Deputy Director, Machine Learning


The candidate for Machine Learning will develop and immediately apply novel machine learning and computational biology-based approaches for vaccine R&D at Sanofi Pasteur. These models span every contemporary learning task: from natural language processing for sentiment analysis, to reinforcement learning tasks (delayed reward and credit assignment), to high-dimensional regression for optimum design, and structured prediction for vaccine composition. Particular focus will be towards (1) developing heterogeneous models and methods that link immunological and clinical outcomes to the biology of vaccine components, and (2) developing models to guide business behaviors and outcomes. The candidate will operate within the newly formed Design Sciences group in the FluNXT “Biotech” within Sanofi Pasteur.

S/he will have an advanced mastery and practical experience with developing and applying complex machine learning and similar modeling solutions. S/he will have had hands-on experience covering advanced algorithms, databases, networking, modeling and simulation, as well as those covering biocomputation and bioengineering informatics, as well as essential scientific programming skills (e.g. in languages such as Python/R and the like).

S/he will have an advanced mastery of numerical methods in both theory and practice for convex (at minimum) and nonconvex optimization (ideally). S/he will have an advanced understanding of common data-parallel and NUMA optimization algorithm transformation, and can evaluate state-of-the-art implementations of these for numerical stability, etc.

Critically, as this is a senior role without direct reports, the candidate will build on their existing mentoring and management experience to lead by influence, rather than by fiat; furthermore this is a “hands on” role in which the measure of impact and excellence will be through focused execution to create FluNXT vaccine designs.

S/he is expected to have a broad based scientific training in machine learning, statistics, applied math, or similar subject (PhD or Master’s degree with significant experience). Ideally s/he will leverage previously acquired industrial experience, and be ready to hit the ground running in a tight knit, fast paced environment that rewards personal initiative, collaboration, and scientific excellence.

Key Accountabilities:

Machine Learning (ML)

  • Brings unconventional ideas from idea to Proof-of-Concept (POC), especially by combining machine learning techniques with laboratory approaches, and helps drive projects through to completion or to the clinic.
  • Develops and deploys contemporary and state-of-the-art machine learning platforms (e.g. deep learning platforms like Tensorflow/MXNet and the like)
  • Develops and deploys convex optimization methods (e.g. by leveraging CVXopt and similar solvers, or by custom methods e.g. SMO-type optimization for Support Vector Machines, Frank-Wolfe methods, etc.)
  • Develops, deploys, and assesses the results of at-scale models at varying levels of model granularity for characterizing the biochemical, cellular, organ, and systems-level properties of vaccination, encompassing heterogeneous preclinical and clinical data.
  • Develops at-scale extensions of existing or novel machine learning methods (e.g. nonconvex optimization methods in deep learning, convex optimization methods for Gaussian graphical models, etc.).
  • Designs and performs computational experiments with a ‘fail fast’ spirit and considers the outlier result the most interesting result.
  • Acts as a scientific expert in ML.
  • Explores future directions of ML and keeps abreast of the latest developments.
  • Generate IP and participate in the drafting of patent  filings

Produces high-quality analyses and codebases that extend the capabilities and impact of the team as a whole

Internal and External Networking

  • Participates in relevant Project Teams and proactively maintain an open interface and communication channel with relevant areas of the company.
  • Ensures transparent and cooperative liaison with other positions around innovation and artificial intelligence/big data within the wider Sanofi Group.
  • Ensures efficient and agile communication of key information, process and workflow operational element in various circumstances.
  • Develops and maintains an international network of experts in CSB/ML, key science, technology and innovation areas, including outside the typical vaccine industry.
  • Representations and interventions at the international/community level on relevant ML matters. Presents at conferences.

Leads by Influence to mentor diverse staff in the interpretation and generation of novel vaccine candidates performance data.

