Offer summary

Qualifications:

Advanced degree (MS or PhD) in Computer Science, Electrical Engineering, or a related field with a focus on machine learning or AI., At least 5 years of industry experience in operationalizing ML models, especially in natural language processing., Proficiency in Python and experience with ML/DL frameworks such as PyTorch or Jax., Strong foundation in machine learning, deep learning, and model lifecycle management..

Key responsabilities:

Design and optimize ML pipelines for document understanding and insights generation.

Develop and deploy large-scale ML models using Netflix’s ML infrastructure.

Automate ML workflows for training, tuning, and deployment to enhance experimentation.

Collaborate with ML scientists and engineers to integrate models into applications and improve model observability.

Job description

Netflix is one of the world's leading entertainment services, with 283 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.

We are looking for an experienced ML engineer to develop, optimize, and deploy scalable ML solutions that enable self-service of analytics of both structured and unstructured data.

This role will be part of the Studio Production Data Science & Engineering team, focusing on enterprise productivity. The team is dedicated to developing and deploying analytical insights, as well as machine learning tools and models, to enhance strategy and decision-making within the Netflix Studio and beyond. By leveraging data science and engineering, the team aims to inform, support, and automate processes to drive efficiency and innovation

Responsibilities

Design, build and optimize ML pipelines for document understanding & extraction, and insights generation.
Develop and deploy large-scale ML models efficiently using Netflix’s ML infrastructure.
Optimize model performance and inference efficiency, ensuring scalability in high-throughput distributed environments.
Automate ML workflows for training, tuning and deployment, enabling faster experimentation and productization.
Collaborate with ML scientists and engineers to integrate language and vision models and embeddings into downstream applications, including chat interfaces, internal applications and other ML models.
Improve ML observability, model evaluations, model monitoring, and debugging tools to ensure reliability of deployed models.
Stay up to date with ML infrastructure advancements, identifying new technologies and best practices to enhance efficiency.

About You

You have a strong foundation in machine learning and deep learning, including embedding methods, supervised and unsupervised learning, deep learning architectures, and model evaluation
You have prior experience in language model embeddings, fine-tuning pipelines and frameworks around language models.
You have a track record of deploying ML systems at scale, particularly in high-performance inference and distributed training environments.
You have hands-on experience with training large generative models across multiple modalities (text, images, videos).
You have a strong understanding of feature engineering, data pipelines, and model lifecycle management.
You hold an advanced degree (MS or PhD) in Computer Science, Electrical Engineering, or a related technical field with a focus on machine learning, artificial intelligence or computer vision.
You have at least 5 years of relevant industry experience operationalizing ML models, particularly in the areas of natural language processing and machine learning.
You are proficient in Python and have experience with ML/DL frameworks such as PyTorch, or Jax.
You excel at complex problem solving with innovative solutions, developing novel algorithms, and adapting existing methods from literature to new challenges.
You are an excellent communicator, capable of explaining complex technical details to both technical and non-technical audiences.
You thrive in fast-paced dynamic environments with ambiguity, contributing positively to team collaboration and company culture.

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.

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