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Quant Developer Internship Jobs in California (NOW HIRING)

Data Engineer

Palo Alto, CA · On-site

$134K - $161K/yr

... software engineering experience (internship experience is applicable) • Experience in ... quantitative analysis to guide technical and product decision, including familiarity of scaling ...

... engineering experience (internship experience is applicable) * Experience in implementing or ... Strong statistical intuition and the ability to use quantitative analysis to guide technical and ...

Data Engineer

Palo Alto, CA · On-site

$134K - $161K/yr

... engineering experience (internship experience is applicable) * Experience in implementing or ... Strong statistical intuition and the ability to use quantitative analysis to guide technical and ...

New

Data Engineer

Palo Alto, CA

$134K - $161K/yr

... engineering experience (internship experience is applicable) * Experience in implementing or ... Strong statistical intuition and the ability to use quantitative analysis to guide technical and ...

Strategic Finance Analyst

Menlo Park, CA · On-site

$90K - $117K/yr

Collaborate with PMs and Sales Work alongside Engineering, Product Managers, and Sales to evaluate ... quantitative and qualitative data through coursework, projects, or internships. You may not have ...

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Quant Developer Internship information

What is a Quant Developer Internship?

A Quant Developer Internship is a temporary position, usually for students or recent graduates, that offers hands-on experience in quantitative finance and software development. Interns work with quantitative analysts and developers to design, implement, and optimize financial models and trading algorithms. The role typically involves programming, data analysis, and collaborating with other teams to solve real-world financial problems. This internship is an excellent opportunity for those interested in combining finance, mathematics, and computer science in a professional setting.

What is the difference between Quant Developer Internship vs Quant Analyst Internship?

AspectQuant Developer InternshipQuant Analyst Internship
Required CredentialsTypically pursuing or holding a degree in Computer Science, Mathematics, or related fieldsUsually pursuing or holding a degree in Finance, Economics, or related fields
Work EnvironmentHands-on coding, software development, and algorithm implementationData analysis, financial modeling, and strategy development
Employer & Industry UsageUsed in hedge funds, investment banks, and trading firms focusing on technology-driven rolesCommon in asset management firms, hedge funds, and financial institutions focusing on market analysis

While both internships involve finance and quantitative skills, Quant Developer Internships focus more on programming and software development, whereas Quant Analyst Internships emphasize financial analysis and modeling. Candidates should choose based on their strengths in coding versus financial analysis.

What are some common challenges faced during a Quant Developer Internship, and how can interns overcome them?

Quant Developer Interns often encounter challenges such as adapting to complex financial models, working with large datasets, and mastering specialized programming languages like Python or C++. To overcome these, interns should proactively seek guidance from senior team members, participate in regular code reviews, and allocate time to strengthen their understanding of both financial concepts and software development best practices. Collaboration and open communication within the team are crucial for navigating technical obstacles and successfully delivering project tasks.

What are the key skills and qualifications needed to thrive as a Quant Developer Intern, and why are they important?

To thrive as a Quant Developer Intern, you need a strong background in mathematics, statistics, and programming, typically demonstrated through a degree in quantitative fields like computer science, mathematics, or engineering. Familiarity with programming languages such as Python, C++, or Java, and experience using financial modeling tools or libraries are highly valued. Analytical thinking, attention to detail, and effective communication are critical soft skills for collaborating with teams and interpreting complex data. These skills and qualities are essential for developing robust quantitative models and contributing effectively to quantitative research and trading strategies.
What are the most commonly searched types of Quant Developer jobs in California? The most popular types of Quant Developer jobs in California are:
What job categories do people searching Quant Developer Internship jobs in California look for? The top searched job categories for Quant Developer Internship jobs in California are:
What cities in California are hiring for Quant Developer Internship jobs? Cities in California with the most Quant Developer Internship job openings:
Infographic showing various Quant Developer Internship job openings in California as of July 2026, with employment types broken down into 84% Full Time, 5% Part Time, 2% Temporary, and 9% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution.

Data Engineer

xAI

Palo Alto, CA • On-site

$134K - $161K/yr

Full-time

Posted 21 days ago


Job description

Job Summary:
xAI is focused on creating AI systems that enhance human knowledge and scientific discovery. The Data Engineer will develop systems and processes for data acquisition, preparation, and quality evaluation to support model training, collaborating with various teams to ensure high-quality data is available for AI models.
Responsibilities:
• Analyze the performance and impact of data used throughout the model training lifecycle
• Investigate anomalous model behavior and rigorously identify the data issues that drive poor downstream performance
• Design, build, and improve the data cleaning, transformation, and quality-control steps required to produce high-quality training data
• Research, evaluate, and develop frontier methods for improving data quality and effectiveness in AI model development
• Apply statistical techniques and empirical analysis to make informed, data-driven decisions about dataset quality and model outcomes
• Partner across teams to identify where data needs exist and define the highest-impact opportunities for new data acquisition and improvement
• Build and maintain production-grade data pipelines, tooling, and software systems that ingest, process, validate, and deliver data for training
• Develop metrics, evaluation frameworks, and monitoring systems to assess how data quality influences model behavior at scale
• Fuse data from multiple sources into reliable, usable datasets for research and production model training
• Create shared datasets, tooling, and internal data products that enable other teams to analyze, debug, and improve model performance
Qualifications:
Required:
• Bachelor’s degree in computer science, data science, physics, mathematics, or a STEM discipline
• 1+ years of data/software engineering experience (internship experience is applicable)
• Experience in implementing or analyzing language models or neural networks
Preferred:
• Professional experience in analytics, data science, machine learning, or data engineering
• Experience building and operating production data pipelines for neural network or large-scale machine learning workloads
• Strong experience with Python and the broader ecosystem of libraries and tools used in modern machine learning and data development
• Experience working with Parquet or similar columnar storage formats in large-scale data systems
• Familiarity with Kubernetes and distributed production environments
• Experience developing predictive models and machine learning pipelines, including clustering, forecasting, anomaly detection, or related techniques
• Experience working with very large-scale datasets, including terabyte- to petabyte-scale data systems
• Strong statistical intuition and the ability to use quantitative analysis to guide technical and product decision, including familiarity of scaling ladder design studies
• Ability to operate effectively in a dynamic environment with evolving priorities, changing requirements, and fast-moving technical challenges
• Demonstrated ability to take ownership of ambiguous problems, drive projects independently, and develop new expertise where needed
Company:
xAI develops AI software and computational infrastructure designed for scientific discovery, automated reasoning, and data processing It is a sub-organization of SpaceX. Founded in 2023, the company is headquartered in Palo Alto, USA, with a team of 1001-5000 employees. The company is currently Late Stage.