Create business opportunities

  • Helps identify external business and partnership opportunities to drive the development and delivery of new vaccine-concepts to the market
  • Recognizes and stimulates internal and external unusual ideas with high potential impact; apply unique skills and interests to develop new opportunity domains

Funding applications

  • Supports, writes and/or develops grant submissions to funding agencies

This position is key for achieving the mission of the FluNXT “biotech” within Sanofi Pasteur: pioneering, testing and implementing innovative cutting edge biological science and novel ML technology solutions and concepts towards influenza and antigen design. This position will also be critical for the long-term ambition of Sanofi Pasteur R&D in the development of a comprehensive adoption of machine learning technologies across the company.

The major challenges related to the role are:

  • This is a role in a newly created group in the company.
  • The use of machine learning is new to the organization, hence will require education and might encounter resistance from in-house scientific experts (perception of threat).
  • The complexity and variety of the role: ability to switch smoothly between different scientific and operational disciplines and requirements; being able to marry deep scientific research and fast exploratory mindset with proper documentation.
  • Execute on a variety of timescales and merge results from many sub-disciplines and techniques to assess and design
  • The need to quickly transform an idea into an experiment and learn from the result to decide on the next step, which might be to kill the idea.
  • Creation of new scientific avenues or new business opportunities historically not explored by SP.
  • Tact, diplomacy, people skills, and excellent networking and communication (both oral and written) skills in general are important.

Scope of Position

This role has a core unique component: Machine Learning as a novel competency at Sanofi Pasteur for design, planning, and execution of large-scale processes (e.g. for manufacturing optimization, preclinical research programmes, and similar scope).

Interactions involve senior management to entry level employees across SP R&D and may occur globally (other Sanofi Pasteur depts., Sanofi divisions). External interactions include external partnerships which may include the US Dept. of Defense, US National Institutes of Health, as well as high tech companies like IBM, Google, and others.

There is no direct budget responsibility.



Broad based scientific and/or applied mathematical training (PhD, MD, BioEngineer, Bioinformatics, Computational Biology or Master’s degree with equivalent experience), multidisclipinary in nature with established expertise in mathematical modelling and/or machine learning.

Advanced mastery of numerical methods in both theory and practice for convex (at minimum) and nonconvex optimization (ideally).

Advanced understanding of common data-parallel and NUMA optimization algorithm transformation, and can evaluate state-of-the-art implementations of these for numerical stability, etc.

Experience with big data, cloud computing and parallel computing.  Experience with supercomputers or high-throughput computing is expected.

Strong experience in implementing ML software applications (including predictive models) and performing test verification.

Strong experience writing and deploying novel algorithms, developing and testing new models.

A strong passion for empirical research and for answering hard questions with data especially via artificial intelligence and vision of what is the next big thing.

Asymmetrical thinker who sees patterns of the big picture emerge from the parts. Creative brainstormer, skilled in divergent thinking. Ability to navigate ambiguity and interact effectively with unconventional people and ideas.

Highly flexible and adaptable individual able to thrive in a fast pace and ambiguous environment.

Ability to process multiple inputs to develop a clear understanding of a problem, issue or potential solution and translate them into practical business opportunities.

Excellent analytical and problem solving as well as communication, scientific writing and presentation skills. Ability to put together a convincing business case.

Excellent communication skills

Demonstrated ability to mentor and develop junior scientists, as well as coaching peers.

Ability to influence without a direct reporting relationship.

Knowledge of at least Word, Excel, PowerPoint, Outlook, and various ML domain specific tools.

Understanding of drug/vaccine discovery and development processes is a plus, as well as familiarity with large, real world (biomedical) data sets

Desire to make a dent in the universe with the FluNXT team.


Sanofi is dedicated to supporting people through their health challenges. We are a global biopharmaceutical company focused on human health. We prevent illness with vaccines, provide innovative treatments to fight pain and ease suffering. We stand by the few who suffer from rare diseases and the millions with long-term chronic conditions.

With more than 100,000 people in 100 countries, Sanofi is transforming scientific innovation into healthcare solutions around the globe.

Sanofi, Empowering Life

Read Full DescriptionHide Full Description
Confirmed 13 hours ago. Posted 30+ days ago.

Discover Similar Jobs

Suggested Articles