Software Engineer, ML Infrastructure, Level 4

Strong programming skills in Python, Java

Strong problem-solving skills with a focus on system performance, scalability, and efficiency

Good understanding of distributed systems and the infrastructure components of large-scale ML

Experience with big data processing frameworks such as Spark, Flink, or Ray

Ability to collaborate and work well with others

Proven track record of operating highly-available systems at significant scale

Ability to proactively learn new concepts and apply them at work

Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of engineering trends and modern development practices

Bachelor’s degree in a technical field such as computer science or equivalent experience

2+ years of post-Bachelor’s software development experience; or Master’s degree in a technical field + 1+ year of post-grad software development experience; or PhD in a relevant technical field

Experience building large scale production machine learning systems, distributed systems or big data processing

Masters/PhD in a technical field such as computer science or equivalent industry experience

Experience working with ML Training platforms or optimizing AI model inference

Familiarity with ML frameworks such as TensorFlow, PyTorch, Caffe2, Spark ML, scikit-learn, or related frameworks

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In the United States, work locations are assigned a pay zone which determines the salary range for the position.

The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions.

The starting pay may be negotiable within the salary range for the position.

These pay zones may be modified in the future.