What You Will Do

At Doctolib, we're revolutionizing healthcare delivery through advanced AI systems focused on medical reasoning. As a Senior Staff Research Scientist, you'll develop cutting-edge AI solutions that enhance clinical decision-making and support healthcare professionals in their daily practice. You'll work at the intersection of machine learning and healthcare, creating models that can understand medical knowledge, reason through complex clinical scenarios, and assist medical practitioners in providing better care.

Your responsibilities include (but are not limited to):

• Solve Real-World Healthcare Challenges: Design and build advanced machine learning models, especially in NLP and large language models, to improve healthcare workflows, enhance patient experiences, and power intelligent health solutions at scale.
• Innovate & Experiment: Research and prototype novel algorithms and architectures, staying at the forefront of AI/ML developments. Bring new ideas from concept to working prototypes, leveraging the latest advances in deep learning and generative AI.
• Collaborate Across Teams: Work closely with product, engineering, medical experts, and other stakeholders to translate business needs into impactful research projects. Communicate technical concepts and results clearly to both technical and non-technical audiences.
• Drive Impact: Analyze large, complex data sets to extract actionable insights, define key metrics, and rigorously evaluate model performance.
• Share & Learn: Advance Doctolib’s AI expertise by sharing findings within the team and with the wider ML community through publications, talks, and workshops. Mentor and support other scientists and engineers in adopting best practices.

Who You Are

• Technical Expertise:
• PhD or Master’s degree (plus significant experience) in Computer Science, Machine Learning, Mathematics, or a related field; Publications as first author in top-tier AI/ML conferences such as NeurIPS, ICLR, ICML, ACL, EMNLP, or relevant medical informatics venues are a plus;
• Deep understanding of machine learning and deep learning concepts, with hands-on experience in NLP, LLMs, or generative AI.
• Strong programming skills in Python (and ideally experience with ML frameworks such as PyTorch or JAX).
• Familiarity with modern data tools and scalable training on large datasets.
• Innovator & Problem Solver:
• Track record of independently driving research and translating it into real-world applications.
• Experience designing experiments, evaluating intrinsic and extrinsic metrics, and iterating quickly.
• Curiosity and drive to learn, research, and apply new machine learning techniques.
  
  
• Collaborative & Communicative:
• Comfortable working in highly cross-functional teams, with the ability to clearly communicate complex concepts to diverse audiences.
• Passionate about sharing knowledge and contributing to a culture of learning and innovation.
  
  
• Mission-Driven:
• Motivated by Doctolib’s mission to make healthcare better for all. Eager to solve meaningful problems with technology.
• Detail-oriented, rigorous, and committed to delivering high-quality, production-ready solutions.

What we offer 

• Free comprehensive health insurance for you and your children

• 25 days of paid vacation per year, plus up to 14 days of RTT

• Free mental health and coaching services through our partner Moka.care

• Work from abroad for up to 10 days per year thanks to our flexibility days policy

• Lunch vouchers (Swile card) worth €8.50 per working day, with €4.50 covered by Doctolib

• A subsidy from the work council to refund part of the membership to a sport club or a creative class

• 50% reimbursement of your public transport subscription

• Parent Care Program: receive one additional month of leave on top of the legal parental leave

• For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support

• Relocation support in case of international mobility

• Access to the best AI tools for coding, development and dedicated training

 The interview process  

• HR Screen 
• Call with Research Team Member 30 mins
• Scientific Presentation + Case Study 1 hour 30mins
• Behavioral Interview 1 hour 15mins
• At least one Reference check 

 Job details 

• Permanent position 
• Full Time
• Location: Doctolib Paris office in Levallois Perret
• Work mode: Hybrid (3 days/week in the office)
• Start date: ASAP

If you would like to find out more about tech life at Doctolib, feel free to read our latest Medium blog articles!

At Doctolib, we are committed to improving access to healthcare for everyone. This translates into our recruitment process. We evaluate candidates based solely on qualifications and motivation, without any form of discrimination.

The more diverse ideas are heard, the more our product will truly improve healthcare for all. You are welcome to apply to Doctolib, regardless of your gender, religion, age, sexual orientation, ethnicity, disability.

To ensure equal opportunities, we invite you to exclude personal information (e.g. pictures, age) from your applications. If you require any accommodation, please let us know for support during the hiring process.

