Happy Elements
Machine Learning Engineer
Location: San Francisco, CA
Salary: $149,998.00 - $250,000.00
Responsibilities
Build, maintain, and improve efficient and reliable data mining and machine learning models.
Design, implement and tune machine learning models, and provide performance feedback.
Work closely with data engineers to adapt and improve data pipelines for production models.
Work closely with software engineers in putting models into production (interface, SLA, scalability).
Qualifications
Strong academic background required. MS in Computer Science or Machine Learning with 2+ years of industry experience or PhD in related field with 1+ years of industry experience required.
Expert in Python, and computation graph toolkits (e.g., Scikit-learn, Tensorflow). Solid experience with Python packages such as Numpy, Panda, and Scikit-learn.
Expert/Master in common families of machine learning models, feature engineering, feature selection techniques, and tuning of machine learning models.
Master with SQL or other relational database.
Master in building and productionizing end-to-end machine learning systems.
Knowledge and experience in cloud computing is a plus.
Extensive data modeling and data architecture skills.
Advanced math skills (linear algebra, Bayesian statistics, group theory).
Ability to consistently exercise independent discretion and judgment on significant matters.
Strong analytical, problem-solving and communication skills.
Ability to work in a team environment.
We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr
Salary: $149,998.00 - $250,000.00
Responsibilities
Build, maintain, and improve efficient and reliable data mining and machine learning models.
Design, implement and tune machine learning models, and provide performance feedback.
Work closely with data engineers to adapt and improve data pipelines for production models.
Work closely with software engineers in putting models into production (interface, SLA, scalability).
Qualifications
Strong academic background required. MS in Computer Science or Machine Learning with 2+ years of industry experience or PhD in related field with 1+ years of industry experience required.
Expert in Python, and computation graph toolkits (e.g., Scikit-learn, Tensorflow). Solid experience with Python packages such as Numpy, Panda, and Scikit-learn.
Expert/Master in common families of machine learning models, feature engineering, feature selection techniques, and tuning of machine learning models.
Master with SQL or other relational database.
Master in building and productionizing end-to-end machine learning systems.
Knowledge and experience in cloud computing is a plus.
Extensive data modeling and data architecture skills.
Advanced math skills (linear algebra, Bayesian statistics, group theory).
Ability to consistently exercise independent discretion and judgment on significant matters.
Strong analytical, problem-solving and communication skills.
Ability to work in a team environment.
We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr