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

F. Hoffmann-La Roche AG; New York (NY); On-site; USD 141,100 - 262,100; Full time

Benefits offered by this job

Discretionary annual bonus based on performance

Job summary

F. Hoffmann-La Roche AG in New York is seeking a Machine Learning Engineer to design and maintain scalable ML infrastructure on AWS. The role involves collaboration with ML engineers and automating workflows, ensuring security best practices while mentoring junior engineers.

Applicants should have a BS/MS in Computer Science or related fields along with 2–5 years of AWS infrastructure experience. Salary range for this position is $141,100 – $262,100, depending on qualifications.

Qualifications

• 2–5 years of industry experience designing and managing AWS infrastructure.
• Hands-on experience with Terraform for provisioning and Helm for Kubernetes.
• Knowledge of MLOps platforms and CI/CD pipelines.

Responsibilities

• Design and maintain scalable ML infrastructure on AWS.
• Automate deployment and operational tasks using Terraform and Helm.
• Collaborate with ML engineers on infrastructure needs.

Skills

AWS infrastructure management

Terraform

Git repository management

Python scripting

Bash scripting

Problem-solving skills

Communication skills

Education

BS/MS in Computer Science or related field

Tools

AWS

Terraform

Helm

Prometheus

Grafana

ELK

Job description

Overview

Roche’s Research and Early Development (R&D) organisations at Genentech (gRED) and Pharma (pRED) are harnessing advances in AI, data, and computational science to accelerate drug discovery and development. The new Computational Sciences Center of Excellence (CoE) unifies these efforts, providing scalable, robust infrastructure that powers machine learning initiatives across gRED and pRED.

Responsibilities

• Design, implement, and maintain scalable, reliable ML infrastructure on AWS.
• Automate deployment, monitoring, alerting, and operational tasks using Terraform, Helm, and scripting languages.
• Manage and optimize CI/CD pipelines and Git repositories for ML projects, ensuring efficient version control.
• Collaborate closely with ML engineers and data scientists to understand infrastructure needs and provide solutions.
• Diagnose and resolve infrastructure‑related issues promptly.
• Enforce security best practices for ML infrastructure.
• Document infrastructure designs, processes, and operational procedures.
• Mentor junior engineers and influence technical alignment across teams.

Qualifications

• BS/MS in Computer Science, Engineering, or related field.
• 2–5 years of industry experience designing, deploying, and managing AWS infrastructure (EC2, S3, RDS, EKS, SageMaker, etc.).
• Proficient with Git and repository management.
• Hands‑on experience with Terraform for infrastructure provisioning and Helm for Kubernetes deployments.
• Strong scripting skills in Python or Bash.
• Excellent problem‑solving skills and ability to debug complex issues.
• Effective communication and collaboration abilities in cross‑functional teams.
• Demonstrated initiative, proactive issue identification, and project delivery under fast‑paced conditions.
• Knowledge of high‑performance computing, distributed systems, and modern machine learning methods.
• Experience with MLOps platforms, CI/CD pipelines for ML workflows, and monitoring/logging tools (Prometheus, Grafana, ELK) is preferred.

Salary & Benefits

Salary ranges (based on location):

• California – Machine Learning Engineer: $147,600 – $274,000; Senior: $167,400 – $310,800.
• New York – Machine Learning Engineer: $141,100 – $262,100; Senior: $160,100 – $297,300.

Actual pay will be based on experience, qualifications, and geographic location. A discretionary annual bonus may be available based on individual and company performance.

Equal Employment Opportunity Statement

Genentech is an equal‑opportunity employer. We are committed to employment practices that promote merit, qualifications, and competence. Discrimination on the basis of veteran status, disability, or any other protected characteristic is prohibited in accordance with all applicable federal, state, and local laws. If you need accommodations during the application process, please contact us or complete the Accommodations for Applicants form.