Join us in building the healthcare we all dream of!

All information provided is processed by Doctolib for application management. For data processing details, click here. Please contact hr.dataprivacy(at)doctolib.com for inquiries or to exercise your rights.

The Opportunity

We are looking for a meticulous and detail-oriented Biology Data Quality Engineer to ensure the integrity and usability of the various and complex datasets that are central to our mission. In this critical role, you'll leverage your expertise in biology, data science, and machine learning to ensure the quality and consistency of biological data used to train and evaluate our foundation models. You'll work in collaboration with the R&D team and our engineers, using your skills to ensure our data meets the highest standards.

What You'll Be Doing

As a Biology Data Quality Engineer, you will own the following tasks:

• Data Validation Pipeline Development: Develop and implement comprehensive data validation protocols for diverse biological datasets (histology, omics, clinical). Ensure data integrity, consistency, and accuracy through rigorous quality checks. Design and implement automated data quality pipelines to streamline data validation and identify potential issues early in the data processing workflow.
• Data Curation & Standardization: Establish and enforce data standardization practices to facilitate seamless integration and analysis across different data types. Curate datasets to enhance their usability for machine learning.
• Collaboration & Communication: Work closely with the R&D team to understand data requirements and address data quality concerns. Communicate data quality findings and recommendations effectively to technical and non-technical stakeholders. Communicate and synchronize with external data providers.
• Documentation & Reporting: Maintain a detailed documentation of the data-quality assessment procedures, validation results, and data specifications. Generate regular reports on data quality metrics and trends.
• Data Source Evaluation: Evaluate and validate external public data sources, ensuring they meet our quality standards and are suitable for inclusion in our foundation model training.
• Continuous Improvement: Stay up-to-date with the latest data quality best practices and tools in the biological domain. Propose and implement improvements to our data- quality assessment processes and pipelines.

What You'll Bring

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 strong domain expertise in biology alongside strong computational, hands-on skills.

• Omics Data Expertise. Deep understanding of transcriptomics data types (bulk, single-cell, spatial) and their specific quality considerations. Good knowledge of genomics and proteomics data.
• Data Quality Management: Proven experience in implementing data quality control procedures and pipelines. Familiarity with data validation tools and techniques.
• Analytical Skills: Strong analytical and problem-solving skills to identify and resolve data quality issues.
• Programming & Data Analysis: Proficiency in Python, good knowledge of data visualization libraries (e.g. matplotlib).
• Communication Skills: Excellent written and verbal communication skills to effectively convey data quality findings and recommendations.
• Educational Background: MSc in Biology, Computational Biology, Bioinformatics.

How to Stand Out:

• Computational Pathology Data Expertise: Experience in machine learning analysis of histology images.
• Cloud expertise: Experience working with AWS.
• Data Annotation Experience: Experience with developing and implementing data annotation guidelines and processes. Experience with data ontologies.
• Proven experience building or contributing to large-scale data collections (e.g. Human Cell Atlas).
• Spatial alignment of multimodal datasets (e.g. alignment between different imaging modalities)

The Candidate Journey

To be considered, please submit your CV in English. We believe in a transparent and collaborative interview process. Here is what you can expect after submitting your application:

1. Screening: Once you have applied, the hiring team will review your application to determine if your work experience and skills align with the necessary proficiencies of this position.
2. Technical Assessment: Given the technical nature of the role, you will be expected to complete a short set of Python exercises in a dedicated platform to assess your proficiency.
3. Interviews:
   • Data Curation Project: The hiring team will have an introductory call with you to share expectations for the role and to provide you with a Data Curation assignment. This assignment covers one or more key data modalities and consists of the submission of Python code and a detailed report about your work. You will get to present your work to the team, and have an interview to explore your knowledge on data modalities and relevant technical artefacts.
   • Team Fit: The hiring team will have a call with you to discuss your motivations, expectations for the role, and an overall Q&A based on your CV and previous experiences.
4. Offer: Following the completion of the interviews, our hiring team will make a final decision and will be in touch to share the outcome of your interviews. If the team would like to move forward, the recruiter will discuss the details of our proposed offer with you.
5. Onboarding: We are happy to have you joining the team. Once you have accepted and signed your offer, we will be in touch to begin the process of onboarding you to Bioptimus.

