Machine Learning Software Engineer - Promo Media & Marketing

Job Description

Machine Learning Software Engineer (L5) - Promo Media & Marketing

At Netflix, our mission is to connect global stories with audiences worldwide. When a Netflix member opens our app, we have a few precious moments to help them choose a story or a game that is right for them at that instance. Presenting them evidence – Artwork, Trailers, Synopses – that authentically represents each title and resonates with the member is essential to this effort.

Beyond connecting global stories with existing audiences, we also aim to reach new subscribers and increase engagement through innovative marketing campaigns. By crafting compelling and targeted marketing strategies, we strive to capture the attention of potential members and convert their interest into subscriptions. Additionally, we focus on increasing conversation and excitement about Netflix and our content, creating buzz and anticipation that encourages both current and prospective members to explore and engage with our diverse offerings.

Getting this evidence just right for each title is a tall order; however, the Promo Media Algo team, with assistance from creative supervision and member feedback data, have built tools & processes that use technologies like Computer Vision, and Machine Learning to enable our creators to tell the best version of the story they want while allowing our studio to scale further.

Join us to be part of a team that is shaping the future of media and marketing at Netflix. We are seeking an experienced Machine Learning Software Engineer with 5+ years of experience to join our team. You will work closely with our ML scientists to design and develop scalable systems and workflows that enable the efficient development, deployment, and operation of ML/CV algorithms across Netflix's Promo Media and Marketing workflows. This role supports a diverse portfolio of projects - from batch Computer Vision pipelines processing every video package ingested to Netflix, to real-time GenAI systems serving creative workflows - requiring versatility and expertise across different ML deployment paradigms.

Responsibilities:
• Architect and implement robust ML pipelines and reusable frameworks across the full ML lifecycle in the multimedia domain, including data processing, efficient distributed model training with GPUs, and deploying models into creator workflows and production systems, personally developing critical components while providing technical leadership and mentorship to team members implementing other parts of the system
• Collaborate cross-functionally with ML scientists, product managers, and engineers to define and prioritize system requirements
• Partner with our ML platform team to translate technical needs into infrastructure requirements, advocating for platform capabilities that enhance reliability, boost team productivity, and support our long-term vision for innovation at scale
• Optimize systems and workflows for latency, throughput, and reliability across both batch processing workflows and real-time services to meet SLA requirements
• Strategically identify and address technical debt to improve development velocity, while implementing tools and processes that enhance team productivity and code quality

About you:
• 5+ years of proven experience in software engineering for ML projects and products, with strong proficiency in Python
• BSc in Computer Science, Electrical Engineering, or a related technical field.
• Familiarity with ML libraries such as PyTorch, experience with ML/CV/GenAI pipelines, and knowledge of distributed data processing systems.
• Experience with ML workflow orchestration tools like Metaflow, Airflow, or similar pipeline management systems
• Proficient in cloud infrastructure, including S3, Docker containers.
• Basic understanding of (multi) GPU training and inference for debugging and performance assessment, and CUDA runtime.
• Demonstrated ability to effectively communicate technical requirements and influence infrastructure decisions across team boundaries
• Track record of mentoring engineers on ML engineering best practices while balancing technical debt reduction with feature delivery
• Excellent communication and interpersonal skills, with a strong ability to navigate ambiguity.
• You are collaborative and thrive in fast-paced dynamic environments, contributing positively to the team and company culture.
• The Netflix culture resonates with you.

Bonus Experience:
• Experience with GPU training and inference optimization, performance tuning, and debugging
• Experience building end-to-end multimedia systems and computer vision algorithms.
• Familiarity with generative models and tools, such as diffusion-based models
Our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $150,000 - $750,000 .

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Job is open for no less than 7 days and will be removed when the position is filled.

Jobcode: Reference SBJ-bxw33x-18-97-14-85-42 in your application.