Applied Research Scientist > Bioptimus > Joboolo FR :

We are an AI-driven startup pioneering the development of a universal foundation model for biology.


Our mission is to revolutionise biological research and innovation through cutting-edge technology.


As a Machine Learning Engineer at Bioptimus, you will have the opportunity to improve medical research using state-of-the-art machine learning algorithms.


You will work with interdisciplinary teams with both machine learning and biomedical expertise to build foundation models of biology that will unlock AI applications in biomedical innovation.

As an expert Applied Scientist in computational biology and pharma R&D, you will:

• Bridge Research & Product:
  
  
  Understand the most valuable biopharma use-cases.
  
  
  Translate biopharma research questions into actionable machine learning objectives & tasks.
  
  
  Engage closely with product, business and research teams to define feature priorities.


• Enable Pre-Sales & Technical Sales:
  
  
  Serve as a trusted scientific partner during technical sales discussions—design proof-of-concept studies, address domain-specific queries, and deliver persuasive presentations that highlight the value of Bioptimus’ solutions.


• Client Education & Engagement:
  
  
  Provide ongoing training and support to clients on how to interpret and effectively apply our foundation models in their R&D pipelines.
  
  
  Help them unlock actionable insights in proteomics, transcriptomics histology data and beyond.


• Thought Leadership:
  
  
  Represent Bioptimus at conferences, workshops, and in client meetings, demonstrating domain expertise and the potential of AI-driven drug development.


• Research & Innovation:
  
  
  Collaborate with our research team to identify new AI and foundation model approaches that can be integrated into the product.
  
  
  Contribute to publications, patents, and case studies showcasing novel applications in pharma R&D.

The successful candidate will have a ‘team-first’ kind of attitude; be independent, curious, and detail-oriented; thrive in a dynamic, fast-paced environment; and be fun to work with.


We value individuals who bring deep domain expertise in pharma R&D alongside strong computational, hands-on skills.

• Pharma R&D Expertise:
  
  
  Deep understanding of biopharma R&D use-cases, challenges, tools and processes (target discovery, preclinical studies, clinical trial design, biomarker discovery, diagnostics, regulatory considerations etc.).
  
  
  Ability to break down high-level biopharma use-cases into actionable recommendations for the research & product team (ex:
  
  
  specific loss function, evaluation metrics, data annotations etc.).


• Computational Biology:
  
  
  Extensive experience working with genomics, proteomics, single-cell or histology data, encompassing the entire analysis pipeline, from dataset generation and curation based on raw measurements with the appropriate bioinformatics tools, to the application of machine learning models to assess scientific hypotheses and drive novel discoveries.
  
  
  Demonstrated expertise applying machine learning to computational biology, including scientific publications at high-impact journals (Nature, Science, Cell, Nucleic Acids Research, Genome Biology, …) and/or top conferences in the field (ISMB, RECOMB, NeurIPS, ICLR, ICML, …).
  
  
  Mastery of the different evaluation protocols and metrics used in the literature.


• Exceptional Communication Skills:
  
  
  Capable of engaging both technical and non-technical stakeholders.
  
  
  Adept at crafting compelling presentations and scientific narratives for high-level stakeholders and internal teams.


• Educational Background:
  
  
  PhD or equivalent experience in Computational Biology, Bioinformatics, Pharmacology, or related field.

• Deep Domain Knowledge:
  
  
  Having extensive experience in applying AI models in pharma or biotech settings, including clinical or translational research.


• Publications & Thought Leadership:
  
  
  A track record of publishing impactful scientific papers or speaking at conferences on computational biology, foundation models, or drug discovery.


• Project Leadership Experience:
  
  
  Demonstrated ability to facilitate & manage complex projects, and deliver results in a fast-paced environment.


• Entrepreneurial Mindset:
  
  
  Experience in a startup or innovative environment, showing adaptability, proactiveness, and eagerness to take on varied responsibilities.


• Client-Centric Approach:
  
  
  Proven success in supporting sales or consulting activities, shaping product offerings, and ensuring client satisfaction through ongoing relationship management.

What We Offer

• Competitive compensation


• The opportunity to shape the foundational IT and cloud infrastructure of a high-growth AI company


• A direct and significant impact on our technical capabilities, scalability, and success.


• A collaborative, mission-driven culture with a passionate team of innovators.


• Flexible work environment with a focus on outcomes, not hours.


• The chance to make a tangible impact at the intersection of AI and biology, driving real-world change.