Benefits:

• Remote-First Culture

• Cutting-Edge Technology

• Growth Opportunities

• Team Collaboration

• Mission-Driven Work

Education Requirements:

• Thorough understanding of Machine Learning fundamentals

Experience Requirements:

• Experience building deep-net models

• Experience with PyTorch or TensorFlow

• Excellent problem-solving ability

Responsibilities:

• Own the end-to-end solution to automate workflows involving intelligent document processing

• Research and develop the right ML/AI models to solve business problems

• Implement solutions and guide the deployment

• Guide the data engineering team on collecting training data

• Guide development of exception handling to provide an end-to-end solution integrating actively labeled data in real-time evolving models to achieve state-of-the-art precision

Education Requirements:

• Minimum Doctoral degree or in the last year of the Doctoral degree in Mathematics/Statistics, Computer Science, Physics or Electrical Engineering.

Other Requirements:

• Demonstrable capacity to produce high quality peer reviewed research.

• Familiar with Linux infrastructure and python (C++ familiarity would be beneficial).

• Preferably some knowledge of financial market mechanics.

• Approachable attitude to joint work and peer review and ability to present complex ideas in a concise manner.

• No previous experience is required.

• mathematics hobbyists

Education Requirements:

• Completed a Master's degree in Computer Science, Mathematics, or a related field, with a published paper in a respectable journal or conference.

Experience Requirements:

• at least 3 years of experience working with computer vision models.

Responsibilities:

• Develop your SOTA: Our team is a pioneer in adversarial AI research with numerous studies under our belt. We will guide your research, development, and implementation of state-of-the-art (SOTA) models and techniques.

• Research and Development: Conduct research on adversarial attack and defense techniques for computer vision models. Explore state-of-the-art methods and propose innovative solutions.

• Collaboration: Work closely with team members, participate in brainstorming sessions, and contribute to the team's success.

• Generative Vision: You will help with the research and development of new generative vision pipelines, tackling various modalities and challenges.

Experience Requirements:

• 3+ years of hands-on experience in Computer Vision and deep learning, particularly in object detection and image classification.

Responsibilities:

• Lead Computer Vision Initiatives: Develop and deploy advanced computer vision models for tasks such as object detection, image classification, data extraction, and image quality assessment.

• Drive Innovation in Core-ML Projects: Work on critical machine learning projects, including Credit Risk Modeling and Scorecard Development, ensuring robust and scalable solutions.

• Data Exploration and Analysis: Explore and analyse unstructured data, particularly images, using advanced image processing techniques.

• Model Research and Development: Collaborate with the data science team to research, develop, evaluate, and optimise deep learning models tailored to solve specific business problems.

Benefits:

• Full insurance benefits including medical, dental, vision, and life insurance for you and your dependants

• 401k plan with employer matching

• Flexible PTO and employees are encouraged to take time off to recharge

• Flexible working hours

• Parental leave

Education Requirements:

• PhD or equivalent research experience

Other Requirements:

• Strong background in CV, ML, AI, computer science, engineering or related fields

• Track record of applied research in computer vision

Responsibilities:

• Research and develop algorithms for computer vision-based problems including scene understanding and anomaly detection

• Develop performance and quality metrics for ML models and systems

• Collaborate with software engineers and product owners on system architecture, design and production code, especially where ML models are used

• Keep up to date with state of the art in ML and CV

• Mentor younger scientists

Benefits:

• A competitive compensation package (base + equity) with bi-annual reviews, aligned to our quarterly OKR planning cycles

• Work at one of the fastest-growing tech startups, backed by top VC firms, Balderton & EQT Ventures

• A clear progression plan.

• Flexibility

• Work where you work best.

Experience Requirements:

• 5+ years of experience doing quantitative analysis within a digital product environment.

Responsibilities:

• Enabling the rapid growth of our business; understanding the ecosystem of our business and identifying the highest impact areas for product-led growth.

• Defining key virality metrics and tracking KPIs to analyse what really matters. You’ll closely monitor our K-factor and find opportunities to improve it.

• Leading the measurement of ROI, incrementality, and cannibalisation of new viral initiatives.

• Influencing the roadmap of product teams through presentation of data-based recommendations.

• Applying graph theory and building network models to uncover new viral opportunities.

Experience Requirements:

• 5-7 years experience in NLP, Machine Learning, Deep Learning, Python, Computer Vision & 1-2 years exp in Gen AI.

Education Requirements:

• PhD in Remote Sensing, Environmental Science, Geospatial Science, or a related field.

Experience Requirements:

• Extensive experience with remote sensing techniques, particularly for flood detection and analysis.

• Proven expertise in change detection and workflow development for event mapping.

Other Requirements:

• Proficiency in using GIS and remote sensing software (e.g., ArcGIS, ERDAS IMAGINE) and programming languages (e.g., Python, R).

• Strong analytical skills and the ability to translate complex data into actionable insights for flood risk management.

Responsibilities:

• Lead the development and application of remote sensing methodologies for flood detection, change detection, and event mapping.

• Design workflows that enable efficient processing and analysis of satellite and aerial imagery for flood monitoring.

