Machine Learning Engineer

Contract: San Francisco, California, US

Salary: $100.00 Per Hour

Job Code: 354376

End Date: 2024-10-27

Days Left: 28 days, 5 hours left

Position Details:
Client: Biotechnology Corporation
Job Title: Machine Learning Engineer 
Duration: 6 Months of Contract 
Location: South San Francisco, CA 94080
Pay Range: $85/hr. - $100/hr.
Start Date: ASAP
 
The team:
  • At Research & Early Development (gRED) we have initiated an exciting journey to bring together and further strengthen our computational talent and capabilities by forming a new, central organization - gRED Computational Sciences (gCS).
  • gCS is on a mission to partner across the organization to realize the potential of data, technology and computational approaches that will revolutionize how targets and therapeutics are discovered and developed, ultimately enabling novel treatments for patients across the world. We stand at the beginning of this exciting journey.
  • The Computational Catalysts group within gCS is a diverse, curious and action-driven team at the intersection of computation, engineering and science with ambition to advance our technical excellence.
  • The focus of the team is on partnering with the informatics and scientific communities to create a computational and data ecosystem that powers scientific discovery and accelerates decision making.
  • We aim to modernize our ability to acquire, store, link, share, find and analyze data across the organization through scalable and integrated solutions that truly make every data point count.
The Opportunity:
  • Our group is seeking an exceptional Machine Learning Engineer with a passion for building machine learning algorithms and systems that will transform the drug discovery process.
  • We are looking for someone who is not only passionate about technical problem-solving but also has a consistent record of delivering innovative solutions in machine learning.
  • The ideal candidate should have extensive experience in developing, deploying, and maintaining models and be able to foster a culture of innovation, collaboration, and excellence across the broader gCS organization.
  • The group provides a dynamic and challenging environment for multidisciplinary research including access to heterogeneous data sources, close links to top academic institutions around the world, as well as collaborations with internal and Roche teams.
  • The right candidate will have experience working in different computing environments, including traditional HPC and AWS.
  • The candidate will have a good understanding of best practices in software engineering and will use it to provide solutions that are scalable and reusable.
  • The candidate will have experience working with diverse data in the biomedical space, including genetics, genomics, imaging, and clinical data.
  • The candidate will be comfortable working as part of a team and also independently.
What you will do:
  • 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.
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 Machine Learning models in an industry setting.
Technical Expertise:
  • 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 Skillset:
  • Strong communication skillset, 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.
Job Requirement
  • Machine Learning
  • Statistics
  • Probability
  • probabilistic
  • data
  • JAX
  • PyTorch
  • Tensorflow
  • Python
  • Framework
  • research
  • development
  • Weights
  • Biases
  • Bias
  • health
  • healthcare
  • pharma
  • pharmaceutical
  • Biotech
  • MLOps
Reach Out to a Recruiter
  • Recruiter
  • Email
  • Phone
  • Swarit Gujrati
  • swarit.gujrati@collabera.com
Apply Now
Apply Now
close-icon

Collabera is a leading global digital talent solutions firm. For over 25 years, we have provided digital and IT talent services, direct placement and career advisement, global remote talent and learning solutions to transform and diversify workforces for the Fortune 1000 globally.

Consultant Login
About
Resources
Phones Email

Collabera is a leading global digital talent solutions firm. For over 25 years, we have provided digital and IT talent services, direct placement and career advisement, global remote talent and learning solutions to transform and diversify workforces for the Fortune 1000 globally.

Consultant Login

©2024 Collabera. All rights reserved.