Find jobs
Pricing
Free Resume Checker
Blog
Sign in
Sign up
FIND JOBSPRICINGFREE RESUME CHECKERBLOGSIGN INSIGN UP
Jobs
/Machine Learning Engineer jobs
GE
Genentech

Machine Learning Engineer/Senior Machine Learning Engineer - Devops, AI for Drug Discovery

Salary$141k – $311k
LocationNew York City; South San Francisco
Typefull-time
SenioritySenior
Experience2–5 yrs
DepartmentEngineering
Company size10,000+ people
First seenOct 6, 2026 · 5d ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Must have14
BS/MS with 2-3 years of industry experience (for ML Engineer) or 3-5 years (for Senior ML Engineer)
Proven experience in designing, deploying, and managing infrastructure on Amazon Web Services (AWS) including EC2, S3, RDS, EKS, SageMaker
Strong proficiency with Git and Git repository management
Hands-on experience with Terraform for infrastructure provisioning and management
Experience with Helm for deploying and managing applications on Kubernetes
Proficiency in scripting languages (e.g., Python, Bash) for automation
Excellent problem-solving skills and a strong ability to debug complex issues
Strong communication and interpersonal skills to effectively collaborate with cross-functional teams and user-facing interactions
Demonstrated ability to take initiative, anticipate needs, and drive projects to completion
Ability to thrive in a fast-paced environment and adapt to evolving requirements while adhering to corporate guidelines
Ability to write clean code with little syntax/convention feedback
Applies software engineering best practices (linting automation, unit testing, documentation, CI/CD)
Familiarity with modern machine learning methods
Knowledge of and experience with high-performance computing, distributed systems, and cloud computing
Nice to have3
Experience with MLOps platforms and tools
Familiarity with CI/CD pipelines for ML workflows
Knowledge of monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack)
Skills
AWS
EC2
S3
RDS
EKS
SageMaker
Git
Terraform
Helm
Kubernetes
Python
Bash
Prometheus
Grafana
ELK stack
About the company
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.
Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.
The Opportunity
At Roche’s AI for Drug Discovery (AIDD) group (Prescient Design), we are revolutionizing drug discovery with cutting-edge machine learning techniques. We are seeking a highly motivated and skilled ML Infrastructure DevOps Engineer to join our growing team within Genentech Research and Early Development AI Drug Development (gRED AIDD). This role is crucial for building and maintaining the scalable and robust infrastructure that powers our machine learning initiatives. The ideal candidate will be proactive, user-facing, and possess a “get-it-done” attitude, while consistently adhering to corporate standards and best practices.
What you’ll do
Machine Learning Engineer - DevOps
•
Design, implement, and maintain scalable and reliable ML infrastructure on AWS.
•
Automate deployment, monitoring, alerting, and operational tasks using tools like Terraform and Helm.
•
Manage and optimize CI/CD pipelines and Git repositories for ML projects, ensuring efficient version control to support collaboration and deployment.
•
Collaborate closely with ML engineers and data scientists to understand their infrastructure needs and provide solutions.
•
Troubleshoot and resolve infrastructure-related issues in a timely manner.
•
Implement and enforce security best practices for ML infrastructure.
•
Document infrastructure designs, processes, and operational procedures.
•
Contribute to initiatives independently as part of a team, delivering assigned outputs.
•
Proactively identify issues and gaps, proposing ideas and suggestions for improvements.
Senior Machine Learning Engineer - DevOps
•
Lead the architecture and delivery of significant technical solutions
•
Mentor junior engineers and drive technical alignment and influence across teams
•
Design, implement, and maintain scalable and reliable ML infrastructure on AWS.
•
Demonstrated ability to lead technical projects from conception to completion and deliver high-quality, scalable, and reliable software." to "Who you are
•
Automate deployment, monitoring, alerting, and operational tasks using tools like Terraform and Helm.
•
Manage and optimize CI/CD pipelines and Git repositories for ML projects, ensuring efficient version control to support collaboration and deployment.
