Lead Engineer, Machine Learning Applications
Toronto
Sanofi
We are an innovative global healthcare company with one purpose: to chase the miracles of science to improve people’s lives.Reference No. R2732897
Position Title: Lead Engineer, Machine Learning Applications
Department: Data Engineering Management
Location: Downtown area of Toronto, Ontario
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.
Our vision for digital, data analytics and AI
Sanofi has embarked into 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. This has enabled us, to accelerate R&D, improve manufacturing and commercial performance, and bring novel drugs and vaccines to patients faster, all in order to improve health and save lives.
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.
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.
Leading Edge Tech Stack: Experience build products that will be deployed globally on a leading-edge tech stack.
World Class Mentorship and Training: Working with renowned, published leaders and academics in machine learning to further develop your skillsets.
Who You Are:
You are a seasoned Software Engineer interested in leveraging large scale ML systems to augment the drug discovery process while also scaling up Sanofi's AI solutions for the patients of tomorrow. You are comfortable working in large teams with disparate stakeholders where you can lead and champion technical decisions. You have experience deploying 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 engineering and ML software integration skills while working across the full stack and moving fluidly between programming languages and technologies.
Key Responsibilities:
Work in agile pods to design and build cloud hosted, ML products with automated pipelines that run, monitor, and retrain ML Models.
Design AI/ML apps and implement automated model and pipeline adaption and validation working closely with data scientists and data engineers.
Support the full MLOps life cycle of new and existing ML applications (e.g., new releases, change management, monitoring and troubleshooting).
Work as ML systems architecture design SME (e.g., develop and maintain enterprise standards, user guides, release notes, FAQs).
Build processes supporting seamless ML integrations (e.g., app monitoring, troubleshooting, life cycle management and customer support).
Maintain effective relationships with application 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 Requirements:
Key Functional Requirements & Qualifications
Experience in data science, statistics, software engineering, modular design and design thinking.
Experience developing CI/CD pipelines for AI/ML development, deploying models to production, and managing the lifecycle in a regulated environment.
Experience building and deploying data science apps with large scale data and ML pipelines and architectures.
Experience working in an agile pod supporting and working with cross-functional teams.
Good understanding of ML and AI concepts and hands-on experience in development, deployment and agile life cycle management of data science apps.
Ability to assess new technologies and compile architecture decision records (ADRs).
Excellent communication skills in English, both verbal and in writing.
Key Technical Requirements & Qualifications
Graduate degree in Computer Science, Information Systems, Software Engineering or another quantitative field.
Ability to work across the full stack and move fluidly between programming languages (e.g.: Python, SQL, Spark) and ML frameworks (e.g.: Metaflow, MLFlow, Argo).
Experience in cloud and high-performance computing environments.
Experience in AWS (e.g.: S3, Lambda, SageMaker, CloudWatch)
Knowledge of relational and non-relational databases.
Nice to have knowledge of visualization technologies (e.g.: Tableau, PowerBI).
Experience in development, deployment and operations of AI/ML modelling of complex datasets.
Experience in developing and maintaining APIs (e.g.: REST, gRPC).
Experience specifying infrastructure and Infrastructure as a code (e.g.: Docker, Kubernetes, EKS, Terraform).
Mentoring and/or technology evangelism/advocacy experience preferred.
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
#DBBCA #DDB
Pursue progress, discover extraordinaryBetter 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!
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile APIs Architecture AWS CI/CD Computer Science Data Analytics Data management Docker Drug discovery Engineering Kubernetes Lambda Machine Learning MLFlow ML models MLOps Pipelines Power BI Python R R&D RDBMS Research SageMaker Spark SQL Statistics Tableau Terraform
Perks/benefits: Career development Equity Health care Team events Wellness
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