Research Engineer, Machine Learning - Privacy

$145,000 - $250,000/Yr

Tiktok - San Jose, CA

Full-time - Entry Level

San Jose, CA

Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

About the position

TikTok is the leading destination for short-form mobile video, and our mission is to inspire creativity and bring joy. As part of this mission, we prioritize privacy in our product design and implementation. The Privacy Innovation (PI) Lab at TikTok is dedicated to exploring the next frontier of privacy technology and theory in the digitalized world. We provide key insights and technical solutions on privacy-related innovation for all TikTok products, collaborating with global technical and academic communities to promote a privacy-friendly digital experience. As a Research Engineer in Machine Learning focused on Privacy, you will be part of a rapidly growing team that tackles critical industrial challenges related to privacy innovation. You will have the opportunity to research advanced privacy technologies and theories alongside influential researchers worldwide, applying cutting-edge technology to serve billions of TikTok users. Your role will involve constructing a multi-party joint modeling and data analysis platform, working closely with product teams to understand privacy requirements, and converting research outcomes into technical solutions and product prototypes. Additionally, you will engage with the community by building open-source tools and infrastructure for privacy-related research and participating in external events such as meetups and hackathons.

Responsibilities

• Participate in the construction of a multi-party joint modeling and data analysis platform
• Work with product teams to understand key privacy requirements from TikTok product family and convert research outcomes into technical solutions and product prototypes
• Collaborate with research teams for complex experiments requiring optimized algorithms running on large datasets or sophisticated data processing
• Build open-source tools and infrastructure for privacy-related research and engage with community contributors in external events including meetups, hackathons, and summits.

Requirements

• PhD or Master's degree in Computer Science or a related field
• Familiarity with federated learning / distributed machine learning algorithms and experience in federated learning frameworks and applications development
• Familiarity with machine learning and deep learning frameworks, such as TensorFlow, Pytorch, JAX
• Proficiency in at least one of the following programming languages: Go, C++, Python, Rust, Java
• Ability to work globally and collaboratively within a team.

Nice-to-haves

• Experience in privacy-enhanced techniques (PET) and related technical domains, including data and identity anonymization, differential privacy, secure multi-party computation, federated machine learning, on-device machine learning, interpretable AI, privacy-preserving technology for large language models (LLM) or foundation models, privacy-preserving regulation technology.

Benefits

• 100% premium coverage for employee medical insurance
• Approximately 75% premium coverage for dependents
• Health Savings Account (HSA) with company match
• Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life and AD&D insurance plans
• Flexible Spending Account (FSA) Options like Health Care, Limited Purpose and Dependent Care
• 10 paid holidays per year
• 17 days of Paid Personal Time Off (PPTO)
• 10 paid sick days per year
• 12 weeks of paid Parental leave
• 8 weeks of paid Supplemental Disability
• Mental and emotional health benefits through EAP and Lyra
• 401K company match
• Gym and cellphone service reimbursements