AI Jobs

Benefits:

• 100% covered medical/dental/vision

• 15 days annual PTO plus holidays

• 401k matching

• Significant ownership

Education Requirements:

• PhD or equivalent industry experience

Experience Requirements:

• Significant prior experience with CNNs, GANs, Diffusion

• 2 years of hands-on experience with TensorFlow or PyTorch

• Working knowledge of C/C++

• Prior key contributor to significant DL projects

Other Requirements:

• Good understanding of common image processing algorithms

• Well-read on major recent research papers

Responsibilities:

• Explore and develop new deep learning models

• Solve inverse problems in imaging

• Evaluate customer feedback and image data

• Refine models based on real-world usage

• Collaborate with other world-class researchers

Experience Requirements:

• Strong grounding in machine learning / deep learning

• Experience with PyTorch, Python, and modern ML workflows

• Experience with geospatial data

• A curious mind and motivation

Other Requirements:

• European working hours

Responsibilities:

• Train and fine-tune vision models

• Research and implement cutting-edge ML architectures

• Contribute to no-code AI platform

• Apply foundation model adaptation techniques

Experience Requirements:

• Strong grounding in machine learning / deep learning

• Experience with PyTorch, Python, and modern ML workflows

• Experience with geospatial data

• A curious mind and motivation

Other Requirements:

• European working hours

Responsibilities:

• Train and fine-tune vision models

• Research and implement cutting-edge ML architectures

• Contribute to no-code AI platform

• Apply foundation model adaptation techniques

Benefits:

• Databricks certifications

• Supportive AI/Big Data team

• Flexible work arrangements

• 20 fully paid days off

• Integration budget

Experience Requirements:

• 3+ years commercial experience with Python

• Hands-on experience with LLMs and GenAI

• Experience with backend frameworks like FastAPI

• Practical experience in cloud (AWS, GCP, Azure)

Other Requirements:

• Keen interest in Data Science

• Familiarity with Docker and Git

Responsibilities:

• Support development of scalable AI systems

• Transform prototypes into production solutions

• Build backend components in Python

• Ensure code quality and best practices

• Participate in cloud maintenance

Benefits:

• Career paths and knowledge-sharing

• Training materials and certifications

• 20 fully paid days off

• Integration budget

• Work anniversaries and birthdays celebration

Education Requirements:

• Master's degree in Computer Science or related field

Experience Requirements:

• 6+ years in designing scalable AI solutions

• Experience leading ML projects

• Proficiency in Python and ML libraries

• Expertise in cloud deployment (AWS/Azure)

• Knowledge of LLMs and semantic search

Other Requirements:

• High proficiency in English (C1 level)

Responsibilities:

• Lead development of ML solutions

• Design AI solution architectures

• Research and select best tools/technologies

• Lead and mentor cross-functional teams

• Translate business problems to DS problems

Benefits:

• International projects with global enterprises

• Flexible work arrangements

• Career paths

• 20 fully paid days off

• Integration budget

Education Requirements:

• Bachelor's or Master's degree in Data Science or related

Experience Requirements:

• Commercial experience designing AI solutions

• Proficiency in ML algorithms

• Strong programming skills in Python

• Expertise in cloud (AWS or Azure)

• Knowledge in applying LLMs

Other Requirements:

• High proficiency in English (C1 level)

Responsibilities:

• Lead development and implementation of ML

• Lead the design of AI solution architectures

• Research and select best technologies

• Architect data pipelines and workflows

• Present findings clearly to stakeholders

Education Requirements:

• PhD or equivalent experience in speech technology, machine learning, or a related field

Experience Requirements:

• Proven track record of publishing in leading speech conferences such as Interspeech, ICASSP, etc.

• Hands-on experience with popular speech toolkits and frameworks

Other Requirements:

• Strong programming and algorithmic skills

Responsibilities:

• Lead and drive innovative research in the field of speech recognition, synthesis, and related technologies

• Collaborate closely with the R&D team to integrate research findings into Camb.ai's products

• Keep abreast of latest advancements in speech technology and continuously push for innovations in the field

• Publish research findings in leading conferences, journals, and workshops

Education Requirements:

• PhD or equivalent experience in NLP, Deep Learning, or a related field

Experience Requirements:

• Experience with popular NLP toolkits and platforms

Other Requirements:

• Strong understanding of current challenges in language models and a passion for innovation

Responsibilities:

• Lead research in Language Model (LLM) development, focusing on zero-shot performance

• Collaborate with other R&D teams to enhance foundational model capabilities

• Stay updated with the latest advancements in NLP and LLM

• Drive efforts for publishing the research in top-tier conferences and journals

Benefits:

• Flexibility and freedom of remote work

• Flexible and inclusive work environment

Other Requirements:

• Passionate about building tools for remote workers

• Dedicated to making AI enhance teams and individual potentials

Responsibilities:

• Help us research the future of remote work with AI

Education Requirements:

• Minimum Bachelor’s Degree in Computer Science, Data Sciences, Statistics, Mathematics, or other related fields

