Software Engineer L4/L5, Model Serving Systems, Machine Learning Platform

This job was posted over 30 days ago, so it has most likely closed. See newer jobs like it.

Written by AI from the job title and company, not by Netflix, so some details may not match this job. The employer's own page has the real description.

Job Overview

As a Software Engineer L4/L5 in the Model Serving Systems team of the Machine Learning Platform at Netflix, you will play a critical role in developing and optimizing scalable systems that deliver machine learning models efficiently. Your expertise will contribute to enhancing user experience by ensuring that our advanced algorithms and models are deployed seamlessly in real-time. You will collaborate with cross-functional teams to shape design strategies, maximize performance, and support continuous improvement initiatives in the delivery of machine learning services.

Job Responsibilities

• Design, implement, and maintain scalable model serving systems that facilitate real-time decision-making.
• Collaborate with data scientists and researchers to integrate machine learning models into production-ready services.
• Monitor and optimize system performance, ensuring high availability and low-latency responses.
• Conduct troubleshooting and debugging to diagnose issues affecting model performance and reliability.
• Implement best practices for software development, including testing and code reviews.
• Stay up to date with advancements in machine learning and software engineering practices to enhance the current systems.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in software engineering with a focus on system design and implementation.
• Strong proficiency in programming languages such as Python, Java, or C++.
• Experience with machine learning frameworks like TensorFlow, PyTorch, or similar.
• Knowledge of cloud platforms (e.g., AWS, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes).
• Excellent problem-solving skills and the ability to work in a fast-paced environment.

Technologies & Tools

The ideal candidate will be familiar with a range of technologies and tools, including but not limited to cloud-based services (AWS, GCP), Docker and Kubernetes for container orchestration, as well as popular machine learning frameworks such as TensorFlow and PyTorch. Proficiency in version control systems like Git and experience with CI/CD pipelines are also crucial for maintaining efficient deployment workflows.

Ideal Candidates

Ideal candidates possess a strong foundation in both software engineering principles and machine learning practices. They are proactive problem solvers with a passion for leveraging data to drive impactful results. A collaborative mindset is essential, as the role requires working closely with diverse teams. Candidates should demonstrate a strong commitment to writing clean, maintainable code and have a keen interest in continuous learning and adaptation to evolving technologies.