Why This is a Unique Opportunity

• Be part of a trailblazing team working at the intersection of AI, biotech, and biomedical research.
• Take on a high-impact leadership role, shaping the future of biomedical AI through strategic data partnerships.
• Work in a collaborative, innovation-driven environment with top researchers and industry experts.
  
  

Locations:

• Europe: Paris / UK / Germany / Remote (EU)

About the role

We are looking for a scientifically credentialed strategist to lead the post-sales journey for our pharmaceutical partners. In this role, you will be the bridge between our cutting-edge foundational models and the R&D pipelines of the world’s leading biopharma companies.

You will use your deep expertise in machine learning and computational biology to build credibility with stakeholders, identify new opportunities for model application within their pipelines, and translate customer feedback into our product roadmap.

What you'll be doing

As our Applied AI Scientist (Pharma Partnerships) you are the primary architect of value for our most critical pharmaceutical partnerships. You will operate at the intersection of computational biology, ML and commercial scale across two strategic domains:

1. Partnership Value Realisation & Growth

• Post-Signature Leadership: Orchestrate the partner journey immediately following contract execution. You will act as the Project Manager for the deployment, ensuring seamless onboarding and integration of our foundational models.
• Scientific & technical thought-leadership: Consult with client R&D teams (ranging from bench scientists and data science teams to Heads of R&D) to diagnose their specific therapeutic challenges. Identify key use cases where our AI foundation models can unlock high value to our customers research and therapeutic priorities.
• Commercial Adoption & Growth: Proactively identify opportunities to expand the scope of the partnership. Leverage your understanding of the client’s pipeline to suggest new use cases, therapeutic areas, or departments where our technology can drive value.

2. Product Intelligence & Roadmap Influence

• Voice of the Customer: Synthesize technical feedback and performance metrics from the field. Translate complex biopharma user requirements into actionable technical specifications for our internal Research and Product teams. Identify high value opportunities to enrich our model capabilities and biology applications offering.
• Gap Analysis: Collaborate with our machine learning engineers to identify data modalities or functional gaps in our current offering, directly influencing future product iterations.

What you'll bring

The successful candidate will have a ‘team-first’ 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 computational biology, ML and pharmaceutical R&D alongside strong hands-on business development skills.

Scientific & Technical Credibility

• Educational Background: PhD in Computational Biology, Machine Learning, Bioinformatics, Genomics, or a related field is required.
• Domain Expertise: Deep understanding of the biopharma R&D value chain (target discovery to clinical trials). You understand the specific pain points of drug developers and are able to translate ambiguous biopharma use cases into rigorous ML applications.
• Technical Fluency:
• Deep experience in biological data modalities, notably multi-omics (single-cell, transcriptomics, proteomics) and histopathology slides.
• Extensive knowledge in modern ML architectures and paradigms like Transformers (ViT), GNNs, foundation models with embedding-based prediction heads (e.g., ABMIL), interpretability methods, and model evaluation & validation principles.
• Proven experience in designing end-to-end ML solutions for complex biological problems, including problem framing, data strategy and model design & evaluation
• Strong fluency in Python and deep learning frameworks (PyTorch, JAX)

Relationship & Strategic Skills

• Stakeholder Management: Proven experience navigating complex, matrixed organizations (Big Pharma experience is a plus). You can present to a VP of R&D in the morning and troubleshoot with a bioinformatician in the afternoon.
• Consulting Mindset: You are not just a support agent; you are a trusted advisor. You have experience in roles such as Field Application Scientist (FAS), Solution Architecture, or Scientific Consulting.
• Feedback Synthesis: Ability to distill complex client complaints or requests into clear, prioritized product requirements.

How to stand out:

• Experience in a startup or innovative environment, showing adaptability and proactiveness.
• A strong existing network within Global Top 20 Pharma R&D.
• Experience specifically with "Foundation Models" or Generative AI in a biological context.
• Track record of high-impact publications (Nature, Cell, NeurIPS).

The candidate journey

To be considered, please submit your CV in English.

