Lead DevOps Engineer at Invitae
Invitae is dedicated to bringing comprehensive genetic information into mainstream medicine to improve healthcare for billions of people. Our team is driven to make a difference for the patients we serve. We are leading the transformation of the genetics industry, by making genetic testing affordable and accessible for everyone to guide health decisions across all stages of life.
This role is with our new Ciitizen team. Ciitizen is a health technology platform that enables patients with cancer and rare neurologic disorders to collect, digitize, and share their health information. We are looking for an experienced and motivated engineer to join our Machine Learning/AI team as the lead DevOps Engineer. In this role, you will focus on designing and developing tools and capabilities to enable the ML/AI and Clinical teams with data management and data annotation as well as architecting ML/AI solutions for productization. You will serve as a bridge between the ML, clinical, and engineering teams to lead efforts to transform ML POC functions to product-grade features. You will collaborate with research scientists, engineers, clinicians, and product managers to make informed decisions, manage risks, and create opportunities. You will demonstrate scaled ML Deployment and MLOps experience to address complex healthcare data problems. The Lead DevOps Engineer will directly work with the Director of ML/AI.Responsibilities:
- Work multi-functionally with research scientists, engineers, clinicians, and product owners to understand, propose, implement, and deploy machine learning pipelines
- Improve existing machine learning scalability, usability, and performance across multiple products
- Familiarize with the state-of-the-art MLOps technologies and apply them to deliver business values
- Design, develop and refine infrastructure for Clinical ML platform, enabling data annotation, rapid ML/AI model development, training, and evaluation at scale
- Establish ML engineering processes and standard methodologies for data scientists using our ML platform
- Collaborate with research scientists and engineers, clinicians, and business leads to deliver
- ML-based systems that can be deployed both in the cloud and on edge using containers
- Communicate and share knowledge with other team members and actively participate in various learning-sharing opportunities
- At least 2 years of experience working in a DevOps or data engineer role using cloud-based infrastructures such as AWS, GCP, or Microsoft Azure
- At least 2 years of experience with containerization and orchestration (Kubernetes)
- Full-stack development experience for end-to-end engineering solutions
- Experience with Databases: SQL, MongoDB, Hadoop etc.
- Proficiency in Python and/or Java and strong object-oriented design skills coupled with a proven understanding of data structures and algorithms
- Experience in design, implementation and delivery of scalable build/test/release solutions using agile software development cycle
- Ability to work in a fast-paced environment and strong technical communication skills
- Familiarity with ML fundamentals and ML model training and deployment.
- Experience with deep learning frameworks (TensorFlow, Pytorch).
- Familiarity with workflow orchestration tools such as Kubeflow, Airflow, Luigi, or Perfect.
By joining Invitae, you’ll work alongside some of the world’s specialists in genetics and healthcare at the forefront of genetic medicine. We’ve built a culture that empowers our teammates to have the biggest impact and to explore their interests and capabilities. We prize freedom with accountability and offer significant flexibility, along with excellent benefits and competitive pay in a fast-growing organization.
At Invitae, we value diversity and provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
#LI - Remote