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Internship Machine Learning Finance Jobs in Seattle, WA

## Staff Machine Learning EngineerApplylocations: Seattle, Washington United Statestime type: Full ... At Remitly, we are on a mission to transform lives by providing trusted financial services that ...

At Remitly, we are on a mission to transform lives by providing trusted financial services that ... As a Staff Machine Learning Engineer in Remitly's Core AI/ML team, you'll work at the heart of our ...

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Internship Machine Learning Finance information

See Seattle, WA salary details

$13

$22

$30

How much do internship machine learning finance jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for internship machine learning finance in Seattle, WA is $22.60, according to ZipRecruiter salary data. Most workers in this role earn between $19.42 and $25.43 per hour, depending on experience, location, and employer.

What is an internship machine learning finance?

Internship Machine Learning Finance positions are temporary roles where students or recent graduates work with financial organizations to apply machine learning techniques to solve finance-related problems. Interns may analyze large datasets, build predictive models, automate trading strategies, or detect fraud using machine learning algorithms. These internships provide hands-on experience in both finance and artificial intelligence, helping interns develop technical and industry-specific skills. They often require a background in programming, statistics, and a basic understanding of financial concepts.

What types of projects do interns typically work on in a machine learning finance internship?

As a Machine Learning Finance intern, you can expect to work on a variety of projects that blend quantitative analysis with practical financial applications. Common responsibilities include developing predictive models for stock prices or credit risk, analyzing large financial datasets, and building tools to automate trading strategies or detect fraud. Interns often collaborate closely with data scientists, software engineers, and finance professionals, gaining exposure to both technical and business aspects of the field. This hands-on experience is invaluable for building real-world skills and understanding the fast-paced finance environment.

What are the key skills and qualifications needed to thrive as an intern in machine learning finance, and why are they important?

To thrive as an Intern in Machine Learning Finance, you need a foundational understanding of statistics, programming (especially Python or R), and financial concepts, often supported by progress toward a quantitative degree. Familiarity with machine learning libraries (such as scikit-learn, TensorFlow, or PyTorch), data analysis tools, and version control systems like Git is typically expected. Strong analytical thinking, problem-solving abilities, and effective communication help you translate technical results into actionable financial insights. These skills are critical for developing robust models, supporting data-driven decision-making, and contributing meaningfully within interdisciplinary finance teams.

What is the difference between Internship Machine Learning Finance vs Data Analyst Intern?

AspectInternship Machine Learning FinanceData Analyst Intern
Required SkillsProgramming (Python, R), Machine Learning, Finance knowledgeData analysis, SQL, Excel, basic statistics
Work EnvironmentFinance firms, tech-driven finance teamsFinancial institutions, consulting firms, tech companies
Industry UsageFinance, Fintech, Quantitative researchFinance, marketing, consulting

Internship Machine Learning Finance focuses on applying machine learning techniques to financial data, requiring programming and finance knowledge. Data Analyst Internships involve analyzing data sets, creating reports, and using statistical tools. Both roles are common in finance-related industries but differ in technical focus and skill requirements.

What job categories do people searching Internship Machine Learning Finance jobs in Seattle, WA look for?

The top searched job categories for Internship Machine Learning Finance jobs in Seattle, WA are:

Infographic showing various Internship Machine Learning Finance job openings in Seattle, WA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $46,999 per year, or $22.6 per hour.

Machine Learning Engineer Intern (E-Commerce Recommendation Mall) - 2027 Start (PhD)

TikTok

Seattle, WA • On-site

$57/hr

Internship

Medical, Life

Posted 8 hours ago

Posted today


TikTok rating

8.2

Company rating: 8.2 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

107th of 244 rated software companies


Job description

Responsibilities
Our E-commerce Recommendation Team is responsible for building up and scaling our recommendation system to provide the best shopping experience for our TikTok users. We are looking for talented individuals to join us for an internship. PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies. Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts. Applications will be reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume (Start date, End date). Responsibilities: - Generative Recommendation Research: Drive the evolution of recommender systems from discriminative to generative paradigms; explore frontier directions such as generative retrieval and generative re-ranking/blending; continuously improve personalization capabilities while deeply optimizing the training and inference efficiency of generative models on GPUs. - LLM for Recommendation Research: Leverage Large Language Models (LLMs), Reinforcement Learning (RL), and related techniques to enhance the semantic understanding and reasoning capabilities of recommender systems, addressing core business challenges in e-commerce scenarios (e.g., cold start, long-tail item distribution, and user intent understanding). - Agentic Recommendation Research: Explore the construction of self-evolving agents and leverage agents to continuously optimize recommender systems; drive the evolution of recommender systems toward agentic architectures capable of keenly perceiving user context and making real-time, personalized decisions and adjustments. - Long-Term Value and User Experience Modeling: Explore replacing traditional heuristic rule-based systems with LLM and agent capabilities; build next-generation algorithms for measuring and optimizing long-term value (LTV) and user experience, enabling sustainable growth of the platform ecosystem.
Qualifications
Minimum Qualifications: - Currently pursuing a PhD in in Computer Science, Electrical Engineering, Mathematics, Statistics or a related discipline. - Solid foundation in machine learning and deep learning, with research or project experience in at least one of the following areas: large language models, reinforcement learning, generative models, recommender systems or information retrieval. - Proficient in Python and at least one mainstream deep learning framework (e.g., PyTorch, TensorFlow, JAX). Strong problem-solving skills and passion for tackling complex, open-ended research problems. Preferred Qualifications: - Experience in recommendation systems, especially in live commerce, e-commerce, search, ads, or other large-scale consumer products. - Experience with generative recommendation, large recommendation models, retrieval and ranking systems, or related recommendation architecture upgrades. - Experience with LLMs or multimodal foundation models, including pre-training, post-training, representation learning, contrastive learning, SFT, or RL-based optimization. - Experience in cross-domain transfer learning, LTV modeling, long-term value optimization, causal inference, or debiasing. - Experience with long-sequence user behavior modeling, multi-task learning, multi-interest modeling, or large-scale distributed training and inference optimization. - Publications in top-tier conferences such as NeurIPS, ICML, ICLR, KDD, ACL, CVPR, SIGIR, or RecSys, or strong achievements in major technical competitions. - Strong curiosity about new technologies, fast learning ability, and a passion for solving challenging real-world problems.
Job Information
[For Pay Transparency]Compensation Description (Hourly) - Campus Intern
The hourly rate range for this position in the selected city is $57- $57.
Benefits may vary depending on the nature of employment and the country work location. Interns have day one access to health insurance, life insurance, wellbeing benefits and more. Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year). Interns who are not working 100% remote may also be eligible for housing allowance.
The Company reserves the right to modify or change these benefits programs at any time, with or without notice.
For Los Angeles County (unincorporated) Candidates:
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:
1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
3. Exercising sound judgment.
About TikTok
TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.
Why Join Us
Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect - and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.
We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.
Diversity & Inclusion
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.
TikTok Accommodation
TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at

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