Engineering Director

Coders Connect are partnering with Sanofi.

The role is hybrid remote 2-3 days onsite per week.

**Who are Sanofi?**

Sanofi is a global bio-pharmaceutical company focused on human health. Their purpose is to find treatments to fight pain and ease suffering. They combine breakthrough science and advanced technology to develop life-changing medicines and vaccines.

**Our vision for digital, data analytics and AI**:
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. This has enabled us, to accelerate R&D, improve manufacturing and commercial performance, and bring novel drugs and vaccines to patients faster.

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.- Leading Edge Tech Stack.
- World Class Mentorship and Training

Who are you? You are a dynamic Engineering Director 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 a 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 are currently leading a team and are keen on taking the challenge of building a high performing team. 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. Join us on our journey in enabling Sanofi’s Digital Transformation through becoming an AI first organization. Main Responsibilities Hire and Build a high performing MLOps team Lead Sanofi’s ML development standards and best practices. Collaborate with others in engineering and product leadership to create and Own the long-term roadmap and deliverables for your team Develop assets, accelerators, and thought capital for your practice by Providing best in class framework and reusable components. Work in agile pods to design and build cloud hosted, ML products with automated pipelines that run, monitor, and retrain ML Models. Oversee the design of AI/ML apps and the implementation of automated model and pipeline adaption. Lead development end-to-end (Data/Dev/ML)Ops pipelines based on in-depth understanding of cloud platforms, AI lifecycle, and business problems to ensure analytics solutions are delivered efficiently, predictably, and sustainably. Support life cycle management of deployed ML apps (e.g., new releases, change management, monitoring and troubleshooting) Maintain effective relationships with stakeholders to develop education and communication content as per life cycle events Co-Own project planning and execution of multiple features and releases Contribute to architecture, design, and code reviews. Also not be afraid to do some hands-on development/debugging to solve complex use cases Minimum 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, DataBricks, Github, MLFlow, Airflow) Experience in AWS cloud (e.g.: S3, Lambda, EC2, cloud watch) and other technologies (Infra as Code : Kubernetes, Docker, terraform Storage/Caching: S3, Snowflake, DocumentDB, Redis...) plus high-performance computing environments Experience with visualization technologies (e.g.: RShiny, Python DASH, Tableau, PowerBI) Experience in development, deployment and operations of AI/ML modelling of complex datasets Experience in developing and maintaining APIs (e.g.: REST, API gateway) 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 Mentoring and/or technology evangelism/advocacy experience