Benefits:

• Extremely competitive compensation

• High degree of autonomy

• Small team of top performers

Experience Requirements:

• Shipped agents to production

• Opinions on what works with today's models

Other Requirements:

• Learn fast

• Ability to ship

Responsibilities:

• Help productize continuous training loops

• Figure out the correct UX to ship products to customers

• Design dashboards, APIs, or other interfaces

Education Requirements:

• Ph.D. or Master's Degree in Computer Science, Electrical Engineering, Statistics, Mathematics, Physics, Computational Finance, Industrial Engineering, Financial Engineering, Operations Research or a similar quantitative field.

• Ph.D. preferred.

Experience Requirements:

• Expertise in Machine Learning, Data Mining, Pattern Recognition, Natural Language Processing or Computer Vision.

• Publications in peer-reviewed journals and conferences.

• Experience or interest in programming in one or more of these languages: C++, C, Java, Python, Go, etc.

Other Requirements:

• Stay hungry: challenge the status quo and develop innovative solutions

• Pursue impacts: business acumen to create customer values from findings

• Passion to work at a start-up and in a team

Responsibilities:

• Lead in cutting-edge AI research and develop innovative approaches in the financial/healthcare domains to solve real-world problems.

• Publish your results and grow Graphen’s IP portfolio.

• Contribute ideas, develop prototypes and implement efficient and effective algorithms for Graphen solutions.

Education Requirements:

• Currently studying or graduated from a scientific or quantitative field (Preferably MS or PhD)

Experience Requirements:

• Extraordinary quantitative and data management skills

• Proficiency processing large datasets with statistical packages

• Software development experience in Python or C++

• Applied Experience with Machine Learning and Big Data technologies

Other Requirements:

• Innovative and flexible thinking

• Previous experience or course work in finance, business, economics, and/or biostatistics is a plus

Responsibilities:

• Develop AI trading strategies in various financial markets

• Develop AI analyses in genome and/or proteome data in the medical domain

• Work with large data sets and solve difficult, non-routine analysis problems

• Translate unstructured, complex business problems into Machine Learning framework

• Prototype, refine, deploy and monitor predictive models and decisions agents

Benefits:

• 401(k)

Education Requirements:

• PhD degree

Experience Requirements:

• Experience with Python (Programming Language)

• Experience with Machine Learning

• Experience with Natural Language Processing (NLP)

• Experience with Large Language Models (LLM)

Other Requirements:

• Published research papers or contributions to research

• Participation in open source ML/NLP projects

• Located within a European time zone (UTC+0 to UTC+3)

• Leading successful EU or national R&D grant proposals

Responsibilities:

• LLM Evaluation

• Agentic Systems

• Research & Development

Benefits:

• competitive pay

• company paid healthcare

• flexible spending accounts

• voluntary life insurance

• 401K matching

Education Requirements:

• Ph.D., M.D., or equivalent advanced degree in cancer biology, molecular biology, pharmacology, computational biology, or a related discipline.

Experience Requirements:

• Typically 12–20+ years of relevant experience in biotech or pharma, with progressive leadership responsibility.

• Demonstrated success advancing at least one oncology program into clinical development.

Other Requirements:

• Deep expertise in translational science, including biomarker strategy, MoA, resistance, and combination biology.

• Proven experience working with large, complex translational and/or clinical datasets.

• Strong working knowledge of AI/ML concepts as applied to drug discovery and development.

• Excellent scientific storytelling and communication skills.

Responsibilities:

• Lead Portfolio-Level Translational Strategy

• Define Biomarker & Patient Selection Strategy

• Mechanism of Action, Resistance & Combination Biology

• AI/ML-Enabled Translational & Clinical Prediction

• Build and Lead a High-Impact Organization

Benefits:

• competitive pay

• company paid healthcare

• flexible spending accounts

• voluntary life insurance

• 401K matching

Education Requirements:

• PhD in biochemistry, cell biology, cancer biology, pharmacology, or related discipline

• MS with 7+ years of experience

• BS with 9+ years of experience

Experience Requirements:

• 2 - 8 years of relevant academic or industry experience (PhD)

• Experience in cancer research, mechanism of action/resistance, or translational biomarker development

• Hands-on experience in in vivo pharmacology

Other Requirements:

• Strong proficiency in cell and molecular biology

• Experience developing and troubleshooting biochemical and cell-based assays

• Excellent communication skills

Responsibilities:

• Work closely with Biology group to design translational studies

• Design and manage in vivo pharmacology studies at CROs

• Design and execute hands-on experiments in cell and molecular biology

• Analyze and interpret data from internal experiments and CRO deliverables

• Conduct literature reviews to support biomarker strategies

Benefits:

• competitive pay

• company paid healthcare

• flexible spending accounts

• voluntary life insurance

• 401K matching

Education Requirements:

• BS in Chemistry

• MS in Chemistry

Experience Requirements:

• 5+ years experience (pharma/biotech) for BS

• 3+ years experience (pharma/biotech) for MS

• 5+ years of experience contributing to drug discovery projects

Other Requirements:

