ML Ops Engineer - All Genders
Le contenu du poste est libellé en anglais car il nécessite de nombreuses interactions avec nos filiales à l’international, l'anglais étant la langue de travail.
Job Title: ML Ops Data Engineering - All Genders
ABOUT THE JOB
About Sanofi
We are an innovative global healthcare company, driven by one purpose: We chase the miracles of science to improve people’s lives.
Sanofi has recently 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, to accelerate R&D, manufacturing and commercial performance and bring better drugs and vaccines to patients faster, to improve health and save lives.
Who You Are
You are a dynamic MLOps Engineer 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 engineering and MLOps skills while working across the full stack and moving fluidly between programming languages and technologies.
Our vision for digital, data analytics and AI
Join us on our journey in enabling Sanofi’s Digital Transformation through becoming an AI first organization.
This means
- 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 renown leaders and academics in machine learning to further develop your skillsets
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 AI/ML apps and implement automated model and pipeline adaption and validation working closely with data scientists and data engineers
- 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 standards, user guides, release notes, FAQs)
- Researching and gain expertise on emerging tools and technologies
- An enthusiasm to ask questions and try and learn new things is essential
ABOUT YOU
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 (MLOps)
- 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 and MLOps technologies (e.g., Python, Spark, R, Metaflow, Github, MLFlow, Argo)
- Experience in cloud and high-performance computing environments
- Experience in AWS (e.g., S3, Lambda, EC2, cloud watch) and other similar technologies (e.g., ELK stack, Snowflake, Informatica)
- Knowledge of relational databases, query authoring (SQL) and designing variety of databases (e.g., Postgres SQL, Document store)
- Nice to have knowledge of visualization technologies (e.g., RShiny, Python DASH, Tableau, PowerBI, web framework)
- Experience in development, deployment and operations of AI/ML modelling of complex datasets
- Experience in developing and maintaining APIs (e.g., REST)
- Experience specifying infrastructure and Infrastructure as a code (e.g., docker, Kubernetes, EKS, Terraform)
- Experience in cloud-based ML engineering in an industrial setting within a global organization (technology company preferred)
- Experience on working within compliance (e.g., quality, regulatory - data privacy, GxP, SOX) and cybersecurity requirements is a plus
- For more senior roles, mentoring and/or technology evangelism/advocacy experience
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.
At Sanofi, we provide equal opportunities to all regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity.
Watch our ALL IN video and check out our Diversity Equity and Inclusion actions at sanofi.com!
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.
As part of its diversity commitment, Sanofi is welcoming and integrating people with disabilities.
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