# Machine Learning Engineer Graduate (E-Commerce Recommendation Foundation)- 2027 Start (PhD)

Source: https://realanalystjobs.com/job/machine-learning-engineer-graduate-e-commerce-recommendation-foundation-2027-sta-3bdd1802
Machine Learning Engineer Graduate (E-Commerce Recommendation Foundation)- 2027 Start (PhD) at TikTok, an on-site role based in Seattle, Washington, USA. First seen on RealAnalystJobs on 15 November 2026, read from TikTok's own careers page (TikTok), which RealAnalystJobs re-checks daily and removes the role when it closes. TikTok has approved H-1B petitions on USCIS record (employer-wide, not a promise for this role).

Updated 15 November 2026.

## Key facts

- Company: [TikTok](https://realanalystjobs.com/companies/tiktok)
- Location: Seattle, Washington, USA
- Work mode: On-site
- First seen: Nov 15, 2026
- Employment type: Full time
- Source: TikTok's careers page (TikTok), re-checked daily

Skills: [Python](https://realanalystjobs.com/skills/python)

## Visa sponsorship

The posting does not say.

TikTok had H-1B petitions approved for 454 workers in fiscal year 2026 (USCIS). That is history, not a promise for this role. [See the record](https://realanalystjobs.com/companies/tiktok#h1b-record)

## About this role

The Recommendation Foundation team within TikTok’s Data - Global E-commerce organization is dedicated to building shared Recommendation Foundation Models across scenarios. We are exploring an event-sequence-driven generative recommendation paradigm that deeply integrates large language and vision-language models (LLMs/VLMs), multimodal understanding, reinforcement learning, and system optimization, advancing recommendation systems beyond click prediction toward general-purpose recommendation agents.

We believe the future of recommendation is not only about predicting clicks, but about understanding the relationships between people and content and generating new connections. We value original exploration and encourage research thinking and engineering practice equally. Every team member can propose hypotheses and validate ideas in an open environment; your code and publications may help shape the next generation of recommendation systems. We are looking for people with a general-intelligence mindset to redefine recommendation with us.

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.

Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.

Responsibilities:
1. Participate in the full training lifecycle of Recommendation Foundation Models, including pre-training, mid-training, and post-training.
2. Design and train multimodal semantic tokenizers for recommendation items, leveraging multimodal foundation models to encode rich item content into discrete semantic tokens and raise the performance ceiling of Recommendation Foundation Models.
3. Develop LLM-native recommendation by incorporating recommendation tasks directly into large language model training and leveraging world knowledge to improve recommendation quality.
4. Build the next generation of recommendation systems powered by Recommendation Foundation Models, spanning retrieval, ranking, and end-to-end generative recommendation.

Qualifications
Minimum Qualifications:
- Individuals who are completing or have recently completed a PhD degree in Computer Science, Electrical Engineering, Mathematics, Statistics or a related discipline.
- Solid foundation in machine learning and deep learning, with strong interest in LLMs and generative recommendation.
- Proficiency in Python and experience with deep learning frameworks such as PyTorch.
- Self-driven, with a strong research mindset and solid engineering skills.

Preferred Requirement:
- Experience with pre-training, mid-training, or post-training of LLMs or Foundation Models.
- Research or project experience in generative recommendation, LLM-native recommendation, or multimodal semantic tokenization.
- Publications on LLM-related topics at top-tier machine learning or natural language processing conferences, such as NeurIPS, ICML, ICLR, ACL, EMNLP, or NAACL, or strong achievements in major technical competitions.

Description from TikTok's public careers feed, reproduced so you can read the role here. Apply on the company's own site; Real Analyst Jobs never submits anything for you.

## How to apply

Open [this role on Real Analyst Jobs](https://realanalystjobs.com/job/machine-learning-engineer-graduate-e-commerce-recommendation-foundation-2027-sta-3bdd1802) and use Apply now there to reach the employer's application. The listing is re-checked against TikTok's careers page daily and removed when it closes.

## TikTok

101 open analyst roles on Real Analyst Jobs. [More roles at TikTok](https://realanalystjobs.com/companies/tiktok)

## More like this

### Other open roles at TikTok

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- [Global Quality Operations AI Solutions Specialist](https://realanalystjobs.com/job/global-quality-operations-ai-solutions-specialist-tiktok-b968d27f), Singapore
- [Monetization Strategy & Operations Manager - GBS](https://realanalystjobs.com/job/monetization-strategy-and-operations-manager-gbs-tiktok-d9b1af11), Buenos Aires, Argentina
- [Risk Analyst](https://realanalystjobs.com/job/risk-analyst-tiktok-900d7b2d), San Jose California, USA (On-site)

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## Sources and links

- [This role on Real Analyst Jobs](https://realanalystjobs.com/job/machine-learning-engineer-graduate-e-commerce-recommendation-foundation-2027-sta-3bdd1802)
- [TikTok on Real Analyst Jobs](https://realanalystjobs.com/companies/tiktok)
- [All analyst jobs](https://realanalystjobs.com/jobs)
