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Machine Learning Assistant Jobs in California (NOW HIRING)

Hive

Machine Learning Manager

San Francisco, CA · On-site

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Hive

Machine Learning Manager

San Francisco, CA

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Apex Systems

Machine Learning Engineer

Pleasanton, CA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

As always from ai assistant Riley will give you a call, but if you think this is the perfect spot ... Position starts off as a 6 month contract Machine Learning Engineer Location: Pleasanton ...

Altera

Machine Learning Engineer

San Jose, CA · On-site

About the Role We are seeking a Machine Learning Engineer to help drive the development ... Experience with Agile methodologies, GitHub Copilot or similar AI coding assistants, and high ...

Sift

Machine Learning Engineer

San Francisco, CA · On-site

$160 - $230/hr

As a Machine Learning Engineer at Sift, you will bridge the gap between data science and large ... Familiarity with leveraging AI coding assistants (e.g., Claude Code) to accelerate development and ...

Superhuman

Machine Learning Engineer

San Francisco, CA · On-site

$180 - $260/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... As a Machine Learning Engineer on this team, you will be at the heart of our company ... Play a pivotal role in evolving Grammarly from a beloved writing assistant into an indispensable ...

Superhuman

Machine Learning Engineer

San Francisco, CA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... As a Machine Learning Engineer on this team, you will be at the heart of our company ... Play a pivotal role in evolving Grammarly from a beloved writing assistant into an indispensable ...

Sift Science, Inc

Machine Learning Engineer

San Francisco, CA · On-site

$134K - $162K/yr

As a Machine Learning Engineer at Sift, you will bridge the gap between data science and large ... Familiarity with leveraging AI coding assistants (e.g., Claude Code) to accelerate development and ...

Superhuman

Machine Learning Engineer

San Francisco, CA · On-site

$250K - $385K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... As a Machine Learning Engineer on this team, you will be at the heart of our company ... Play a pivotal role in evolving Grammarly from a beloved writing assistant into an indispensable ...

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All JobsMachine Learning JobsMachine Learning Assistant JobsMachine Learning Assistant Jobs in California

Machine Learning Assistant information

What is a machine learning assistant?

A Machine Learning Assistant is a professional who supports the development, implementation, and maintenance of machine learning models and systems. They assist data scientists and engineers by preparing datasets, conducting preliminary data analysis, running experiments, and helping to optimize algorithms. This role often involves coding, testing models, and ensuring the quality and reliability of machine learning solutions. Machine Learning Assistants play a key role in streamlining workflows and enabling faster progress in AI projects.

What are the key skills and qualifications needed to thrive as a machine learning assistant?

To thrive as a Machine Learning Assistant, a solid background in mathematics, statistics, programming (often Python), and foundational knowledge of machine learning algorithms is essential, typically supported by a relevant degree or coursework. Familiarity with tools like TensorFlow, scikit-learn, Jupyter Notebooks, and version control systems such as Git is commonly required. Strong problem-solving abilities, attention to detail, and the capability to communicate findings effectively are standout soft skills in this role. These skills ensure accurate data analysis, effective model building, and successful collaboration within multidisciplinary teams.

What are some common challenges a machine learning assistant may face when supporting data preparation and model training?

Machine Learning Assistants often encounter challenges such as cleaning large, unstructured datasets, identifying and handling missing or inconsistent data, and ensuring data privacy compliance. They also need to communicate effectively with data scientists and engineers to understand project requirements and adapt to evolving priorities. Staying organized and managing multiple tasks simultaneously—such as data preprocessing, feature engineering, and running model experiments—is crucial for success in this role.

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

The most popular types of Machine Learning jobs in California are:

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

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

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

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

What cities in California are hiring for Machine Learning Assistant jobs?

Cities in California with the most Machine Learning Assistant job openings:

Machine Learning Assistant jobs near you
Infographic showing various Machine Learning Assistant job openings in California as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer

RZR Global Inc.

San Francisco, CA • On-site

Full-time

Re-posted yesterday

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.

Role Overview

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.

Key Responsibilities

  • 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

Required Skills / Experience

  • Bachelor's or Master's degree in Mathematics, Physics, Computer Science, or a related technical field.

  • At least 1 year 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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