Backend Engineer - Applied Machine Learning Engine (Efficiency Tool)

10 Hours ago • 3 Years +

Job Summary

Job Description

As a Backend Engineer, you will be responsible for researching, designing, and developing computer and network software and specialized utility programs. You will analyze user needs and develop software solutions using principles of computer science, engineering, and mathematical analysis. Your role also involves updating software, enhancing capabilities, and directing testing and validation procedures. Furthermore, you will work with hardware engineers to integrate systems and define specifications. The role involves working on the Applied Machine Learning (AML) team, which focuses on massively distributed recommendation systems. The candidate will be working on DevOps, ensuring machine learning services at TikTok have the highest level of availability, as well as creating highly automated systems and pipelines.
Must have:
  • Bachelor’s degree in Computer Science or equivalent with 3+ years of experience
  • Experience analyzing and troubleshooting distributed systems
  • Experience designing and maintaining large-scale systems
  • Programming experience in Python or Golang
  • Expertise in DevOps technologies (Ansible, Terraform, etc.)
  • Experience with cloud services (AWS, GCP, etc.)
  • Familiarity with Unix/Linux operating systems
Good to have:
  • Ability to thrive in a fast-paced environment
  • Understanding of code optimization and automation
  • Proficiency in machine learning frameworks (TensorFlow, PyTorch, etc.)
  • Solid background in algorithms and data structures

Job Details

Responsibilities
ByteDance will be prioritizing applicants who have a current right to work in Singapore, and do not require ByteDance's sponsorship of a visa. About ByteDance Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content. Why Join Us Creation is the core of ByteDance's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. To us, every challenge, no matter how ambiguous, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At ByteDance, we create together and grow together. That's how we drive impact - for ourselves, our company, and the users we serve. Join us. About The Team The Applied Machine Learning (AML) team combines system engineering and the art of machine learning to develop and run massively distributed recommendation system around the world. On the team, you'll have the opportunity to sharpen your expertise in coding, performance analysis and large system operation, and get heavily involved in the process of hardware/capacity decision-making. DevOps ensures that the very centric machine learning services at TikTok have the highest level of availability, as well as creating highly automated systems and pipelines. Responsibilities - Research, design, and develop computer and network software or specialised utility programs. - Analyse user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis. - Update software, enhances existing software capabilities, and develops and direct software testing and validation procedures. - Work with computer hardware engineers to integrate hardware and software systems and develop specifications and performance requirements. - Research, design, and develop computer and network software or specialised utility programs. - Analyse user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis. - Update software, enhances existing software capabilities, and develops and direct software testing and validation procedures. - Work with computer hardware engineers to integrate hardware and software systems and develop specifications and performance requirements.
Qualifications
Minimum Qualifications - Bachelor’s degree in Computer Science or equivalent with 3+ years of relevant experience - Proven experience in analyzing and troubleshooting distributed systems. - Prior experience designing and maintaining large-scale systems. - Experience programming in at least one of the following languages: Python or Golang. - Expertise in DevOps technologies like Ansible, Terraform, Salt, Bash Scripting, etc. - Experience in building solutions with AWS, GCP, Azures, AliCloud or other cloud services. - Familiar with Unix/Linux operating systems. Preferred Qualifications - Ability to thrive in a fast-paced environment. - Strong understanding of code optimizing and routine tasks automation. - Proficiency in at least one machine learning framework: TensorFlow, PyTorch, MXNet or PaddlePaddle. - Solid background of algorithms and data structures. ByteDance 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 ByteDance, our mission is to inspire creativity and enrich life. 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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About The Company

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

Tokyo, Japan (On-Site)

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San Jose, California, United States (On-Site)

San Jose, California, United States (On-Site)

San Jose, California, United States (On-Site)

San Jose, California, United States (On-Site)

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