Technical Lead, Machine Learning Engineering (Multiple Positions)

About the role

Our team plays a crucial role in ensuring the company's success. We seek people who are willing to learn and put in the effort to solve problems. Our challenges are not your regular day-to-day problems - you'll be part of a team that's developing new solutions to new challenges. It's working fast, at scale, and we're making a difference. We are looking for talents to join us on this exciting journey!

Responsibilities

• 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.
• Analyze user behavior and apply machine learning (ML) algorithms to optimize content consumption and production experience by understanding product objectives and ML techniques to improve model and recommendation strategy.
• Design and apply ML algorithm and recommendation strategies to improve users' experience on platform and content, including videos and livestreams.
• Build industry-leading recommendation system, and develop highly scalable classifiers and tools leveraging ML.
• Build full-stack search engine system and combine information retrieval technology with modern ML methods from related fields such as natural language processing (NLP), Computer Vision (CV), and recommender system.
• Work on highly scalable classifiers, predictive models and algorithms in big data mining, CV, NLP, and other domains.
• Work with engineering teams to implement model pipeline and deploy services at scale.
• Conduct offline and online experiments, analyze data accordingly and evaluate to improve algorithms and strategies.
• Work with Data Engineers, Data Analysts, Product and other engineers to deliver features to drive the user growth of products.
• Build the core systems and algorithms development including query understanding, result ranking, query recommendation, and system reliability.
• Partner with product managers and product strategy and operation team to define product strategy and features.
• Collaborate with strategy team, product managers, policy team and other key stakeholders to define products and drive initiatives from engineering viewpoint.
• Work with large, complex data sets to solve difficult, non-routine analysis problems by applying advanced analytical methods as needed.

Requirements

• Of the required experience, must have 4 years of experience in each of the following:
• Coding using Python or C++;
• Developing and deploying large-scale machine learning systems;
• Developing data-driven prediction models using classic statistical methods, machine learning, and neural network/deep learning;
• Optimizing, training, and deploying machine learning and deep learning models using PyTorch or TensorFlow;
• Researching, testing and productionizing state-of-the-art deep learning models and methods; and
• Utilizing Hive, Spark, Hadoop, or Flink.
• Type: Full time, 40 hours/week
• Location: San Jose, CA
• Salary Range: $275850 - $450000 per year
• To Apply, click the apply button below. Contact lpresumes@tiktok.com if you have difficulty submitting resume through the website.

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