Software Engineer (L4), Consumer ML Model Compute & Serving Systems

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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.

Overview

The Software Engineer (L4) for Consumer ML Model Compute & Serving Systems at Netflix will play a pivotal role in designing, developing, and maintaining scalable machine learning systems that cater to consumer applications. This position involves collaborating with cross-functional teams to implement advanced machine learning models, ensuring their efficient serving and compute capabilities. The ideal candidate will leverage their technical expertise to optimize processes, drive architectural improvements, and enhance user experiences through innovative software solutions.

Job Responsibilities

• Design, implement, and optimize machine learning pipelines and serving systems for consumer applications.
• Collaborate with data scientists to deploy robust and scalable machine learning models in production.
• Ensure high availability and performance of machine learning services, monitoring system health and performance metrics.
• Conduct code reviews and provide mentoring to junior engineers and team members on best practices.
• Participate in system architecture discussions and contribute to engineering roadmaps.
• Utilize big data processing frameworks to analyze and improve existing models and systems.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in software development, with a focus on machine learning and data processing.
• Proficient in programming languages such as Python, Java, or C++.
• Experience with cloud technologies and platforms, particularly AWS, GCP, or Azure.
• Solid understanding of machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Strong problem-solving skills and ability to work on complex technical challenges.

Technologies & Tools

In this position, you will primarily work with cloud services (AWS, GCP), machine learning libraries (TensorFlow, PyTorch), and software engineering tools such as Git, Jenkins, and Docker. Familiarity with big data processing frameworks like Apache Spark and tools for monitoring and logging (e.g., Datadog, Prometheus) will also be beneficial to ensure optimal system performance and reliability.

Ideal Candidates

The ideal candidates for this position will possess a blend of technical expertise and interpersonal skills. They should demonstrate a strong analytical mindset and a passion for solving complex problems. Successful candidates will be collaborative, adaptable, and able to thrive in a fast-paced, innovative environment. A commitment to continuous learning and improvement, coupled with the ability to communicate effectively with both technical and non-technical stakeholders, will ensure success in this dynamic role.