We believe in a transparent and collaborative interview process. We need to find a fit for both you and the company. Here is what you can expect after submitting your application:

• Screening: Once you have applied, the hiring team will review your application. If your experience and skills align with the role, you will be invited to a 30-minute introductory call with the Hiring Manager to discuss your background, motivations, and the position in more detail.
• Interviews: Following a successful screening, you will be invited to a series of interviews:
  • Case Study (60 min): You will prepare a mock kick-off document for a client engagement with us to evaluate the model on their desired use-cases, including suggesting interesting use cases for our model and outlining the project plan. We want to see how well you understand the potential use cases for foundation models in the clinical stage of pharma development cycles, and how you would manage a key strategic partner through the deployment and delivery process.
  • Scientific Deep Dive Presentation (30 min): You will briefly present a piece of scientific work to a small panel of our researchers and engineers, led by a senior member of our technical team, and answer Q&S after (10-15 min presentation, 15-20 min Q&A). The content is up to you: it can be your own past research, a relevant paper in the field, or extra points if it’s a specific Bio-AI use case you’ve worked on with a biopharma. The goal is to assess your technical fluency, your ability to facilitate scientific debate, and how you communicate complex concepts to experts.
  • Executive Interview (30 min): A comprehensive discussion with member(s) of our Senior Leadership. This session moves beyond technical competency to focus on long-term vision, values, and mutual potential. This is an opportunity for you to get to know the company better as well.
• Offer: Following the completion of all interviews, our hiring team will make a final decision and will be in touch to share the outcome. Please note that an offer is contingent upon the successful completion of a reference check.
• Onboarding: We are happy to have you joining the team! Once you have accepted and signed your offer, we will be in touch to begin the process of onboarding you.

Why this is a unique opportunity

• A collaborative and mission-driven work environment.
• Competitive salary and equity package.
• Flexible work arrangements, including remote options.
• Opportunities for professional growth and leadership development.
• Shape the future of biology and AI by contributing to groundbreaking work.

Job Title: Infusion Registered Nurse

About Us

At West Cancer Center, we are dedicated to providing compassionate, patient-centered care while advancing groundbreaking research. Our team fosters collaboration, innovation, and professional growth, ensuring that every role contributes to making a difference in patients’ lives. Join us in our mission to provide comprehensive support to those navigating the challenges of cancer treatment.

Position Overview

As an Infusion RN, you will be responsible for providing safe, effective, and comprehensive infusion services, including chemotherapy administration. This role includes conducting patient assessments, educating patients and caregivers, managing venous access devices, and ensuring seamless coordination of care. Infusion RNs are vital members of our interdisciplinary team, working to enhance patient outcomes and satisfaction. 

Key Responsibilities

• Conduct comprehensive assessments of patients’ physical, psychological, and social needs
• Facilitate seamless patient flow to ensure efficient outpatient care delivery
• Administer chemotherapy and other infusion therapies safely and effectively
• Maintain competency in managing peripheral and central venous access devices
• Educate patients and caregivers on treatment plans, medications, and procedures
• Ensure compliance with infection control, medication safety, and emergency protocols
• Accurately document and monitor patient data and treatment outcomes
• Participate in clinical research trials (as applicable, after 6 months of employment)
• Conduct telephone follow-ups within the RN scope of practice
• Perform other duties as assigned

Qualifications

Education & Experience

• Required:
• Graduate from an accredited nursing program
• Minimum of one (1) year of experience in a medical, surgical, or clinical setting
• Current RN license in the state of employment or compact license
• Basic Life Support (BLS) certification through American Heart Association.
• Preferred:
• Bachelor’s degree in Nursing
• Experience in outpatient nursing and infusion therapy

Skills & Abilities

• Strong verbal and written communication skills
• Proficiency in healthcare documentation and patient tracking systems
• Knowledge of healthcare resources and navigation practices
• Excellent problem-solving and conflict-resolution abilities
• Team-oriented mindset with commitment to exceptional patient care and service
• Displays compassion, professionalism, and cultural sensitivity

Why West Cancer Center is a Great Place to Work

• Meaningful Impact: Play a direct role in supporting patients through one of the most challenging times of their lives.
• Collaborative Culture: Work alongside a multidisciplinary team of dedicated professionals committed to improving cancer care.
• Professional Development: Benefit from ongoing training, educational resources, and growth opportunities.
• Mission-Driven Environment: Be part of an organization guided by compassion, integrity, and innovation.

No nights, weekends, or holidays. Comprehensive benefits package.

Join Us

Join our team and be part of our mission to provide outstanding infusion care. If you are a compassionate RN passionate about making a difference in cancer care, apply now to join West Cancer Center as an Infusion RN.

