General Hire) Machine Learning Scientist Graduate

Tiktok Inc
San Jose, CA, United States
1 day ago
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Role details

Contract type
Internship / Graduate position
Employment type
Full-time (> 32 hours)
Experience level
Starter
Experience required
3 years minimum
Compensation
$162,000.0 - $316,800.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence Algorithm Design Artificial Neural Networks C++ (Programming Language) Computer Engineering Data Structures Python (Programming Language) Unix Shell Machine Learning Recommender Systems Tensorflow Software Engineering
+3 more
Pytorch Deep Learning Information Technology

Job description

Recommendation algorithm team plays a central role in the company, driving critical product decisions and platform growth. The team is made up of machine learning researchers and engineers, who support and innovate on production recommendation models and drive product impact. The team is fast-pacing, collaborative and impact-driven., 1. Build industry-leading recommendation system, improving user experience, content ecosystem and platform security;

  1. Deliver end-to-end machine learning solution to address critical product challenges;
  2. Own the full stack machine learning system and optimize algorithms and infrastructure to improve recommendation performance.
  3. Work with cross functional teams to design product strategies and build solutions to grow TikTok in important markets.

Requirements

  1. Individuals who are completing or have recently completed a PhD degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
  2. Good knowledge of theoretical and empirical research in addressing research problems
  3. Solid knowledge and experience with at least one popular deep learning framework (e.g., PyTorch,TensorFlow) and familiarity with deep neural network architectures

Preferred Qualifications:

  1. Research experience in one or more of the following fields: applied machine learning, machine learning infrastructure, large-scale recommendation system, market-facing machine learning product.
  2. Strong first-author publications record in major AI conferences or journals(e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL etc.)
  3. Proficient in C/C++, Python, and shell programming languages, and have a deep understanding of data structure and algorithm design.
  4. Internship experience in an AI research organization

Benefits & conditions

The base salary range for this position in the selected city is $162000 - $316800 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:

  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.

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