Senior Machine Learning Engineer, E-commerce Recommendation Foundation - USDS

Responsibilities

The E‑commerce Recommendation Foundation team is dedicated to building the next‑generation recommendation intelligence. We aim to develop a unified Foundation Model that supports multi‑business and multi‑scenario recommendation systems, covering the full pipeline from retrieval and ranking to re‑ranking, and driving a comprehensive upgrade in intelligence and generative capability. The team explores an event‑sequence‑driven generative recommendation paradigm, deeply integrating large language models (LLMs), multimodal understanding, reinforcement learning, and system optimization to advance recommendation systems toward general‑purpose intelligent agents. We value original exploration, encourage both research thinking and engineering excellence, and empower every team member to propose hypotheses and validate ideas.

• Build and optimize cross‑scenario shared Foundation Models to enable unified modeling and efficient inference. Advance the event‑sequence‑driven generative recommendation paradigm, integrating multimodal understanding and generative capabilities.
• Apply LLM technologies across retrieval, ranking, and re‑ranking stages; participate in model training, inference optimization, and system co‑design.
• Explore integration of LLMs / VLMs with recommendation systems to develop adaptive and evolving intelligent recommenders.
• Research end‑to‑end generative recommendation and system optimization methods that balance efficiency and user experience.

Qualifications

Minimum Qualifications

• Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field.
• 3+ years of experience in machine learning, deep learning, or information retrieval.
• Proficiency in Python and familiarity with mainstream deep learning frameworks (e.g., PyTorch).
• Strong passion for intelligent recommendation systems and a self‑driven research mindset.

Preferred Qualifications

• PhD degree in Computer Science, Machine Learning, or a related field.
• Experience in large‑scale recommendation system development or large‑model training, with notable technical achievements in a sub‑area.
• Research experience or publications in LLMs, multimodal learning, reinforcement learning, or generative recommendation.
• Familiarity with pre‑training and post‑training processes for large language models (LLMs) or Foundation Models.

About USDS

TikTok USDS Joint Venture LLC is dedicated to the safety and security of millions of Americans who create, discover, and connect on the apps we operate. Established in compliance with the Executive Order signed on September 25, 2025, the joint venture runs a comprehensive data‑privacy and cybersecurity program to protect national security and secure U.S. user data, apps, and algorithms. We safeguard the U.S. content ecosystem, hold decision‑making authority for trust and safety policies and moderation, and enable Americans to express creativity, discover new interests, and build thriving communities and businesses at global scale. The company is shifting from a hybrid work model to a fully in‑person schedule (up to five days a week) to enhance speed, alignment, and agility.

Why Join Us

Inspiring creativity is at the core of TikTok's mission. Our innovative product helps people authentically express themselves, discover, and connect. Global, diverse teams make that possible, creating value for communities, inspiring creativity, and bringing joy. 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. By fostering an “Always Day 1” mindset, we achieve meaningful breakthroughs for ourselves, the company, and our users.

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 worldwide, and our workplace reflects that diversity. We celebrate diverse voices and strive to build an environment that mirrors the many communities we serve.

Pay

The base salary range for this position in the selected city is $198,360 – $416,100 annually. Compensation may vary outside of this range based on qualifications, skills, competencies, experience, and location. Base pay is part of a total package that may include discretionary bonuses/incentives and restricted stock units. Employees receive day‑one access to medical, dental, and vision insurance, a 401(k) plan with company match, paid parental leave, short‑ and long‑term disability coverage, life insurance, wellbeing benefits, 10 paid holidays, 10 paid sick days, and 17 days of paid personal time (prorated upon hire with increasing accruals by tenure). Benefits may vary by employment nature and country location.

Schedule

The role requires on‑site presence, with the company moving to a fully in‑person schedule of up to five days per week.