What you’ll do

We are looking for a Senior Staff Machine Learning Engineer to join the Clinical team in the AI and Machine Learning Department. You'll lead the technical direction of AI systems that enhance clinical decision-making and patient care. You'll tackle the hardest problems in healthcare AI, from building voice-powered consultation assistants to establishing LLM evaluation frameworks that ensure clinical safety and efficacy. This role combines deep R&D with strategic technical leadership, shaping how Doctolib deploys AI in regulated healthcare environments.

Your responsibilities include but are not limited to:

Technical Strategy & Architecture

• Own the long-term technical roadmap for clinical ML systems, from model architecture selection to production deployment patterns
• Drive strategic build vs. buy decisions, balancing custom development with foundation model APIs
• Define standards for safe rollout in healthcare contexts: shadow testing, staged deployment, and human-in-the-loop workflows

End-to-End ML Delivery

• Lead design and implementation of LLM-powered clinical agents (consultation summarization, clinical coding, evidence-grounded recommendations)
• Establish rigorous evaluation frameworks using real-world clinical datasets, ensuring outputs meet clinical accuracy and safety standards
• Build production infrastructure: model and prompt versioning, guardrails, uncertainty quantification, cost optimization, and observability
• Define a bold strategy for online and offline performance objectives to reach new levels of healthcare professionals satisfaction

Leadership & Impact

• Mentor Staff or Senior ML Engineers and Applied Scientists, elevating technical standards across the organization
• Lead cross-functional initiatives spanning Product, Medical Affairs, Legal, and Compliance teams
• Translate clinical needs into research questions and production systems that measurably improve patient outcomes
• Partner with our medical, legal, and compliance teams to meet EU regulatory expectations (e.g., GDPR, MDR, upcoming EU AI Act) and market standards.

Who you are

Before you read on,  if you don't have the exact profile described below, but you feel this job description matches your skill set, we still encourage you to apply.

• You have 10+ years in ML/AI with 3+ years at Staff+ or Principal level leading complex, multi-team technical initiatives
• You have a PhD in Computer Science, AI, Statistics, or related field (or equivalent research experience)
• You have deep expertise in at least two of: clinical NLP, LLM fine-tuning and evaluation, automatic speech recognition, RAG systems, or reinforcement learning
• You are expert in Python, PyTorch/Transformers for training, vLLM/similar for inference with a track record deploying ML systems in production (AWS/GCP)
• You have exceptional communication skills and are able to align diverse stakeholders and explain complex technical decisions

Now it would be fantastic if you have:

• Publications in top-tier ML/AI conferences (NeurIPS, ICLR, ACL) or medical informatics venues
• Experience with EU healthcare regulations (GDPR, MDR, AI Act)
• Prior work with clinical data or healthcare applications

What we offer

• Free comprehensive health insurance for you and your children
• Parent Care Program: receive one additional month of leave on top of the legal parental leave
• Free mental health and coaching services through our partner Moka.care
• For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support
• Work from abroad for up to 10 days per year thanks to our flexibility days policy
• Work Council subsidy to refund part of sport club membership or creative class
• Up to 14 days of RTT
• A subsidy from the work council to refund part of the membership to a sport club or a creative class
• Lunch voucher with Swile card

The interview process

• HR Screen
• Hiring Manager Interview
• Behavioral Interview
• Technical Questions 
• Technical Case Study
• At least one reference check

Job details

• Permanent position
• Full-time
• Hybrid work mode (3 days/week in the office)
• Paris, France
• Start date: as soon as possible

If you would like to find out more about tech life at Doctolib, feel free to read our latest Medium blog articles!

At Doctolib, we are committed to improving access to healthcare for everyone. This translates into our recruitment process. We evaluate candidates based solely on qualifications and motivation, without any form of discrimination.

The more diverse ideas are heard, the more our product will truly improve healthcare for all. You are welcome to apply to Doctolib, regardless of your gender, religion, age, sexual orientation, ethnicity, disability.

To ensure equal opportunities, we invite you to exclude personal information (e.g. pictures, age) from your applications. If you require any accommodation, please let us know for support during the hiring process.

Join us in building the healthcare we all dream of!

All information provided is processed by Doctolib for application management. For data processing details, click here.

Please contact hr.dataprivacy(at)doctolib.com for inquiries or to exercise your rights.

