ZipRecruiter

Log In

1

Assistant Mlops Jobs in California (NOW HIRING)

Advantest

Software Engineer - AI/ML

San Jose, CA · On-site

... RAG), MLOps pipelines, and data visualization to optimize engineering productivity, test coverage, and decision-making across semiconductor operations. Responsibilities include: * Assist in ...

next page

Showing results 1-20

All JobsMlops JobsAssistant Mlops JobsAssistant Mlops Jobs in California

Assistant Mlops information

What is an Assistant MLOps?

Assistant MLOps are professionals who support the deployment, monitoring, and management of machine learning models in production environments. They assist senior MLOps engineers with tasks like automating workflows, managing data pipelines, maintaining infrastructure, and ensuring model performance. Their role bridges the gap between data science and IT operations, helping organizations scale and maintain their AI solutions efficiently. Assistant MLOps often have knowledge of cloud services, CI/CD tools, and basic programming, and they work closely with data scientists and engineers.

What are the typical daily responsibilities of an Assistant MLOps?

As an Assistant MLOps professional, you can expect your daily tasks to involve supporting the deployment, monitoring, and maintenance of machine learning models in production environments. This often includes collaborating with data scientists to automate model training and testing workflows, managing cloud-based resources, and ensuring that data pipelines are running smoothly. You'll also help troubleshoot issues related to model performance or infrastructure and assist in implementing best practices for version control and continuous integration. Working closely with both engineering and data teams, you'll play a key role in ensuring that ML models remain reliable and scalable in real-world applications.

What are the key skills and qualifications needed to thrive as an Assistant MLOps?

To thrive as an Assistant MLOps, you need a solid understanding of machine learning fundamentals, programming (especially Python), and experience with cloud platforms; a degree in computer science or a related field is typically preferred. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, and version control systems (e.g., Git) is important, and certifications in cloud services (AWS, Azure, GCP) can be advantageous. Strong problem-solving, communication, and collaboration skills help you bridge the gap between data science and operations teams. These combined skills ensure efficient deployment, monitoring, and maintenance of machine learning models in production environments.

What is the difference between Assistant Mlops vs Data Engineer?

AspectAssistant MlopsData Engineer
Required CredentialsCertifications in cloud platforms, basic scripting, ML toolsComputer science degree, SQL, Python, data architecture
Work EnvironmentCollaborates with ML teams, supports deployment pipelinesBuilds data pipelines, manages databases, processes large datasets
Industry UsageAI/ML projects, cloud-based environmentsData infrastructure, analytics, big data solutions

Assistant Mlops and Data Engineer roles share overlapping skills in cloud platforms and scripting. However, Assistant Mlops focuses on supporting ML deployment and operations, while Data Engineers primarily build and maintain data infrastructure. Both roles are essential in data-driven organizations but serve different functions within the data ecosystem.

What are the most commonly searched types of Mlops jobs in California?

The most popular types of Mlops jobs in California are:

What are popular job titles related to Assistant Mlops jobs in California?

For Assistant Mlops jobs in California, the most frequently searched job titles are:

What job categories do people searching Assistant Mlops jobs in California look for?

The top searched job categories for Assistant Mlops jobs in California are:

What cities in California are hiring for Assistant Mlops jobs?

Cities in California with the most Assistant Mlops job openings:

Assistant Mlops jobs near you
Infographic showing various Assistant Mlops job openings in California as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 23% Part Time, 1% Temporary, and 5% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution.

Senior Machine Learning (MLOps) Engineer- Worldwide Product Marketing

Apple

Cupertino, CA • On-site

$128K - $177K/yr

Full-time

Re-posted 4 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 678 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

Job description

As an MLOps Engineer, you will be the backbone of our machine learning infrastructure, ensuring that AI/ML systems are reliable, scalable, and continuously improving in production. You will bridge the gap between data science and engineering, driving operational excellence across the full ML lifecycle.
Description
The MLOps Engineer will drive end-to-end quality initiatives across data ingestion, model training, deployment pipelines, and MLOps tooling. This hire will build, deploy, and optimize AI/ML based applications with a strong emphasis on scalable, and production-ready systems. You will establish standard methodologies for model integration, deployment, and monitoring using CI/CD principles.
Minimum Qualifications
8 years in software engineering with demonstrated experience in large-scale software system design and implementation.
Bachelor's Degree in Software Engineering, Computer Science, Statistics, Data Mining, Machine Learning, Operations Research, or related field.
Proven track record of shipping and maintaining production-grade ML systems end-to-end.
Strong experience with distributed systems, databases (SQL/NoSQL), cloud platforms (AWS, Azure, or GCP), and container orchestration tools such as Kubernetes.
Hands-on experience with MLOps tooling and platforms such as Ray, MLflow, Kubeflow, SageMaker, Vertex AI, or similar.
Proficiency in Python and familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
Experience building and managing CI/CD pipelines for ML workflows using tools such as Jenkins, GitHub Actions, or ArgoCD.
Strong understanding of data pipeline orchestration tools such as Airflow, Prefect, or similar.
Preferred Qualifications
10 years of related experience building high-throughput, scalable applications or machine learning models in a production environment.
Familiarity with model monitoring, drift detection, and observability practices in production environments.
Excellent cross-functional communication skills with the ability to collaborate effectively across engineering and data science teams.
Comfort using LLM-based tools such as Claude, Gemini, or ChatGPT to assist with code generation, documentation, debugging, and workflow automation.
Demonstrated ability to critically evaluate and validate LLM-generated outputs, ensuring accuracy and reliability before applying them in production contexts.
Experience incorporating AI-assisted tools into day-to-day engineering workflows, with an understanding of their limitations and appropriate use cases.

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

View All Apple Jobs

Apply