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Machine Learning Engineer (Recommendation) - TikTok e-Commerce Job Opening In Singapore, Singapore – Now Hiring TIKTOK PTE. LTD.

Machine Learning Engineer (Recommendation) TikTok e Commerce

    Singapore Jobs Expertini Expertini Singapore Jobs Other General Machine Learning Engineer (Recommendation) Tiktok E Commerce

Job description

TikTok will be prioritizing applicants who have a current right to work in Singapore, and do not require TikTok's sponsorship of a visa.


TikTok is the leading destination for short-form mobile video.

Our mission is to inspire creativity and bring joy.

TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Singapore, Jakarta, Seoul and Tokyo.


Why Join Us
Creation is the core of TikTok's purpose.

Our platform is built to help imaginations thrive.

This is doubly true of the teams that make TikTok possible.


Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day.


To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team.

Status quo?

Never.

Courage?

Always.


At TikTok, we create together and grow together.

That's how we drive impact - for ourselves, our company, and the communities we serve.


Join us.


About the team
Our team works on large-scale recommendation systems for various offerings under TikTok and its affiliates, focusing on developing recommendation algorithms/models/strategies.

We are committed to developing cutting-edge solutions for e-commerce recommendation systems.


Responsibilities
Work on recommendation systems, involving contents of various forms ranging from products, short videos to live streams, with each unified recommendation model fulfilling heterogeneous E-commerce scenarios/goals across multiple countries.


Optimize e-commerce recommendation models at massive scales, using deep learning/transfer learning/multi-task learning techniques.


Data mining and analysis to improve the quality of recommended contents.


Conduct research on various topics, which aim to optimize content recommendation circulation, ranging from ensuring diversity and new discovery in recommendation contents, to cold-start problem for new users/items and discovery of high-quality products/live streamers.


Develop innovative and state-of-the-art e-commerce models and algorithms.


Support the production of scalable and optimised AI/machine learning (ML) models.


Focus on building algorithms for the extraction, transformation and loading of large volumes of realtime, unstructured data to deploy AI/ML solutions from theoretical data science models.


Run experiments to test the performance of deployed models, and identify and resolve bugs that arise in the process.


Work in a team setting and apply knowledge in statistics, scripting and programming languages required by the firm.


Work with the relevant software platforms in which the models are deployed.


Qualifications
Strong in data structures and algorithms, with excellent problem-solving ability and programming skills.


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 etc.


Experience in working with main components of recommendation systems(recall, sort, reranking, cold-start problem), with good understanding of mainstream recommendation models used in the industry.


Experience in C++ and Python; at least one of the Big Data tools (For eg.

Hive sql/Spark/Mapreduce; at least one of the Deep Learning tools(For eg.

Tensorflow/Pytorch).


Possess strong communication skills, positive mindset, good teamwork skills, and eagerness to learn/implement new technology and experiment.


Preferred Qualifications
Experience in personalized recommendation, online advertising, information retrieval or related fields.


Publications at KDD、NeurIPS、 and related conferences.


Excellent performance in data mining, machine learning, or ACM-ICPC/NOI/IOI competitions.


Developed widely-recognized machine learning project(s) on github or personal webpage.


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.


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The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at TIKTOK PTE. LTD. adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

1. Independence

2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying Singapore laws and regulations

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The average salary range for a varies, but the pay scale is rated "Standard" in Singapore. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

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TIKTOK PTE. LTD. interview tips for Machine Learning Engineer (Recommendation)   TikTok e Commerce

Here are some tips to help you prepare for and ace your Machine Learning Engineer (Recommendation) TikTok e Commerce job interview:

Before the Interview:

Research: Learn about the TIKTOK PTE. LTD.'s mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

Follow Up: Send a thank-you email to the interviewer within 24 hours.

Additional Tips:

Be Yourself: Let your personality shine through while maintaining professionalism.

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Be Positive: Focus on your strengths and accomplishments.

Body Language: Maintain good posture, avoid fidgeting, and make eye contact.

Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your Machine Learning Engineer (Recommendation) TikTok e Commerce interview at TIKTOK PTE. LTD., research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the TIKTOK PTE. LTD.'s products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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