Machine Learning Platform Engineer, Applied Machine Learning Team

Responsibilities

• Design, develop, and maintain core functions of the machine learning platform, including data processing, feature engineering, model training, model insights, and model deployment.
• Build efficient, scalable data processing and computing processes to ensure platform stability and performance.
• Collaborate with data scientists and machine learning engineers to understand their requirements and provide tool and technical support.
• Work closely with system administrators and software engineers to ensure smooth platform integration with other systems.
• Manage and monitor the operation of the machine learning platform, troubleshooting any platform-related issues.
• Continuously track and evaluate emerging technologies and tools and provide suggestions for platform improvements and development.

• A bachelor’s or higher degree in computer science, software engineering, or a related field.
• At least three years of experience in software engineering, proficient in Python and Golang.
• In‑depth understanding of distributed computing and large‑scale data processing, familiar with open‑source tools such as Hadoop, Spark, etc.
• Strong communication and teamwork skills, capable of collaborating with cross‑functional teams.
• Enthusiastic learner, passionate about engineering challenges and solving complex problems.
• Strong analytical and problem‑solving skills, able to quickly understand and resolve engineering problems.

• Annual base salary range of $156,000 – $387,600, with potential for additional bonuses and incentives.
• Health, dental, and vision insurance with day‑one coverage.
• 401(k) savings plan with company match.
• Paid parental leave, short‑term and long‑term disability coverage, and life insurance.
• Well‑being benefits, 10 paid holidays, 10 paid sick days, and 17 days of paid personal time.

Byte Dance is an equal‑opportunity employer committed to providing reasonable accommodations for candidates with disabilities, pregnancy, or sincerely held religious beliefs.