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Assistant Machine Learning Quant Jobs in California

Qualcomm

Machine Learning Engineer

San Diego, CA · On-site

$122K - $184K/yr

Principal Duties and Responsibilities: • Applies Machine Learning knowledge to assist in extending training or runtime frameworks or model efficiency software tools with new features and ...

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 ...

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 ...

Magnopus

Machine Learning Engineer II

Los Angeles, CA · On-site

$100K - $150K/yr

Required Qualifications * 4+ years full time work experience in Machine Learning, Data Engineering or related quantitative field with a track record of delivering end-to-end ML products * Experience ...

True Anomaly

Machine Learning Engineer

Long Beach, CA · On-site

They are seeking a Machine Learning Engineer to join their Applied Algorithms and Autonomy team ... Responsibilities : • Assist in the development, training, and evaluation of ML models across a ...

Adobe

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123K - $169K/yr

They are seeking a Senior Machine Learning Engineer to lead the development of ML models and ... quantitative field. Company : Adobe is a software company that provides its users with digital ...

Poesis LLC

Machine Learning Engineer

Menlo Park, CA

We're hiring our Founding ML Engineer, the first full-time machine learning hire who will turn ... Required Competencies * 5-10+ years of experience as an ML Engineer, Quant Engineer, or similar ...

Ema

Software Engineer, Machine Learning

Bodega Bay, CA · On-site

$135K - $200K/yr

D. in Computer Science, Machine Learning, or a related quantitative field. * At least 2 years of industry experience in building and deploying production-level machine learning models. * Deep ...

Ema

Software Engineer, Machine Learning

San Francisco, CA · On-site

$135K - $200K/yr

D. in Computer Science, Machine Learning, or a related quantitative field. * At least 2 years of industry experience in building and deploying production-level machine learning models. * Deep ...

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Assistant Machine Learning Quant information

What are Assistant Machine Learning Quants?

Assistant Machine Learning Quants are entry-level professionals in quantitative finance who support senior quants by applying machine learning techniques to analyze financial data, build predictive models, and develop trading strategies. Their responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They work closely with quantitative researchers and traders to improve algorithmic trading systems and risk management processes. This role typically requires strong programming skills, a solid understanding of machine learning concepts, and familiarity with financial markets.

How does an Assistant Machine Learning Quant typically collaborate with senior quants and data scientists on projects?

As an Assistant Machine Learning Quant, you will often work closely with senior quantitative researchers and data scientists by supporting model development, data preprocessing, and feature engineering tasks. You may contribute to brainstorming sessions, implement prototypes, and assist in backtesting trading strategies or risk models. This collaborative environment provides valuable mentorship opportunities and exposure to best practices in quantitative analysis and machine learning within the finance industry. Effective communication and a willingness to learn from senior team members are key to success in this role.

What are the key skills and qualifications needed to thrive as an Assistant Machine Learning Quant, and why are they important?

To thrive as an Assistant Machine Learning Quant, you need strong quantitative skills, a background in statistics or mathematics, and typically a degree in a STEM field. Familiarity with programming languages such as Python or R, experience with machine learning frameworks, and knowledge of financial modeling tools are essential. Strong problem-solving abilities, attention to detail, and effective communication are standout soft skills in this role. These competencies enable accurate model development, efficient data analysis, and clear collaboration with team members in high-stakes financial environments.
What are the most commonly searched types of Machine Learning Quant jobs in California? The most popular types of Machine Learning Quant jobs in California are:
What are popular job titles related to Assistant Machine Learning Quant jobs in California? For Assistant Machine Learning Quant jobs in California, the most frequently searched job titles are:
What job categories do people searching Assistant Machine Learning Quant jobs in California look for? The top searched job categories for Assistant Machine Learning Quant jobs in California are:
What cities in California are hiring for Assistant Machine Learning Quant jobs? Cities in California with the most Assistant Machine Learning Quant job openings:
Assistant Machine Learning Quant jobs near you
Infographic showing various Assistant Machine Learning Quant job openings in California as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Machine Learning Engineer

RZR Global Inc.

San Francisco, CA • On-site

Full-time

Posted 21 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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