Machine Learning Engineer, E-commerce Feed Recommendation San Jose Technology - Algorithm Regular

TikTok; San Jose, Northern (CA, KY); Hybrid; USD 162,000 - 317,000; Full time

Job summary

TikTok is hiring a Machine Learning Engineer for the E-commerce Feed Recommendation team in San Jose. You will develop large-scale recommendation algorithms for live-streaming and short video commerce, focusing on user interest modeling and ranking.

You will build and optimize models (CTR/ CVR) and real-time data pipelines, collaborate with cross-functional teams, and contribute to the deployment and monitoring of production systems. This role offers strong growth in a fast-moving tech company.

Qualifications

• Must have Bachelor's degree in CS or related field.
• 1 year of applied ML experience.
• Experience with DL frameworks such as TensorFlow or PyTorch.
• Proficiency in C++ or Python.

Responsibilities

• Build large-scale ML models for e-commerce recommendations (live-streaming & short videos).
• Develop data pipelines and feature engineering for candidate generation and ranking.
• Experiment, evaluate, and iterate on models to improve engagement and conversion.
• Create tools to support debugging and model monitoring.

Skills

Programming ability

Problem-solving

Applied ML

Education

Bachelor's degree in Computer Science or related field

Tools

TensorFlow

PyTorch

Job description

Machine Learning Engineer, E-commerce Feed Recommendation

Location:

San Jose

Employment Type:

Regular

Job Code:

A142260

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Responsibilities

About the teamInterest-based E-commerce is a new and fast growing business that aims at connecting all customers' interests to excellent sellers and high quality products on TikTok Shop. Different from other traditional E-commerce platforms, TikTok Shop provides customers with personalized and unique shopping experience through E-commerce live-streaming and E-commerce short videos. The recommendation system plays an extremely important role in helping customers explore their shopping interests.We are a group of applied machine learning engineers and research scientists that focus on E-commerce video/live-streaming recommendations on the major traffic source of TikTok ForU page, where we serve traffic for billions of users every single day. We develop innovative algorithms and ML techniques to improve user engagement and satisfaction, converting creative ideas into business-impacting solutions. We are interested and excited about applying large scale machine learning to solve various real-world problems in E-commerce and recommendation.

• Participate in building large-scale (10 million to 100 million) live-streaming and short video e-commerce recommendation algorithms and systems on TikTok.


• Design, develop, evaluate and iterate on predictive models for candidate generation and ranking(eg. Click Through Rate and Conversion Rate prediction) , including, but not limited to building real-time data pipelines, feature engineering, model optimization and innovation.


• Build long and short term user interest models, analyze and extract relevant information from large amounts of various data and design algorithms to explore users' latent interests efficiently.


• Design and develop various strategies using ML technology to improve user shopping experience, and resolve e-commerce business challenges, such as the cold start problem and traffic allocation.


• Design and build supporting/debugging tools as needed.

Qualifications

• Minimum Qualifications- Bachelor's degree or higher in Computer Science or related fields.


• Strong programming and problem-solving ability.


• 1 year of experience in applied machine learning, familiar with one or more of the algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, Wide and Deep etc.


• Experience in Deep Learning Tools such as tensorflow/pytorch.


• Experience with at least one programming language like C++/Python or equivalent.


• Preferred Qualifications- 2 years of experience in recommendation system, online advertising, information retrieval, natural language processing, machine learning, large-scale data mining, or related fields.


• Publications at KDD, NeurlPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RECSYS and related conferences/journals, or experience in data mining/machine learning competitions such as Kaggle/KDD-cup etc.

Job Information

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;


• 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 https://tinyurl.com/RA-request

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