About this opportunity
myBridge Corporation lists this Machine Learning Engineer opportunity in san francisco, California. Review the employer’s description below for duties, qualifications and application requirements.
Job description
$160,000 Annually
401K, Medical Insurance, Dental Insurance, Vision Insurance
Full-Time | On-site
Why work here
Work with innovative AI technologies and talented data professionals on practical machine learning projects.
Required Skills
Machine Learning Engineer
Industry: Artificial Intelligence / Data Science
Job Type: Full-Time
Location: San Francisco, California, USA
Postal Code: 94105
Job Description
We are looking for an experienced Machine Learning Engineer to develop, deploy, and maintain machine learning solutions that support business and product objectives. The role involves transforming data into predictive models, building machine learning pipelines, evaluating model performance, and deploying AI solutions into production environments.
The Machine Learning Engineer will collaborate with data scientists, data engineers, software developers, product managers, and business stakeholders. The successful candidate should understand the complete machine learning lifecycle, including data preparation, model development, evaluation, deployment, monitoring, and continuous improvement.
Key Responsibilities
Develop and deploy machine learning models.
Prepare and transform large datasets.
Build scalable ML pipelines.
Evaluate and improve model performance.
Work with data scientists on productionizing models.
Implement machine learning APIs and services.
Monitor models in production.
Perform model validation and testing.
Research emerging AI technologies.
Document machine learning systems.
Collaborate with engineering and product teams.
Education
Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, Artificial Intelligence, or related field.
Master's degree in Machine Learning, AI, or Data Science preferred.
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Worksite address
san francisco, CA, 94199, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.