En cliquant sur "Accepter", vous acceptez le stockage de cookies sur votre appareil pour améliorer la navigation sur le site, analyser l'utilisation du site et contribuer à nos efforts de marketing. Consultez notre politique de confidentialité pour plus d'informations.
Flèche permettant d'actionner le carrousel
Retour

Machine Learning Engineer in Genomics (H/F)

Lieu : 
Paris
Type : 
Hybride
Salaire : 
40k€-85k€
TJM : 
Machine Learning
Python
AI
Fullstack

CLIENT

Our partner company is a trailblazing force in the realm of artificial intelligence, continuously pushing the boundaries of innovation.

With strategically positioned offices in major global hubs, they engage in collaborations with industry behemoths like Google, alongside esteemed educational institutions.

In a testament to their prowess, our partner has secured a prominent position among notable AI players, fast-rising enterprises, and Europe's top 1000 fastest-growing businesses in 2022.

Their recent acquisition by a prominent biotechnology leader has further cemented their commitment to pioneering the industry.

Currently, we are actively seeking talented Machine Learning Software Engineers - (Protein Folding ) (M/F) to fortify their dynamic team.

PROJECT

In your role as a Machine Learning Engineer on our Genomics team, you will be instrumental in propelling our efforts to advance genomics research.

Your focus will be on the creation of innovative AI and deep learning solutions, specifically tailored for DNA analysis.

Your responsibilities will include significant contributions to our proprietary machine learning codebases and libraries. Your primary duties will involve the design, development, and refinement of deep learning models, particularly language models, with an emphasis on improving accuracy, efficiency, and scalability in processing extensive sequence datasets.

Your daily work will involve close collaboration with experienced computational geneticists who are dedicated to helping you fully grasp the project requirements.

Your task will be to investigate potential solutions and implement the necessary strategies to achieve enhanced and innovative computational performance.

In this process, your role will also encompass the development of effective, modular, and sustainable software solutions, as well as regular interactions with our team of AI researchers.

ROLE RESPONSIBILITIES/ACCOUNTABILITIES

  • Enhance Our Machine Learning Libraries: Take an active role in enhancing our proprietary Machine Learning libraries.
  • Application of Algorithms in Genomics Research: Employ algorithms and research methodologies on language models and deep learning techniques for genomics applications.
  • Advocate for Excellence in Engineering: Promote and support the use of best engineering practices in converting research into code that is both reusable and maintainable.
  • Optimize Algorithms for Contemporary Hardware: Design and implement algorithms tailored for today's hardware and distributed computing environments, including CPUs, GPUs, TPUs, and cloud-based systems.
  • Clear and Effective Communication: Articulate experimental outcomes and research insights effectively, both within the organization and to external stakeholders, through written and oral communication.
  • Team Collaboration: Work in close partnership with diverse teams, comprising computational geneticists and AI experts, to seamlessly incorporate AI advancements into genomics research processes.
  • Stay Informed on AI and Genomics Developments: Remain updated with the latest trends and developments in AI and genomics, contributing to scientific literature and exploring new methods to tackle genomics challenges.
  • Establish Comprehensive Performance Metrics: Develop and maintain robust benchmarks for evaluating the performance of AI models, continuously improving these models based on feedback.
  • Detailed Documentation: Meticulously document your work for clarity and replicability, sharing knowledge internally to benefit the entire team.


PROFIL & REQUIREMENTS:

  • A higher degree in Computer Science, Machine Learning, or a related scientific discipline.
  • Demonstrated expertise in deep learning, neural networks, and AI model development, with a special focus on language models, especially transformers.
  • Proficiency in programming languages like Python and familiarity with libraries such as TensorFlow, PyTorch, or Jax.
  • While specific knowledge in genomics is not a prerequisite, a keen interest in genomics data, tools, and databases is greatly beneficial.
  • Excellent problem-solving abilities and a creative approach to tackling intricate challenges in genomics research.
  • Strong communication skills, enabling effective collaboration in multidisciplinary teams.
  • A history of publications in AI, deep learning, or genomics research is a notable advantage

PROCESS - 3 to 5 weeks

  • 1st screen / initial discussion with the tech recruiter department over video
  • A programming test / technical hacker rank test + Review of the test
  • Take Home assignment + review call with the candidate
  • Call with a head of department

MODALITIES

  • Type of contract: CDI
  • Salary range: From 40k€ to 85k€
  • English MANDATORY
  • Permanent contract with the end client
  • Remote: 2-3 jours / semaine
  • Localisation: PARIS 

Postulez directement au poste de

Machine Learning Engineer in Genomics (H/F)

Nous vous recontacterons rapidement !
Format PDF - Taille max : 10MO
Téléchargement en cours
fileuploaded.jpg
Le téléchargement a échoué. La taille maximale des fichiers est de 10 Mo.
Merci !
Nous avons bien reçu votre message et nous vous répondrons dans les plus brefs délais !
Oops! Une erreur s'est produite lors de l'envoi du formulaire.
N'hésitez pas à nous appeler directement !