Research Scientist Graduate (Global E-commerce Content Recommendation) - 2026 Start (PhD) San J[...]

Ellis Technologies, Inc.; San Jose (CA); On-site; USD 156,000 - 387,600; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) savings plan with company match

Paid parental leave

Paid holidays and personal time

Job summary

Ellis Technologies, Inc. is seeking a Research Scientist Graduate for their Global E-commerce Content Recommendation team, starting in 2026. The position is based in San Jose and focuses on designing algorithms leveraging LLMs for content recommendations and summarization.

Qualified candidates will hold a PhD in a relevant field and possess experience with LLMs and deep learning frameworks. The role offers a competitive salary range of $156,000–$387,600 annually, and includes a comprehensive benefits package.

Qualifications

• Individuals who are completing or have recently completed a PhD degree in a related field.
• Experience with LLMs through research or practical application.
• Demonstrated ability to conduct rigorous research and analyze large-scale data.

Responsibilities

• Design algorithms and systems for content-to-commerce matching.
• Contribute to research via papers, patents, or publications.
• Explore novel architectures for generative recommendation systems.

Skills

Experience with LLMs (e.g., GPT, LLaMA, PaLM)

Proficient coding skills in Python

Strong problem-solving skills

Education

PhD in Computer Science, Machine Learning, or related field

Tools

TensorFlow

PyTorch

Job description

Research Scientist Graduate (Global E-commerce Content Recommendation) - 2026 Start (PhD)

Location: San Jose

Employment Type: Regular

Job Code: A176558

Responsibilities

• Design algorithms and systems that leverage LLMs and generative models for content‑to‑commerce matching, product summarization, etc.
• Explore novel architectures and strategies for generative recommendation systems.
• Contribute to the research community via internal papers, patents, or external publications.
• Drive scientific rigor while balancing real‑world constraints.

Qualifications

Minimum Qualifications

• Individuals who are completing or have recently completed a PhD degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related technical field.
• Experience with LLMs (e.g., GPT, LLaMA, PaLM) or diffusion/generative models, through research or practical application.
• Proficient coding skills in Python and hands‑on experience with deep learning frameworks such as TensorFlow or PyTorch.
• Demonstrated ability to conduct rigorous research and analyze large‑scale data.
• Strong problem‑solving skills and a high sense of ownership.

Preferred Qualifications

• Publications in ML/AI conferences (e.g., NeurIPS, ICML, ACL, SIGIR, KDD, CVPR, RecSys).
• Experience with recommendation systems, retrieval models, or multi‑modal learning.
• Familiarity with building and deploying real‑time, scalable ML systems in production.
• Background in e‑commerce or related applied AI research domains.

Job Information

The base salary range for this position in the selected city is $156,000–$387,600 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day‑one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short‑term and long‑term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

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:

• Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
• Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems;
• Exercising sound judgment.

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