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Sr. Machine Learning Engineer

Pinterest Job Advertisements · San Francisco, CA, US; Remote, US

Extracted from the posting

Base
Not stated
Remote
Partial telecommuting from commutable distance
Visa
No relocation assistance
Stack
Python, TensorFlow, PyTorch, Kubernetes

Sr ML Engineer building recommendation systems and LLM models for Pinterest's Homefeed, Ads, and Search surfaces. Stack: C++, Python, Java, SQL, PyTorch, Spark, Airflow, Kubernetes.

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

Job Duties: Build cutting edge technology using the latest advances in deep learning and machine learning. Partner closely with teams across to experiment and improve machine learning models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how machine learning works in different areas. Use data driven methods and leverage the unique properties of our data to improve candidates’ retrieval. Work in a high-impact environment with quick experimentation and product launches. Keep up with industry trends in recommendation systems. Leverage LLMs to enhance content understanding. Partial telecommuting permitted from within a commutable distance.

Minimum Requirements: Master's degree in Electrical Engineering, Computer Science or a related field and three (3) years of experience in the job offered or in a related position.

Special Skill Requirements: Three years of experience in the following: 1) C++, Python, Java, and SQL for production services, data analysis.; 2) Databases and distributed storage- distributed relational system; 3) Large Language Model (LLM); 4) Approximate nearest neighbor (ANN) search; 5) Recommender systems, Search systems, Ads systems; 6) Spark; 7) Airflow; 8) Kubernetes; 9) A/B Testing; 10) Pytorch; and 11) Information retrieval. Partial telecommuting permitted from within a commutable distance.

Salary: $249,600.00 to $332,012.00 per annum

Reference #: L25-167700

This position is not available for relocation assistance.

Our Commitment to Inclusion:

Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Know Your Rights and Pinterest Policy for more information regarding U.S. roles. If you require a medical or religious accommodation during the job application process, please complete this form for support.

By submitting this application, I certify that all information submitted in my application and throughout the hiring process is true, accurate, and complete to the best of my knowledge. I understand that any false statement, omission, or misrepresentation may disqualify me from employment consideration or result in termination if discovered after hire.

Technologies

PythonTensorFlowPyTorchKubernetesAWSSQLApache SparkGit
Pinterest Job Advertisements
Pinterest Job Advertisements

Job details

TypeFull-time
Work ModeHybrid
LevelSenior
Location🇺🇸San Francisco, CA
PostedNov 03, 2026
Apply Now

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