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Assistant Machine Learning Quant Jobs in Hercules, CA

Poesis

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

About the Role At Poesis, machine learning and artificial intelligence open the door to improved ... Familiarity with quantitative investing, portfolio construction, or risk management * Experience ...

MSCI

Machine Learning Researcher

San Francisco, CA · On-site

$144K - $187K/yr

Strong interest in quantitative finance * Expert programming skills * Publication record in machine learning or quantitative finance (preferred) * Ability to communicate complex ideas clearly to ...

MSCI

Machine Learning Researcher

San Francisco, CA · On-site

$144K - $187K/yr

Strong interest in quantitative finance * Expert programming skills * Publication record in machine learning or quantitative finance (preferred) * Ability to communicate complex ideas clearly to ...

MSCI

Machine Learning Researcher

San Francisco, CA · On-site

$144K - $187K/yr

Strong interest in quantitative finance * Expert programming skills * Publication record in machine learning or quantitative finance (preferred) * Ability to communicate complex ideas clearly to ...

Reducto

Machine Learning Engineer

San Francisco, CA · On-site

They are seeking a Machine Learning Engineer to train and deploy critical models for their core ... quantitative approach to building products. Ability to debug, experiment, and iterate fast. You ...

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 · 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 ...

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Assistant Machine Learning Quant information

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How much do assistant machine learning quant jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for assistant machine learning quant in Hercules, CA is $19.93, according to ZipRecruiter salary data. Most workers in this role earn between $18.03 and $21.25 per hour, depending on experience, location, and employer.

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.
Assistant Machine Learning Quant jobs near you
Infographic showing various Assistant Machine Learning Quant job openings in Hercules, CA as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $41,459 per year, or $19.9 per hour.

Machine Learning Engineer

Poesis

San Francisco, CA • On-site

$200K - $280K/yr

Full-time

Medical, Dental, Vision

Posted 26 days ago

Job description

About Poesis
Whoever builds the leading intelligence for finance will create far more than returns. Poesis is the AI-native investment firm running autonomous agents that predict markets, construct portfolios, and manage risk. Our founders managed institutional capital at Capital Group ($3T AUM) and led enterprise ML at Goldman Sachs and Amazon. We're building a new type of firm, where live capital is the training ground for an intelligence that compounds with every signal.
About the Role
At Poesis, machine learning and artificial intelligence open the door to improved alpha discovery, higher quality decision-making and intelligent risk management. We're looking for an exceptional Machine Learning Engineer to help build the systems that make this possible. In this role, you'll develop models, signals and evaluation frameworks that power investment decision-making across the platform. You'll work across the full machine learning lifecycle, from experimentation and model and agent development to deployment and iteration, with significant ownership over both research and production outcomes.
Responsibilities
  • Rapidly implement and iterate on machine learning models, signals and research ideas
  • Design and run experiments to evaluate and improve model and agent performance and investment impact
  • Build reproducible workflows for feature generation, training, validation and evaluation
  • Work with large-scale financial, fundamental and alternative datasets to identify predictive signals and improve model performance

Required Competencies
  • 5+ years experience as a Machine Learning Engineer, or related role
  • Prior experience at a frontier AI lab, agentic startup, leading hedge fund, big tech company, or similar
  • Strong Python and SQL skills, with experience working with large-scale datasets
  • Experience developing, evaluating and deploying machine learning models in production environments
  • Success building reproducible research workflows and experimentation frameworks
  • Familiarity with modern AI systems, including LLMs, evaluation frameworks, and agent workflows
  • Skill leveraging Claude Code, Codex, or other coding agents
  • BS/MS/PhD in Computer Science or a related field, or equivalent practical experience

Preferred Competencies
  • Experience developing ML and AI systems using financial, fundamental, alternative, or time-series datasets
  • Familiarity with quantitative investing, portfolio construction, or risk management
  • Experience with PyTorch or TensorFlow, and AI workflows for parsing financial documents (filings, transcripts)

Location
Hybrid: 3 days per week on-site at our office in Menlo Park, CA. Relocation allowance available.
Benefits
We offer excellent medical, dental, and vision coverage, alongside a strong benefits package that includes catered lunches in our Menlo Park office, commuter benefits, and more.
Current legal authorization to work in the US required; continuing work visa sponsorship available for full-time employees.
Working at Poesis
As an early team member, you'll help shape not just the product, but how the company operates. Your decisions will have lasting impact across the business. You'll build from first principles, with no legacy systems, or entrenched processes slowing you down. Our team is made up of people from elite companies and universities who are low ego, collaborative, and excited to build together.

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