Machine Learning Engineer, BioAIM

About Sanofi:

We are an innovative global healthcare company, driven by one purpose: chasing the miracles of science to improve people’s lives. Our team, across some 100 countries, is dedicated to transforming the practice of medicine by working to turn the impossible into the possible. We provide potentially life-changing treatment options and life-saving vaccine protection to millions of people globally, while putting sustainability and social responsibility at the center of our ambitions.

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.  

In alignment to our digital transformation, we have launched a new major strategic initiative: the Biologics x AI Transformation. This is positioned to be a unique data-driven team, with expertise in AI platforms, data engineering, ML operations, data science, computational biology, strategy, and beyond. We are working as one to identify, design, and scale state-of-the-art AI capabilities targeted to truly transform how we research biologics.

Who You Are:

You are a seasoned Machine Learning 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 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 closely with Computational Scientist, MLOps and Data Scientists.

Job Highlights: 

• Work in agile pods to design and build cloud-based ML products with automated CI/CD pipelines that run, monitor, and retrain ML Models.
• Design and implement ML apps working closely with computational scientists and data engineers.
• Support the full MLOps life cycle of new and existing ML applications (e.g., new releases, change management).
• Work as ML systems architecture design subject matter expert (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.
• Research and gain expertise on emerging tools and technologies. Bring an enthusiasm to ask questions and try and learn new things is essential.
• Build and evaluate models from internal and external data sources, algorithms, simulations, using state-of-the art ML technologies.
• Work closely with computational scientists, data engineers, software engineers, UX designers, as well as research scientists in core scientific platforms focusing on protein therapeutics, in an international context (North America and Europe).
• Update and report relevant results to interdisciplinary project teams and stakeholders.

Key Functional Requirements & Qualifications:

• MS or PhD in Computer Science, Statistics, Mathematics, Information Systems, Software Engineering or another quantitative field.
• Ideally 1+ years of industry experience, new grads will also be considered.
• 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.
• 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.
• Good understanding of deployment and agile life cycle management of data science apps.
• Ability to work across the full stack and move fluidly between programming languages (e.g.: Python, SQL, Spark) and frameworks (e.g.: Airflow, MLFlow, Argo).
• Experience with high-performance computing environments.
• Experience with AWS (e.g.: S3, Lambda, SageMaker, CloudWatch, EC2, EFS, FSX).
• Knowledge of relational and non-relational databases.
• Excellent communication skills in English, both verbal and in writing, strong tropism for teamwork.

Desired Qualifications:

• Experience managing the lifecycle in a regulated environment.
• Familiarity with protein structure or sequence is a plus.
• Strong understanding of pharma R&D process is a plus.

PursueProgress. Discover Extraordinary.

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. You can be one of those people. Chasing change, embracing new ideas and exploring all the opportunities we have to offer. Let’s pursue progress. And let’s discover extraordinary together.

Visas for those who do not already have the right to work in the UK will be considered on a case by case basis according to business needs and resources.

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!

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