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Machine Learning Engineer Opt Jobs in California

Hadrian

Machine Learning Engineer

Los Angeles, CA · On-site

The Senior Machine Learning Engineer will be responsible for designing, building, and scaling advanced software systems to automate Design for Manufacturing analysis, utilizing deep learning models ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

They are seeking Machine Learning Engineers to build their platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to core technology and product features.

Aquabyte

Machine Learning Engineer

San Francisco, CA · On-site

$130K - $170K/yr

Aquabyte is seeking a Machine Learning Engineer to help develop and deploy new algorithms to fish farms across the world. You'll be responsible for software and machine learning model development of ...

Skild AI

Machine Learning Engineer

San Mateo, CA · On-site

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...

Gotion Inc.

Machine Learning Engineer

Fremont, CA · On-site

They are seeking a highly motivated Machine Learning Engineer to design and implement machine learning models for advanced battery products, collaborating with cross-disciplinary teams to address ...

Latent

Machine Learning Engineer

San Francisco, CA · On-site

$225K - $300K/yr

Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For ...

Advantest

Machine Learning Engineer

San Jose, CA

Advantest is seeking a motivated Junior Machine Learning Engineer to support the development of datadriven and MLpowered solutions for semiconductor R&D, test, and operations teams. In this role,you ...

BeeGenius

AI/Machine Learning Engineer

Sunnyvale, CA · On-site

BeeGenius is building the future of work, and they are seeking an AI/Machine Learning Engineer to join their team. In this role, you will be responsible for developing and implementing machine ...

Machina Labs

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of what's possible in smart manufacturing. In this role, you will design, build, train, and deploy ...

Adobe

Machine Learning Engineer

San Jose, CA

As a Machine Learning Engineer, you will play a key role in developing machine learning models and algorithms. Our team is dedicated to solving complex business challenges through innovative machine ...

Apple

Machine Learning Engineer

Cupertino, CA · On-site

As a Machine Learning Engineer on our core AI/ML team, you will design and build GenAI-powered features and workflows leveraging LLMs and modern AI techniques. You will collaborate closely with ...

Apple

Machine Learning Engineer

Cupertino, CA · On-site

Apple's Health Sensing team is seeking a versatile Machine Learning Engineer to develop next-generation health algorithms that deliver meaningful insights to users by combining classical ML, signal ...

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Machine Learning Engineer Opt information

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What is the difference between Machine Learning Engineer Opt vs Data Scientist?

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

What are popular job titles related to Machine Learning Engineer Opt jobs in California? For Machine Learning Engineer Opt jobs in California, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Opt jobs in California look for? The top searched job categories for Machine Learning Engineer Opt jobs in California are:
What cities in California are hiring for Machine Learning Engineer Opt jobs? Cities in California with the most Machine Learning Engineer Opt job openings:
Machine Learning Engineer Opt jobs near you
Infographic showing various Machine Learning Engineer Opt job openings in California as of May 2026, with employment types broken down into 90% Full Time, 4% Part Time, 3% Temporary, and 3% Contract. Highlights an 100% Physical job distribution.

Machine Learning Engineer

RZR Global Inc.

San Francisco, CA • On-site

Full-time

Posted 9 days ago

Job description

Who are we?RZR Global is an AI-driven company specializing in mobile advertising solutions designed to fuel revenue growth. We leverage AI to discover audiences in a privacy-first environment through trillions of contextual bidding signals and proprietary behavioral models. Our audience engagement platform includes creative strategy and execution. We handle 5 million mobile ad requests per second from over 10 billion devices, driving performance for both publishers and brands. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC.
The role?
We are seeking a motivated and detail-oriented Machine Learning Engineer to join our team. As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with Senior MLE and other team members to drive impactful machine learning projects and contribute to innovative solutions.
What will you do?
  • Support the development of machine learning models to address challenges in programmatic advertising, such as predicting user responses, forecasting bid landscapes, and detecting fraud.
  • Collaborate with senior data scientists and cross-functional teams (product, engineering, and analytics) to integrate models into production workflows.
  • Analyze the impact of integrating new data sources and features into our models.
  • Build and maintain data pipelines to process and prepare large datasets for model training and evaluation.
  • Contribute ideas and assist in testing new tools, methodologies, and technologies to improve our machine learning capabilities.
  • Document experiments, assumptions, and outcomes; maintain reproducibility
What are we looking for?
  • Bachelor's degree in Mathematics, Physics, Computer Science, or a related technical field.
  • At least 2 years of professional experience in machine learning, statistical analysis, and data analysis.
  • Experience with machine learning techniques such as regression, classification, and clustering.
  • Proficiency in Python and SQL and familiarity with big data tools (e.g., Spark) and ML libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
  • Strong grasp of probability, statistics, and data analysis principles.
  • Ability to work effectively in a team environment, with good communication skills to explain complex concepts to diverse stakeholders.
Nice-to-Have
  • Familiarity with system programming languages including C++ and Rust is a plus.
  • Exposure to online inference systems, gRPC/REST model endpoints, or streaming features (Kafka/Flink)
  • Ad-tech familiarity: auction dynamics, pacing, fraud signals, creative personalization.

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