ML Engineer

Reference No. R2791160

Position Title: MLOps Engineer

Department: MLOps Engineering

Location: Toronto, Ontario, Hybrid

About the Job

Our Hubs are a crucial part of how we innovate, improving performance across every Sanofi department and providing a springboard for the amazing work we do. Build a career and you can be part of transforming our business while helping to change millions of lives. Ready?

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. 

We are an innovative global healthcare company with one purpose: to chase the miracles of science to improve people’s lives. We’re also a company where you can flourish and grow your career, with countless opportunities to explore, make connections with people, and stretch the limits of what you thought was possible. Ready to get started?

About You 

You are a dynamic MLOps Engineer interested in challenging the status quo to ensure seamless AI/ML Engineering Operations that scale up Sanofi's AI solutions for the patients of tomorrow. You are an influencer and a future leader who has deployed AI/ML solutions with technically robust lifecycle management and infrastructural support. You are deeply interested in improvement opportunities and always thrive to demonstrate ability to deliver using AI/ML Engineering skills while working across the full stack and moving fluidly between programming languages and technologies.   

 Main Responsibilities:  

• Work in an agile development pod to design, build and maintain cloud hosted AI/ML products with automated pipelines that run, monitor, and retrain ML Models  

• Implement automated ML pipelines (e.g., training and inference) working closely with other peers e.g., data scientists and data engineers  

• Support life cycle management of deployed AI/ML apps (e.g., new releases, change management, monitoring and troubleshooting) 

• Work as subject matter expert in MLOps (e.g., develop and maintain enterprise standards, user guides, release notes, FAQs)  

• Build processes and reusable components supporting seamless ML Operations (e.g., app monitoring, troubleshooting, life cycle management and customer support)  

• Walk stakeholders and solution partners through solutions and reviewing product change and development needs 

• Maintain effective relationships with app userbase to develop education and communication content as per life cycle events  

• Research and gain expertise on emerging tools and technologies. An enthusiasm to ask questions and try and learn new things is essential 

Key Technical Skills  

• University degree (Bachelor, Master or PhD) in Computer Science, Information Systems, Software Engineering, or another quantitative field.   

• Minimum 2 years of experience in building, deploying, monitoring and maintaining AI/ML applications utilizing cloud technologies (e.g., AWS, GCP, Azure, Snowflake etc.). 

• Ability to work across the full stack and move fluidly between programming languages (e.g., Python) and MLOps technologies (e.g. Github, Argo, Metaflow, WandB, Snowflake, AWS SageMaker)   

• Experience in implementing CI/CD pipelines for AI/ML driven app development 

• Experience in building and deploying apps with large scale data and ML pipelines  

• Ability to assess new technologies and compile architecture decision records (ADRs) 

• Experience working in an agile team supporting and working with cross-functional teams 

• Knowledge of relational (e.g., Postgres SQL) and non-relational databases (e.g., Graph database, Vector Database etc.) 

• Experience in visualization technologies (e.g.  Python DASH, Tableau, PowerBI)   

• Experience in developing and maintaining backend APIs (e.g.  REST)   

• Experience in provisioning cloud infrastructure leveraging Infrastructure as a code tools (e.g.: Docker, Kubernetes, Terraform)   

• Experience in cloud-based ML engineering in an industrial setting within a global organization (technology company preferred)   

• Experience in working within compliance (e.g. quality, regulatory - data privacy, GxP, SOX) and knowledge in cybersecurity is a plus   

Why Choose Us?

• Bring the miracles of science to life alongside a supportive, future-focused team.

• Discover endless opportunities to grow your talent and drive your career, whether it’s through a promotion or lateral move, at home or internationally.

• Enjoy a thoughtful, well-crafted rewards package that recognizes your contribution and amplifies your impact.

• Take good care of yourself and your family, with a wide range of health and wellbeing benefits including high-quality healthcare, prevention and wellness programs

This position is for a current vacant role that we are actively hiring for.​

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.

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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.

At Sanofi, we provide equal opportunities to all regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, ability or gender identity.

Watch our ALL IN video and check out our Diversity Equity and Inclusion actions at sanofi.com!