•
Collaborate closely with ML engineers and data scientists to understand their infrastructure needs and provide solutions.
•
Troubleshoot and resolve infrastructure-related issues in a timely manner.
•
Implement and enforce security best practices for ML infrastructure.
•
Document infrastructure designs, processes, and operational procedures.
•
Contribute to initiatives independently as part of a team, delivering assigned outputs.
•
Proactively identify issues and gaps, proposing ideas and suggestions for improvements.
Who you are
Machine Learning Engineer - DevOps
•
BS/MS with 2-3 years of industry experience required
•
Proven experience in designing, deploying, and managing infrastructure on Amazon Web Services (AWS), including services such as EC2, S3, RDS, EKS, SageMaker, etc.
•
Strong proficiency with Git and Git repository management.
•
Hands-on experience with Terraform for infrastructure provisioning and management.
•
Experience with Helm for deploying and managing applications on Kubernetes.
•
Proficiency in scripting languages (e.g., Python, Bash) for automation.
•
Excellent problem-solving skills and a strong ability to debug complex issues.
•
Strong communication and interpersonal skills to effectively collaborate with cross-functional teams and user-facing interactions.
•
Demonstrated ability to take initiative, anticipate needs, and drive projects to completion.
•
Ability to thrive in a fast-paced environment and adapt to evolving requirements while adhering to corporate guidelines.
•
Ability to write clean code with little syntax/convention feedback.
•
Applies software engineering best practices (linting automation, unit testing, documentation, CI/CD).
•
Familiarity with modern machine learning methods.
•
Knowledge of and experience with high-performance computing, distributed systems, and cloud computing.
Senior Machine Learning Engineer - DevOps
•
BS/MS with 3-5 years of industry experience required
•
Proven experience in designing, deploying, and managing infrastructure on Amazon Web Services (AWS), including services such as EC2, S3, RDS, EKS, SageMaker, etc.
•
Strong proficiency with Git and Git repository management.
•
Hands-on experience with Terraform for infrastructure provisioning and management.
•
Experience with Helm for deploying and managing applications on Kubernetes.
•
Proficiency in scripting languages (e.g., Python, Bash) for automation.
•
Excellent problem-solving skills and a strong ability to debug complex issues.
•
Strong communication and interpersonal skills to effectively collaborate with cross-functional teams and user-facing interactions.
•
Demonstrated ability to take initiative, anticipate needs, and drive projects to completion.
•
Ability to thrive in a fast-paced environment and adapt to evolving requirements while adhering to corporate guidelines.
•
Ability to write clean code with little syntax/convention feedback.
•
Applies software engineering best practices (linting automation, unit testing, documentation, CI/CD).
•
Familiarity with modern machine learning methods.
•
Knowledge of and experience with high-performance computing, distributed systems, and cloud computing.
Nice to have
Preferred
•
Experience with MLOps platforms and tools.
•
Familiarity with CI/CD pipelines for ML workflows.
•
Knowledge of monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack)
Relocation benefits are NOT available for this job posting
The expected salary range for this position based on the primary location of California for the Machine Learning Engineer is $147,600, - $274,000 and New York is $141,100 - $262,100, and the Senior Machine Learning Engineer for California is $167,400 - $310,800 and New York is $160,100 - $297,300. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits
Benefits
#ComputationCoE
#tech4lifeComputationalScience
#tech4lifeAI
Legal
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company’s policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.
More roles at Genentech
Business Engagement Manager (BEM) - Michigan EcosystemSenior Group Medical Director, Global Disease Area Head Respiratory, Allergy, and Infectious Diseases Product DevelopmentSenior Director, U.S. Product Public Relations - Neuroscience & OphthalmologyPeople & Culture Enabling Support SpecialistBioprocess Technician - Clinical Supply Center
Seekless
Seek less: one search across companies' own career pages, instead of a dozen job boards.
Product
Find jobsCompaniesPricingFree Resume Checker
Company
AboutBlog
Legal
PrivacyTermsCookies
© 2026 SEEKLESS. ALL RIGHTS RESERVED.BUILT WITH CARE