Experience Requirements:

• 1 – 3 years of experience as a hands-on analyst with risk knowledge

Other Requirements:

• Working experience in handling large-scale unstructured data

• Experience in using business intelligence tools such as Microsoft Excel, Tableau, and Qlik Sense

• Experience in SQL or other data handling tools a bonus

Responsibilities:

• Handle end to end process from data analysis to presenting recommended actions

• Monitor any new or existing implementations relating to risk

• Timely response to alerts for any risk related escalations

• Deep dive investigation on potential issues such as changes to clients’ metrics

• Optimize fraud detection by identifying emerging fraud trends

Benefits:

• Flexible, hybrid work environment

• Office based at Station F in Paris

• Competitive compensation package

Education Requirements:

• Currently enrolled in a Ph.D. or M.Sc program in Machine Learning, applied mathematics or computer science (Ph.D preferred)

Experience Requirements:

• Experience with distillation and/or improved sampling techniques for diffusion models

• Proven track record through personal projects or deep learning experience

• Experience with generative models (diffusion models, GANs, VAEs, transformers)

Other Requirements:

• Strong coding abilities in Python and deep learning frameworks (PyTorch, TensorFlow, JAX)

• Problem-solving mindset and excellent teamwork skills

• Availability for a period of 6 months

Responsibilities:

• Conduct literature reviews and propose innovative methods for diffusion models

• Participate in the fine-tuning stages of large-scale text-to-image models

• Document research findings and prepare technical reports

• Contribute to open-source projects and engage with the AI community

• Design evaluation metrics and analyze model performance

Benefits:

• Flexible, hybrid work environment

• Office based at Station F in Paris

• Competitive compensation package

Education Requirements:

• Currently enrolled in a Ph.D. or M.Sc program in Machine Learning, applied mathematics or computer science (Ph.D preferred)

Experience Requirements:

• Experience with RLHF techniques applied to LLMs or Diffusion Models

• Proven track record through personal projects or deep learning experience

• Strong coding abilities in Python and frameworks like PyTorch

Other Requirements:

• Problem-solving mindset

• Excellent teamwork skills

• Availability for 6 months

Responsibilities:

• Conduct literature reviews on RLHF and DPO methods

• Implement fine-tuning techniques for text-to-image models

• Analyze model performance and conduct rigorous ablations

• Document findings and prepare technical reports

• Contribute to foundational open-source models

Benefits:

• A competitive compensation package including opportunities for employee options awards

• Opportunities to enjoy meaningful and disruptive works on game-changing products

• A flexible, supportive and productive working environment

• Passionate colleagues and friends

• A strong commitment to your personal and professional growth

Experience Requirements:

• 2+ years as a Data Scientist or ML Engineer in a strong data-driven SaaS environment/product

• Real-world experience in working with customers to develop and deploy Data Science and ML solutions

Other Requirements:

• Solid analytical thinking and problem-solving skills

• Hands-on experience and demonstrable ability to code fluently in Python

• Strong working knowledge of efficient data structures, computational complexity and algorithms

• Solid theoretical understanding in probability, statistics, supervised and unsupervised learning, time series

• Strong experience and demonstrable skills in Data Science stack (scikit-learn, pandas, numpy, scipy)

Responsibilities:

• Applying Data Science and Machine Learning to solve real-world business problems

• Developing new data-science / ML functions across products

• Taking charge of existing code base for continuous maintenance, bug fixing, and improvement

• Working with the Software/DevOps Engineering team to brainstorm ideas and develop new features

• Participate the design process for new features as a representative from the Data Science team

Education Requirements:

• A bachelor or higher degree in linguistics, communication, psychology, social sciences, literature, or equivalent.

Experience Requirements:

• Excellent reading and writing skills in casual and business English

• Experience in managing multiple projects by deadlines

Other Requirements:

• Open-minded, multi-talented individuals

• Sensitive to the nuances of interpersonal communication

• Adept at writing conversations

• Comfortable working with customers and new technologies

Responsibilities:

• Teach AI assistants natural language understanding and communication skills

• Deliver fun and satisfying conversational experience

• Gain experience in the application of AI in diverse business settings

• Manage multiple projects

• Write conversations

Responsibilities:

• Making human-level language AI part of everyday life through next-gen generalization-focused language research

Education Requirements:

• M.Sc. in Computer Science, Data Science, or a related technical field

• B.Sc. with 3+ years of hands-on experience in AI/ML applications

• PhD in Computer Science (Nice to Have)

Experience Requirements:

• 3+ years of hands-on experience in AI/ML applications (if B.Sc.)

• Strong understanding of LLMs, embeddings, cross-encoders, vector search

• Experience running experiments and analyzing results with rigor

• Experience in a fast-paced startup (Nice to Have)

• Paper publications in conferences (Nice to Have)

Other Requirements:

• Familiarity with open-source libraries, models and research environments

• Ability to translate ideas into prototypes and iterate quickly

Responsibilities:

• Be the expert in the latest research and tooling around LLMs and RAG

• Develop benchmarks and evaluation frameworks

• Productionize research and build end-to-end reliable systems

• Contribute to internal research documentation

• Stay up to date on academic and open-source developments

Experience Requirements:

• Leaders with experience running research organizations or data-driven strategy teams.