• Proven skills in multi-step organic synthesis

• Reaction optimization and SAR analysis skills

• Ability to thrive in a fast-paced environment

• Familiarity with ADME-PK principles

Responsibilities:

• Design, synthesize, purify, and characterize chemical compounds

• Identify and optimize reaction conditions

• Collaborate with the high-throughput experimentation team

• Analyze biological and ADME-PK data

• Partner with computational chemists

Benefits:

• competitive pay

• company paid healthcare

• flexible spending accounts

• voluntary life insurance

• 401K matching

Education Requirements:

• PhD or equivalent degree in computational chemistry (or related field)

Experience Requirements:

• 5+ years of experience working in an industry drug discovery environment

• Experience supporting active small molecule drug discovery programs

• Experience with ligand and structure based design tools

Other Requirements:

• Python programming

• Familiarity with MOE molecular modeling package

• Familiarity with MD simulation and advanced binding affinity prediction methods

• Experience with ML-augmented small molecule discovery

Responsibilities:

• Apply ligand and structure-based approaches across drug discovery phases

• Guide design cycles through SAR identification

• Partner with medicinal chemists to prioritize virtual libraries

• Partner with ML scientists to integrate SBDD methods

• Leverage proprietary protein-ligand co-folding technology

Benefits:

• competitive pay

• company paid healthcare

• flexible spending accounts

• voluntary life insurance

• 401K matching

Education Requirements:

• PhD or equivalent degree in chemistry or another physical science

Experience Requirements:

• 3+ years of experience or commensurate degree and job experience

• 3+ years of experience working in a drug discovery project

Other Requirements:

• Python programming

• Statistics knowledge

• Familiarity with using statistical analysis techniques to evaluate models

• Excellent written and verbal communication skills

Responsibilities:

• Train, fine-tune, and evaluate machine learning models

• Partner with computational chemists, medicinal chemists and biologists

• Generate value from machine learning models internally and for partners

• Communicate results with internal drug discovery teams

• Support evolution of ML models by gathering analytical feedback

Education Requirements:

• Ph.D. in Artificial Intelligence

Responsibilities:

• We are looking for Ph.D. in Artificial Intelligence, if you are interested please complete the form below.

Experience Requirements:

• 3-6 years

Responsibilities:

• Help us push the boundaries of AI-powered code generation and understanding.

• Work on cutting-edge ML models and systems.

Experience Requirements:

• 2-5 years

Responsibilities:

• Analyze user behavior

• Improve our AI models

• Drive data-informed product decisions

Education Requirements:

• Bachelor’s degree in Computer Science, Engineering, Software Engineering, Applied Mathematics, Statistics, or related field

• Masters/PhD in Data Science, Machine Learning or AI (Desired)

Experience Requirements:

• Relevant data science or machine learning engineering experience

• Programming experience, preferably fluent with Python and SQL

• Familiar with fundamental machine learning theory

• Experience with at least one Cloud provider

• Experience with building training and inference pipelines for ML projects

Other Requirements:

• Strong analytical skills and passion for solving data problems

• Strong communications skills

• Understanding of database architectures

• AWS certifications

• Interested in learning more about Cloud Native Computing Foundation technologies

Responsibilities:

• Exploratory data analysis

• Implementing data pipelines

• Training models (machine learning or not)

• Data visualisation

• Communicate effectively with both business and technical stakeholders

Benefits:

• Generous compensation in cash and equity

• Flexible paid time off

• Health insurance coverage

• Annual health and wellness stipend

• Monthly meal stipend

Education Requirements:

• Advanced degree in a quantitative field (Mathematics, Statistics, Computer Science, etc.)

Experience Requirements:

• 5+ years of experience in data science or quantitative modeling

Other Requirements:

• Strong working knowledge of Python, R, Spark, or SQL

• Critical thinking and problem-solving skills

• Ability to explain technical findings to non-technical stakeholders

Responsibilities:

• Build and deploy ML models to prevent fraud

• Support development of risk mitigation strategies

• Work directly with clients to deliver solutions

• Evolve risk metrics and measurement of impact

• Collaborate with engineering to scale models

Benefits:

• Real impact on client strategies

• Diverse project portfolio

• Growth paths into consulting or AI engineering

• Flexible working hours

• High-end equipment

Experience Requirements:

• Minimum of 4 years of experience in Data Science

• Proficiency in classical and non-linear ML techniques

• Fluent Python programming (NumPy, pandas, scikit-learn)

• Ability to manage and analyze data using SQL

• Ability to translate data into actionable business insights

Other Requirements:

• Strong communication skills

• Ability to explain complex concepts simply

Responsibilities:

• Data exploration and cleaning

• Predictive modeling and time-series analysis

• Generating business insights directly supporting decisions

• Creating data visualizations and dashboards

• Collaborating with AI engineers and product teams

Experience Requirements:

• top tier

Other Requirements:

• n8n

• OpenAI AgentKit

• OpenAI ChatKit

Responsibilities:

• Data & Insights / Streaming

• Machine Learning research for creative tech

Responsibilities:

• Data & Insights / Streaming

• Managing core ad metrics