Ml Ops Engineering Lead (Digital Data, Large Molecule Research)

Reference No. R2681338
Position Title: ML Ops Engineering Lead (Digital Data, Large Molecule Research)
Department: Data Strategy Program Management
At Sanofi, we chase the miracles of science to improve people’s lives. We believe our cutting-edge science and manufacturing, fueled by data and digital technologies, have the potential to transform the practice of medicine, turning the impossible into possible for millions of people.
As one of Canada’s leading investors in life sciences, manufacturing and research and development, we focus on delivering new and better ways to address unmet medical needs. Our life-changing and lifesaving products are grounded in science that Canadians can trust. They empower self-care, prevent and treat diseases, and help people live better.
Location: Located in the downtown area of Toronto, Ontario Canada, our team uses a hybrid working model combining remote and office-based work.
The Digital Team at Sanofi is a unique data-driven team. We pride ourselves on being data obsessed and highly focused on using state of the art processes along with global technologies to drive impact to our solutions. We measure our insights and products based on how they perform across the globe and hold ourselves to the highest regard as our solutions can impact millions of lives. When tackling a problem, we do not just ask how we will create a solution, but how we will create a solution that reaches across the world with the best possible societal outcome.
If you are passionate about improving the health and wellness of people across the globe using Data as your means, then you should look no farther than the Digital Team here at Sanofi. Join us on our journey in enabling Sanofi’s Digital Transformation through becoming an AI first organization.

• World Class Mentorship and Training: Working with renowned, published leaders and academics in machine learning to further develop your skillsets.
• Leading Edge Tech Stack: Experience build products that will be deployed globally on a leading-edge tech stack.
• AI Factory - Versatile Teams Operating in Cross Functional Pods: Utilizing digital and data resources to develop AI products, bringing data management, AI and product development skills to products, programs and projects to create an agile, fulfilling and meaningful work environment.

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.
Key Responsibilities:

• Design and build effective, user-friendly infrastructure to enable scalable, auditable and maintainable machine learning services.
• Design AI/ML apps and implement automated model and pipeline adaption and validation working closely with data scientists, engineers, project managers and more.
• Work as MLOps subject matter expert (e.g., develop and maintain enterprise machine learning standards, user guides, release notes, FAQs).
• 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.
• Support life cycle management of deployed ML apps (e.g., new releases, change management, monitoring and troubleshooting).
• Work in agile pods to design and build cloud hosted, ML products with automated pipelines that run, monitor, and retrain ML Models.
• 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.

Key Requirements:

• Graduate degree in Computer Science, Information Systems, Software Engineering, or another quantitative field.
• Experience on working within compliance (e.g.: quality, regulatory - data privacy, GxP, SOX) and cybersecurity requirements is a plus.
• Experience in developing and maintaining APIs (e.g.: REST).
• Experience in data science, deep learning, statistics, software design, and design thinking.
• Experience in cloud and high-performance computing environments (AWS, Databricks preferred).
• Experience working in an agile pod supporting and working with cross-functional teams.
• Experience specifying infrastructure and Infrastructure as a code (e.g.: Docker, Kubernetes, Terraform).
• Mentoring and/or technology evangelism/advocacy experience.
• 2+ years of experience deploying and monitoring ML applications at scale across a range of models and platforms.
• Excellent communication skills in English, both verbal and in writing.
• Knowledge of SQL and relational databases, query authoring (SQL) and designing variety of databases (e.g., Postgres SQL).
• Experience developing and maintaining software libraries, following industry standard expectations. Preferably have experience contributing to open-source libraries.
• Familiarity with visualization technologies (e.g.: RShiny, Python DASH, Tableau, PowerBI).
• 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.
• Ability to assess new technologies and compile architecture decision records (ADRs).
• Experience in AWS (e.g.: S3, Lambda, EC2) and other similar technologies (e.g.: ELK stack, Snowflake, Informatica).
• Ability to work across the full stack and move fluidly between programming languages and MLOps technologies (e.g.: Python, Spark, GitHub, MLFlow, Argo Workflows).
• 5+ years of experience as a MLOps or ML Engineer, preferably building and maintaining machine learning models.

Pursue Progress.
Discover Extraordinary
Better is out there. Better medications, better outcomes, better science. But progress doesn’t happen without people – people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. So, let’s be those people.
Watch our ALL IN video and check out our Diversity, Equity and Inclusion actions at sanofi.com!
Sanofi is an equal opportunity employer committed to diversity and inclusion. Our goal is to attract, develop and retain highly talented employees from diverse backgrounds, allowing us to benefit from a wide variety of experiences and perspectives. We welcome and encourage applications from all qualified applicants. Accommodations for persons with disabilities required during the recruitment process are available upon request.
Thank you in advance for your interest.
Only those candidates selected for interviews will be contacted.
Follow Sanofi on Twitter: @SanofiCanada and on LinkedIn: https://www.linkedin.com/company/sanofi
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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.