What you’ll do 

At Doctolib, we're on a mission to transform how healthcare is delivered by harnessing the power of AI.

As a Senior/Staff Machine Learning Engineer, you’ll play a key role in designing, implementing, and scaling the evaluation framework that ensures our AI Health Companion behaves safely, reliably, and helpfully for millions of patients and practitioners.

You’ll join a cross-functional team of Machine Learning Engineers, Product Engineers, and Medical Experts to build robust evaluation pipelines for agentic AI systems — models capable of reasoning, planning, and interacting with complex healthcare data.

Your responsibilities include, but are not limited to:

• Define and own the evaluation strategy for our AI agentic system - metrics, protocols, datasets, and tooling
• Implement and maintain automated evaluation pipelines to monitor model quality, safety, and alignment across iterations
• Run systematic experiments to assess reasoning, factuality, robustness, and user experience
• Collaborate closely with model developers and research scientists to provide insights and drive iterative improvement
• Contribute to research and internal knowledge sharing on LLM evaluation methodologies and best practices

About our tech environment

• Our solutions are built on a single fully cloud-native platform that supports web and mobile app interfaces, multiple languages, and is adapted to the country and healthcare specialty requirements. To address these challenges, we are modularizing our platform run in a distributed architecture through reusable components 
• Our stack is composed of Rails, TypeScript, Java, Python, Kotlin, Swift, and React Native
• We leverage AI ethically across our products to empower patients and health professionals. Discover our AI vision here!

 Who you are 

Before you read on — if you don't have the exact profile described below, but you feel this job description matches your skill set, we still encourage you to apply.

• MSc or PhD in Computer Science, Machine Learning, Data Science, or related field
• 7+ years of hands-on experience working with large language models (e.g., GPT, Claude, Llama, or BERT-like architectures)
• Proven experience in evaluating agentic or reasoning systems (e.g., autonomous agents, tool-using LLMs, dialogue systems, or task-oriented assistants)
• Strong track record in experiment design, metric definition, and evaluation automation
• Ability to bridge research and production, influencing modeling and product decisions
• Excellent communication skills and a collaborative mindset

Now it would be fantastic if:

• You have experience in the clinical or medical domain and sensitivity to ethical or regulatory challenges in healthcare AI

What we offer 

• Free health insurance for you and your children
• Parent Care Program: receive one additional month of leave on top of the legal parental leave
• Free mental health and coaching services through our partner Moka.care
• For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support
• Work from EU countries and the UK for up to 10 days per year, thanks to our flexibility days policy
• Work Council subsidy to refund part of sport club membership or creative class
• Up to 14 days of RTT
• Lunch voucher with Swile card

 The interview process  

• Recruiter interview 
• Technical Deep Dive 
• Data System Design 
• Behavioral Interview 
• At least one reference check 

 Job details 

• Permanent position
• Full Time 
• Workplace : Hybrid in our Levallois office
• Start date: asap

At Doctolib, we are committed to improving access to healthcare for everyone. This translates into our recruitment process. We evaluate candidates based solely on qualifications and motivation, without any form of discrimination. The more diverse ideas are heard, the more our product will truly improve healthcare for all.

You are welcome to apply to Doctolib, regardless of your gender, religion, age, sexual orientation, ethnicity, disability. To ensure equal opportunities, we invite you to exclude personal information (e.g. pictures, age) from your applications. If you require any accommodation, please let us know for support during the hiring process.

All information provided is processed by Doctolib for application management. For data processing details, click here.Please contact hr.dataprivacy(at)doctolib.com for inquiries or to exercise your rights.

About the role

We are looking for a meticulous and detail-oriented Biology Data Quality Engineer to ensure the integrity and usability of the various and complex datasets that are central to our mission. In this critical role, you'll leverage your expertise in biology, data science, and machine learning to ensure the quality and consistency of biological data used to train and evaluate our foundation models. You'll work in collaboration with the R&D team and our engineers, using your skills to ensure our data meets the highest standards.