• Collaborate with data science and engineering teams to integrate flood detection models into our platform.

• Conduct research and develop algorithms to enhance the accuracy of flood event mapping and prediction.

• Provide technical expertise and guidance on flood-related risk assessment and management strategies.

Benefits:

• Healthcare

• Remote Work

• Integrated Team

• Unlimited Time Off

• A Voice, Professional Development

Benefits:

• 100% paid comprehensive medical coverage, including vision and dental, and HSA plan options for employees and their dependents

• Health & wellness app reimbursement

• On-site gym

• Free lunch

• 12 company holidays and flexible time off Generous parental leave: 18 weeks for birth parents and 12 weeks for non-birth parents Hybrid work environment: 3 days a week onsite and two days work from home Twice yearly multi-day offsites Safe harbor matching 401(k) Tax Advantaged Accounts including FSA, Dependent Care FSA, HSA, and commuter benefits Employer Paid Basic Life & AD&D Short Term and Long Term Disability

Education Requirements:

• PhD in biological sciences

Experience Requirements:

• at least 5-year experience in RNA-targeted small molecule discovery

• Proven hands-on experience in working with RNA targets and related screening technologies including but not limited to ASMS, ALIS, Microarray, SPR, ITC.

• Ability to evaluate newer methods as appropriate and implement novel approaches to screen RNA as needed.

• Ability to independently drive, manage, execute, and deliver results on key programs under tight timelines.

• Ability to work in a collaborative environment to enable integration of state-of-the-art technology platform with RNA biology to accelerate the program pipeline.

Responsibilities:

• Work with company leadership to advance our strategy for targeting RNA with small molecules and RNA degraders.

• Develop RNA screening strategy, establish screening platform and relevant technologies internally and/or in collaboration with external partners including but not limited to ASMS, Microarray, SPR, ITC, and/or other relevant biophysical methods. In addition, evaluate any new methods and implement them as necessary.

• Enable RNA-directed small molecule drug discovery efforts. Establish validated processes for small molecule hit ID, validation, and lead optimization for RNA targets. Deliver on program requirements in a timely manner.

• Collaborate with the drug discovery, ML data and ML teams to build an integrated workflow to support RNA biology programs.

• Provide scientific leadership and perform day-to-day lab activities.

Experience Requirements:

• 1+ years

Experience Requirements:

• 3+ years

Experience Requirements:

• 3+ years

Education Requirements:

• BS, MS, PhD in quantitative field, such as Physics, Mathematics, Statistics, Engineering, or equivalent practical experience.

Experience Requirements:

• Experience with some form of Deep Learning, for example Image recognition, or NLP, and a solid understanding of the foundations.

• Experience with programming in Python.

• Good knowledge of statistics, data analysis, and modelling methods.

• Problem solving skills with respect to approaching a new dataset/customer request and formulating a problem.

Other Requirements:

• Good written and verbal communication.

• Demonstrated ability to work with minimal to no supervision.

• Ability to work remotely with cross-cultural teams.

• Self-motivation to learn new concepts and an excellent record of execution.

• A sense of urgency, result orientedness, and excellent ability to prioritize.

Responsibilities:

• The data scientist in a team has a varied role. This can include working directly with our customers to support the deployment of our products, or internally to strengthen the products themselves.

• For our customers, your work will vary from initial data exploration, to modelling and problem formation, and then finally to the Reinforcement Learning training itself.

• Subspecialties within this broad scope are encouraged.

• You will work collaboratively with our backend, product, and AI teams.

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.

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:

• Proficiency processing large datasets with statistical packages

• Software development experience as demonstrated through course work, research projects or open source activities, preferably in Python or C++

• Applied Experience with Machine Learning and Big Data technologies

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

Responsibilities:

• Develop AI trading strategies in various financial market (Forex, stock, ETF, etc.) for finance domain

• 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 that are used in automation and analysis tasks

Benefits:

• comprehensive medical, dental, and vision plans

• yearly wellness stipend

• 401k program

• parental leave program

• workstation setup allowance

Experience Requirements:

• 5+ years of professional experience with machine learning, or 2+ years of professional experience with machine learning with an advanced degree in a relevant field

• 1+ year of professional experience working directly with external customers to scope out build machine learning models, tools, or services

• Expertise in modern machine learning frameworks and technologies (e.g. PyTorch, Transformers, Scikit-learn, NumPy, Pandas), and an obsession with thorough ML evaluation

• Experience building and maintaining large scale, production data pipelines for machine learning applications

• Ability to work in a fast-paced environment and strong technical communication skills

Responsibilities:

• Assist customers with the delivery of a Machine Learning project from beginning to end, including business case definition and scoping, data aggregation and exploration, algorithm selection, and model deployment to deliver business impact to the organization

• Present findings and recommendations to customer stakeholders, assist with program ideation and technical program management, and brief materials.

• Design, develop, and deploy enterprise AI/ML solutions across various industries like finance, healthcare, insurance, retail and more

• Serve as the voice of our customers for new ML paradigms, data science workflows, and share customer feedback to product teams