Machine Learning Infrastructure Engineer - #4694

GRAIL, Inc.

Job Overview

Location

Menlo Park, CA

Job Type

Full-time

Full Job Description

📋 Description

• As a Machine Learning Infrastructure Engineer at GRAIL, you will play a critical role in enabling the development and deployment of cutting-edge machine learning models that power early cancer detection technologies, directly contributing to life-saving advancements in healthcare by ensuring robust, scalable, and efficient ML systems.
• You will design, build, and maintain the foundational infrastructure that supports machine learning workflows, including data pipelines, model training environments, experiment tracking, and model serving systems, ensuring seamless integration between research and production environments.
• Your day-to-day responsibilities will include developing and optimizing scalable data ingestion and preprocessing pipelines using technologies such as Apache Spark, Kafka, and Airflow to handle large-scale genomic and clinical datasets.
• You will implement and manage containerized ML workloads using Kubernetes and Docker, ensuring reproducibility, scalability, and efficient resource utilization across GPU and CPU clusters.
• You will collaborate closely with data scientists and ML researchers to translate experimental models into production-ready systems, providing tools and platforms that accelerate model iteration, validation, and deployment.
• You will establish and maintain CI/CD pipelines for ML models, incorporating automated testing, version control, and monitoring to ensure reliability and performance in production.
• You will work with cloud infrastructure (primarily AWS and/or GCP) to provision and manage compute, storage, and networking resources optimized for ML workloads, including cost optimization and security best practices.
• You will contribute to the development of internal ML platforms and tools that standardize workflows, improve collaboration, and increase the velocity of ML innovation across teams.
• You will monitor system performance, troubleshoot issues, and implement observability solutions (logging, metrics, tracing) to ensure high availability and reliability of ML services.
• You will stay current with emerging ML infrastructure technologies and advocate for adoption of innovations that improve efficiency, scalability, and model performance.
• GRAIL is a mission-driven healthcare technology company at the forefront of early cancer detection, bringing together world-class experts in genomics, data science, clinical research, and engineering to transform cancer care through innovation.
• The team operates with a strong culture of scientific rigor, collaboration, and urgency, where engineering excellence directly impacts patient outcomes and advances the frontiers of medical science.
• In this role, you will gain deep expertise in ML infrastructure at scale, working with cutting-edge tools in cloud computing, distributed systems, and MLOps while contributing to a cause with profound societal impact.
• You will have the opportunity to grow as a technical leader, shaping the architecture and strategy of ML systems that support breakthroughs in early cancer detection and potentially influencing the future of healthcare AI.

🎯 Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 3+ years of experience building and maintaining ML infrastructure, data pipelines, or large-scale distributed systems in production environments.
• Proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Hands-on experience with orchestration tools like Apache Airflow, Kubeflow, or MLflow for managing ML workflows.
• Strong background in cloud platforms (AWS, GCP, or Azure), including experience with services such as EC2, S3, SageMaker, EKS, or equivalent.
• Experience with containerization (Docker) and orchestration (Kubernetes) in production ML or data-intensive applications.

🏖️ Benefits

• Comprehensive health, dental, and vision insurance plans for employees and dependents.
• Generous paid time off, including vacation, sick leave, and company holidays.
• 401(k) retirement plan with company matching to support long-term financial security.
• Equity compensation opportunities, allowing employees to share in the company’s success and mission-driven growth.
• Wellness programs and resources supporting physical and mental health, including access to fitness subsidies and mental health services.
• Relocation assistance available for eligible candidates transitioning to the Menlo Park, CA area.

Skills & Technologies

DevOps

Onsite

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GRAIL, Inc.

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About GRAIL, Inc.

GRAIL develops multi-cancer early-detection blood tests using high-intensity sequencing, population-scale clinical trials, and machine learning. Its Galleri test screens for over 50 cancers from a single blood draw, aiming to shift diagnosis from late-stage symptoms to early, treatable stages. The company conducts large prospective studies, partners with health systems, and pursues FDA approval to integrate screening into routine care. Founded in 2016 as a spin-out from Illumina, GRAIL operates laboratories in the United States and the United Kingdom and focuses on evidence generation, regulatory science, and equitable test access.

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