing and architecting solutions on AWS
  • Familiarity with Large Language Models (LLMs), other generative AI modalities, and how they are applied in production
  • Familiarity with Snowflake, RDS, DynamoDB, Kafka, Fivetran, dbt, Airflow, Docker, Kubernetes,
  • EMR, Sagemaker, DataDog, PagerDuty, Data Cataloging tools, Data Observability tools and Data Governance tools
Additional Information

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: 

  • The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. 

  • We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.

  • This job is eligible to participate in our long-term incentive programs. 

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law.

AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled. 

US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html

US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:

https://www.abbvie.com/join-us/reasonable-accommodations.html


What AbbVie employees say

Pay

Benefits

Hours and flexibility

Workplace

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AbbVie logo

About AbbVie

Sourced by ZipRecruiter

AbbVie's mission is to discover and deliver innovative medicines that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas: immunology, oncology, neuroscience, eye care, virology, women's health, and gastroenterology, in addition to products and services across its Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on Twitter, Facebook, Instagram, YouTube, and LinkedIn.

Industry

Scientific research and development services

Company size

10,000+ Employees

Headquarters location

North Chicago, IL, US

Year founded

2013