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Machine Learning Engineer
2 months ago
Role: Machine Learning Engineer
Location: South San Francisco, CA
Job Type: C2H (W2 Only)
Pay Rate: Open
Job Description:
Develop and deploy machine learning models in production environments, working closely with other engineers to ensure solutions are scalable, reliable, and built with best practices.
Solve core research engineering challenges including the design, implementation, and scaling of machine learning algorithms.
Collaborate with cross-functional teams including research scientists, computational biologists, and data engineers to solve complex problems.
Build solutions that allow stakeholders to interact with and analyze multimodal datasets.
Who you are:
Educational Background: B.S. in Computer Science, Machine Learning, Statistics, Mathematics, Physics, or a related field (Graduate degree preferred).
Experience: Proven track record with 4+ years of experience developing and applying ML models in an industry setting.
Technical Skills:
Proficiency in Python
Experience with Weights and Biases
Proficiency in MLOps workflows (e.g., familiar with code version control, high-performance compute infrastructures, and machine learning experiment monitoring workflows)
Extensive experience with machine learning frameworks and libraries (e.g., JAX, PyTorch, PyTorch Lightning, Tensorflow).
Strong background in statistics, probabilistic modeling, and data analysis.
Soft Skills:
Strong communication skills, with the ability to effectively communicate technical concepts to both technical and non-technical audiences as well as interfacing with scientific and engineering leadership
Experience collaborating with external scientific partners, such as academic institutions or industry research groups
A passion for solving complex technical problems and a commitment to staying up-to-date with the latest developments in machine learning.
Note from the hiring manager:
-gRED Computational Sciences is recruiting for a seasoned ML engineer with direct experience in Research and Development
-This individual will be working on high profile and high visibility initiatives and will be interacting with cross-functional data and computational scientists and key leaders across gRED and gCS
-We've set a broad pay range as we are open to more junior candidates with the right experience and background who show potential to excel in the role.
-Our goal is to convert this individual to a FTE role after 3-6 months depending on performance
-The final pay/bill rate will be based on the experience level of the selected candidate.
