MLOps Engineering Lead - Digital Data, Large Molecule Research - Vaccines

Company: Sanofi
Location: Cambridge
Posted on: March 17, 2023

Job Description:

Position Title: MLOps Engineering Lead (Digital Data, Large Molecule Research)

About Sanofi:

We are an innovative global healthcare company, driven by one purpose: chasing the miracles of science to improve people's lives. Our team, across some 100 countries, is dedicated to transforming the practice of medicine by working to turn the impossible into the possible. We provide potentially life-changing treatment options and life-saving vaccine protection to millions of people globally, while putting sustainability and social responsibility at the center of our ambitions.

Sanofi has recently embarked on a vast and ambitious digital transformation program. A cornerstone of this roadmap is the acceleration of its data transformation and of the adoption of artificial intelligence (AI) and machine learning (ML) solutions to accelerate R&D, manufacturing and commercial performance, and bring better drugs and vaccines to patients faster, to improve health and save lives.

In alignment to our digital transformation, we have launched a new major strategic initiative in 2023: the Biologics x AI Transformation. This is positioned to be a unique data-driven team, with expertise in AI platforms, data engineering, ML operations, data science, computational biology, strategy, and beyond. We are working as one to identify, design, and scale state-of-the-art AI capabilities targeted to truly transform how we research biologics.

Who You Are:

You are a dynamic MLOps specialist interested in challenging the status quo to ensure seamless MLOps that scale up Sanofi's AI solutions for the patients of tomorrow. You are an influencer and leader who has deployed AI/ML solutions with technically robust lifecycle management (e.g., new releases, change management, monitoring and troubleshooting) and infrastructural support. You have a keen eye for improvement opportunities and a demonstrated ability to deliver using software Leading and MLOps skills while working across the full stack and moving fluidly between programming languages and technologies.

Our Tech Stack:

We leverage best-in-class tools and practices to accelerate our analytical builds. For creating production ready machine learning pipelines and monitoring, we leverage tools such as: Python, PySpark, MLFlow, Grafana, and Prometheus. For container technologies, we leverage tools like Docker and Kubernetes. The list of tools continues if we look at GitHub for CI/CD, Terraform and Ansible for deployment, Argo Workflows for orchestration/scheduling and much more.

Job Highlights:

• Work in agile pods to design and build cloud hosted, ML products with automated pipelines that run, monitor, and retrain ML Models
• Design and build effective, user-friendly infrastructure to enable scalable, auditable and maintainable machine learning services
• Support life cycle management of deployed ML apps (e.g., new releases, change management, monitoring and troubleshooting)
• Work as MLOps subject matter expert (e.g., develop and maintain enterprise machine learning standards, user guides, release notes, FAQs)
• Design AI/ML apps and implement automated model and pipeline adaption and validation working closely with data scientists, engineers, project managers and more
• Walk stakeholders and solution partners through solutions and reviewing product change and development needs
• Collaborate with pharma domains to make production level machine learning code and support creating reusable components in the form of libraries and APIs to accelerate data science build
• Research and gain expertise on emerging tools and technologies related to MLOps. An enthusiasm to ask questions and try and learn new things is essential Key Functional Requirements & Qualifications:
  • Graduate degree in Computer Science, Information Systems, Software Engineering, or another quantitative field
  • 5+ years of experience as a MLOps or ML Engineer, preferably building and maintaining machine learning models
  • 2+ years of experience deploying and monitoring ML applications at scale across a range of models and platforms
  • Experience developing and maintaining software libraries, following industry standard expectations. Preferably have experience contributing to open-source libraries
  • Experience in data science, deep learning, statistics, software design, and design thinking
  • Experience developing CI/CD pipelines for AI/ML development, deploying models to production, monitoring models in production, and managing the lifecycle in a regulated environment. Preferably using Git for version control and tools like Kubeflow, Metaflow or MLFlow for lifecycle management
  • Experience in developing and maintaining APIs (e.g.: REST)
  • Experience specifying infrastructure and Infrastructure as a code (e.g.: Docker, Kubernetes, Terraform)
  • Ability to work across the full stack and move fluidly between programming languages and MLOps technologies (e.g.: Python, Spark, GitHub, MLFlow, Argo Workflows)
  • Experience in cloud and high-performance computing environments (AWS, Databricks preferred)
  • Experience in AWS (e.g.: S3, Lambda, EC2) and other similar technologies (e.g.: ELK stack, Snowflake, Informatica)
  • Experience working in an agile pod supporting and working with cross-functional teams
  • Ability to assess new technologies and compile architecture decision records (ADRs)
  • Knowledge of SQL and relational databases, query authoring (SQL) and designing variety of databases (e.g., Postgres SQL)
  • Familiarity with visualization technologies (e.g.: RShiny, Python DASH, Tableau, PowerBI)
  • Experience on working within compliance (e.g.: quality, regulatory - data privacy, GxP, SOX) and cybersecurity requirements is a plus
  • Mentoring and/or technology evangelism/advocacy experience
  • Excellent communication skills in English, both verbal and in writing As a healthcare company and a vaccine manufacturer, Sanofi has an important responsibility to protect individual and public health. All US based roles require individuals to be fully vaccinated against COVID-19 as part of your job responsibilities.
    
    According to the CDC, an individual is considered to be "fully vaccinated" fourteen (14) days after receiving (a) the second dose of the Moderna or Pfizer vaccine, or (b) the single dose of the J&J vaccine. Fully vaccinated, for new Sanofi employees, is to be fully vaccinated 14 DAYS PRIOR TO START DATE.
    
    Sa nofi Inc. and its U.S. affiliates are Equal Opportunity and Affirmative Action employers committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.
    
    At Sanofi diversity and inclusion is foundational to how we operate and embedded in our Core Values. We recognize to truly tap into the richness diversity brings we must lead with inclusion and have a workplace where those differences can thrive and be leveraged to empower the lives of our colleagues, patients and customers. We respect and celebrate the diversity of our people, their backgrounds and experiences and provide equal opportunity for all.
    
    

Keywords: Sanofi, Cambridge , MLOps Engineering Lead - Digital Data, Large Molecule Research - Vaccines, Engineering , Cambridge, Massachusetts