What you'll be doing

As a Biology Data Quality Engineer, you will own the following tasks:

• Data Validation Pipeline Development: Develop and implement comprehensive data validation protocols for diverse biological datasets (histology, omics, clinical). Ensure data integrity, consistency, and accuracy through rigorous quality checks. Design and implement automated data quality pipelines to streamline data validation and identify potential issues early in the data processing workflow.
• Data Curation & Standardization: Establish and enforce data standardization practices to facilitate seamless integration and analysis across different data types. Curate datasets to enhance their usability for machine learning.
• Collaboration & Communication: Work closely with the R&D team to understand data requirements and address data quality concerns. Communicate data quality findings and recommendations effectively to technical and non-technical stakeholders. Communicate and synchronize with external data providers.
• Documentation & Reporting: Maintain a detailed documentation of the data-quality assessment procedures, validation results, and data specifications. Generate regular reports on data quality metrics and trends.
• Data Source Evaluation: Evaluate and validate external public data sources, ensuring they meet our quality standards and are suitable for inclusion in our foundation model training.
• Continuous Improvement: Stay up-to-date with the latest data quality best practices and tools in the biological domain. Propose and implement improvements to our data- quality assessment processes and pipelines.

What you'll bring

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 strong domain expertise in biology alongside strong computational, hands-on skills.

• Omics Data Expertise. Deep understanding of transcriptomics data types (bulk, single-cell, spatial) and their specific quality considerations. Good knowledge of genomics and proteomics data.
• Data Quality Management: Proven experience in implementing data quality control procedures and pipelines. Familiarity with data validation tools and techniques.
• Analytical Skills: Strong analytical and problem-solving skills to identify and resolve data quality issues.
• Programming & Data Analysis: Proficiency in Python, good knowledge of data visualization libraries (e.g. matplotlib).
• Communication Skills: Excellent written and verbal communication skills to effectively convey data quality findings and recommendations.
• Educational Background: MSc in Biology, Computational Biology, Bioinformatics.

How to stand out:

• Computational Pathology Data Expertise: Experience in machine learning analysis of histology images.
• Cloud expertise: Experience working with AWS.
• Data Annotation Experience: Experience with developing and implementing data annotation guidelines and processes. Experience with data ontologies.
• Proven experience building or contributing to large-scale data collections (e.g. Human Cell Atlas).
• Spatial alignment of multimodal datasets (e.g. alignment between different imaging modalities)

The candidate journey

To be considered, please submit your CV in English. We believe in a transparent and collaborative interview process. Here is what you can expect after submitting your application:

1. Screening: Once you have applied, the hiring team will review your application to determine if your work experience and skills align with the necessary proficiencies of this position.
2. Technical Assessment: Given the technical nature of the role, you will be invited to complete a timed (up to 1 hour and 30 minutes) technical assessment on a dedicated platform. This stage consists of a short set of Python exercises designed to assess your coding proficiency.
3. Interviews:
   • Hiring Manager (30 min): A call with the Hiring Manager to discuss your background, motivation, and expertise. This will include a deep dive into your technical skills, including your experience with coding and cloud environments.
   • Data Curation Project (Take-home): Based on the outcome of the previous call, you will be assigned a Data Curation homework. This assignment covers one or more key data modalities and consists of the submission of Python code and a detailed report about your work.
   • Assignment Presentation & Technical Q&A (60 min): You will present your take-home assignment to a broader team. You are also welcome to include a brief presentation of your past experience. This session consists of a 30-minute presentation followed by a 30-minute Q&A to discuss your homework and probe your deeper technical expertise.
   • Executive Interview (30 min): A comprehensive discussion with our Senior Leadership. This session moves beyond technical competency to focus on long-term vision, values, and mutual potential.
4. Offer: Following the completion of the interviews, our hiring team will make a final decision and will be in touch to share the outcome of your interviews. If the team would like to move forward, the recruiter will discuss the details of our proposed offer with you.
5. Onboarding: We are happy to have you joining the team. Once you have accepted and signed your offer, we will be in touch to begin the process of onboarding you to Bioptimus.

Why This is a Unique Opportunity

You will:

• Be part of a trailblazing team working at the intersection of AI, biotech, and biomedical research.
• Take on a high-impact leadership role, shaping the future of biomedical AI through strategic data partnerships.
• Work in a collaborative, innovation-driven environment with top researchers and industry experts.

And benefit from:

• A collaborative and mission-driven work environment.
• Competitive salary and equity package.
• Flexible work arrangements, including remote options.
• Opportunities for professional growth and leadership development.
• Shape the future of biology and AI by contributing to groundbreaking work.