• Individuals who see GTM as a science — and are obsessed with defining its core primitives.

• Deeply curious, multidisciplinary thinkers fluent in AI, economics, and market systems.

• Comfortable managing hybrid teams of humans, models, and agents producing open knowledge.

Responsibilities:

• Oversees the institution’s open-source GTM research agenda, including frameworks, benchmarks, and ontologies.

• Drives the roadmap for how OpenGTM codifies market knowledge — from company profiles and GTM data models to AI benchmarks and cross-vendor evaluations.

• Ensures the Lab functions as both an R&D engine and a public institution: balancing academic rigor with industry relevance.

• Leads a distributed network of researchers, AI systems, and contributors working toward the unified goal of mapping global GTM intelligence.

Benefits:

• Drive real drug discovery with visible impact on pipeline progress

• Join a science-first team blending AI and chemistry for next-gen therapeutics

• Enjoy flexible working with support for remote collaboration

Education Requirements:

• Ph.D. in Computational Chemistry, Medicinal Chemistry, or a related field

• Master’s degree in computational drug discovery or related roles

Experience Requirements:

• 2–5 years of experience in drug discovery (with Ph.D.)

• 5+ years of hands-on industry experience in computational drug discovery or related roles (with Master's degree)

• Proven track record of contributing to hit identification, hit-to-lead, or lead optimization programs

• Proficiency in molecular modeling platforms

• Strong understanding of medicinal chemistry and SAR interpretation

Other Requirements:

• Comfortable working in fast-moving, cross-functional project teams

• Is actively contributed to real drug discovery projects and can confidently apply modeling techniques to impact design decisions.

• Is comfortable balancing scientific depth with practical prioritization and can independently plan and drive modeling strategies within multi-disciplinary projects.

Responsibilities:

• Use molecular modeling tools (e.g., docking, molecular dynamics, FEP, pharmacophore design) to support compound design.

• Interpret SAR data, suggest new analogs, and prioritize compound ideas.

• Collaborate with medicinal chemistry teams.

• Contribute to planning project workflows and setting modeling priorities.

• Drive hypothesis generation and test cycles based on evolving data.

Benefits:

• Mentorship from experts with deep industry experience.

• Work on high-impact, real-world drug discovery programs.

• Flexible, remote-friendly culture.

Education Requirements:

• Final-year student or recent graduate (B.Sc. or M.Sc.) in Chemistry, Biochemistry, Pharmaceutical Sciences, Computational Chemistry, Structural Biology, or related fields.

• Candidates from engineering or physics with exposure to molecular simulations, bioinformatics, or AI in life sciences are encouraged to apply.

Experience Requirements:

• Basic understanding of molecular docking principles and exposure to tools such as AutoDock, Glide, or GOLD through coursework, internships, or self-study.

• Introductory knowledge of computer-aided drug design (CADD) concepts.

• Familiarity with molecular visualization tools (PyMOL, UCSF Chimera, VMD).

• Basic proficiency in Python or another scripting language; experience with Jupyter or Google Colab preferred.

• Coursework, research projects, or self-initiated learning in computational modeling will be considered favorably.

Other Requirements:

• Strong scientific curiosity and willingness to learn hands-on tasks in computational drug discovery.

• Ability to communicate findings clearly and work collaboratively in a team environment.

• Openness to feedback and continuous learning in a fast-paced setting

• Experience in academic drug discovery programs, hackathons, or internships at pharma, CROs, or research centers.

• Familiarity with AI/ML frameworks for chemistry (e.g., DeepChem, PyTorch).

Responsibilities:

• Support hit discovery projects by preparing protein and ligand structures for modeling.

• Run docking workflows and visualize protein–ligand interactions using molecular modeling tools.

• Assist in structure- and ligand-based design tasks across live projects.

• Contribute to the setup and execution of cheminformatics pipelines (e.g., RDKit, Open Babel).

• Document workflows, results, and insights clearly for team discussions.

Education Requirements:

• Background in biophysics, biology, chemistry, or a related field.

Experience Requirements:

• Practical experience with GROMACS.

• Knowledge of system preparation (force fields, solvation, methods of parameterization).

• Experience with membrane protein simulations.

• Linux proficiency; basic scripting (Bash, Python).

Other Requirements:

• Experience with other MD engines (AMBER, NAMD, or OpenMM)

• Familiarity with enhanced sampling methods.

• Experience with mixed-solvent simulations.

• Hands-on experience with HPC.

Responsibilities:

• Prepare and run MD simulations on HPC/cloud systems.

• Perform standard analyses (RMSD, RMSF, hydrogen bonds, clustering, etc.).

• Automate routine steps with simple scripts.

• Document and report results clearly.