Software / DevOps Engineer

 Job description 

About Aqemia 

Aqemia’s ambition is to discover better and more innovative therapeutic molecules faster. Better molecules because our physics-based technology has unparalleled precision. More innovative molecules because we don’t rely on past data, we’re not stuck to staying close to what already exists. Faster because our precision implies less experiments. 

Aqemia leverages a unique technology based on 8 years of research in quantum and  statistical mechanics at Oxford (UK), Cambridge (UK) and École normale supérieure (Paris). Our algorithms are able to compute the affinity between molecules as precisely as experiment and 10 000x faster than competition. This technology guides our AI towards the molecule that has maximum affinity for the therapeutic target yet validates other biological and physico-chemical properties.

 

We’re looking for a Software / DevOps engineer to join our core team and make an impact on a critical challenge: discovering drug candidates to cure key diseases. You will work in an interdisciplinary team of drug hunters, physicists, chemists and ML engineers.

Founded in June 2019, we have raised €1.6M with leading VC fund Elaia Partners and Bpifrance.

If this sounds exciting to you, come and join us! 
 

Job description

As a Software / DevOps engineer, you will collaborate with ML researchers and engineers to develop and accelerate experiments exploring new applications of AI and Statistical Mechanics to Drug Discovery. 

 

Your day-to-day responsibilities:

  • Architect, manage the software and compute infrastructure

  • Implement tools, libraries and frameworks to speed up research and development

  • Enforce software engineering best practices and mentor the research teams

  • Design cloud infrastructure to serve millions of physics-based calculations and ML predictions

  • Write continuous integration and delivery tools to build new Docker containers, deploy updated models, and distribute code in response to Git hooks or other web events

  • Connect Docker-based microservices and serverless scripts to enable automated dataset ingestion pipelines that speed up the pace of model development and serving

  • Architect and build cloud-based data lakes along with data APIs to power machine learning models, visualization tools, and chemistry software

  • Optimise codebases to speed-up the screening runtime

  • Implement security policies across Aqemia’s software infrastructure

Preferred experience

Your profile:

  • Bachelor’s or Master’s degree in computer science (or equivalent experience)

  • Experience in using Docker and Kubernetes to containerize and launch microservices. ML-specific experience not required

  • Experience and appetite for building production systems in Python, especially in a microservices or serverless environment

  • Strong expertise with either AWS or GCP, including maintaining a VPC, writing build tools, tests and CI workflows and enforcing best practices for authorization and authentication

 

Nice to have:

  • Basic knowledge in physics, biology, chemistry or machine learning

  • Experience using TensorFlow, Jax, NumPy, Pandas or similar ML/scientific libraries

 

You should join us if…

  • You are passionate about solving difficult problems on topics that really matter

  • You are curious, willingful and dynamic

  • You want to grow and help others grow as well

  • You like working collaboratively in an interdisciplinary, fast-paced environment

  • You believe in silico/AI can have strong impact on how to find new drugs

  • You want to join a small team to bring your own impact in drug discovery

 

To apply, send us your CV:

maximilien.levesque@aqemia.com or emmanuelle.martiano@aqemia.com

Aqemia is growing fast. You do not fit in this job description but are excited by this adventure? 

© 2020 Aqemia

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Agoranov, 96 bis Bd Raspail, 75006 Paris