Applied Machine Learning Production Engineer Graduate (AML-Production Engineer) - 2027 Start

About Us

Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, Lemon8, CapCut, and Pico, as well as platforms specific to the China market, such as Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content.

Our innovative products are built to help people authentically express themselves, discover, and connect. Together, we create value for our communities, inspire creativity, and enrich life. As ByteDancers, we strive to do great things with great people, leading with curiosity, humility, and a desire to make an impact in a rapidly growing tech company.

About the Role

The production engineering team for the Applied Machine Learning (AML) organization is at the heart of what we do. We are a global team of engineers who blend deep systems knowledge with software engineering to build and run the large-scale, distributed systems that power our machine learning products. Our mission is to ensure that ByteDance's core machine learning services are reliable, scalable, and efficient.

As a production engineer intern, you will be immersed in a fast-paced, high-impact environment. You will have the opportunity to work on real-world challenges, receive mentorship from experienced engineers, and contribute to systems that serve millions of users worldwide. This is a unique chance to develop your skills in coding, performance analysis, and large-scale system operations.

Responsibilities

• Assisting in the design and development of software and tools to enhance system automation, monitoring, and operational efficiency.
• Participating in troubleshooting and resolving system issues, analyzing root causes, and implementing preventative measures.
• Contributing to the enhancement of existing software by updating capabilities and supporting testing and validation procedures.
• Collaborating with software and hardware engineers to understand system requirements and contribute to performance improvements.
• Learning and applying principles of computer science, engineering, and mathematical analysis to solve real-world problems.

Qualifications

Minimum Qualifications

• Individuals who are completing or have recently completed a Bachelor's/Master's degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
• Solid understanding of fundamental data structures and algorithms.
• Foundational programming experience in at least one language, such as Python, C++, or Go.
• A keen interest in troubleshooting and analyzing distributed systems.
• Strong problem-solving skills and the ability to learn quickly.

Preferred Qualifications

• Previous internship experience in a related field is a plus, but not required.
• Familiarity with Linux/Unix operating systems.
• Basic understanding of networking concepts (e.g., TCP/IP, HTTP).
• Exposure to containerization technologies like Docker and Kubernetes.
• Experience with Machine Learning frameworks like TensorFlow or PyTorch is a bonus.

Pay

The base salary range for this position in the selected city is $128,000 - $256,000 annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies, 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

• Day one access to medical, dental, and vision insurance.
• 401(k) savings plan with company match.
• Paid parental leave.
• Short-term and long-term disability coverage.
• Life insurance.
• Wellbeing benefits.
• 10 paid holidays per year.
• 10 paid sick days per year.
• 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.