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

Benefits:

• comprehensive medical, dental, and vision plans

• yearly wellness stipend

• 401k program

• parental leave program

• workstation setup allowance

Experience Requirements:

• 7+ 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

Education Requirements:

• A PhD in Industrial-Organizational Psychology, Psychometrics, or a related field is required.

Experience Requirements:

• A proven track record in psychological assessment, AI governance, and the application of IO psychology principles to data science and machine learning.

Other Requirements:

• Professional Memberships: Chartered status or higher with the British Psychological Society (BPS) or the European Federation of Psychologists Associations (EFPA) is essential.

• Thought Leadership: Experience publishing in peer-reviewed journals and contributing to industry discourse on ethical AI and innovative assessment methods.

• Collaborative Leadership: A willingness to work within a small, high-performing team, fostering collaboration to achieve global success.

Responsibilities:

• Lead the organisational psychology function

• Build the brand of Sapia.ai in the market with a focus on the UK market. This includes being a thought leader in the I/O community and in the HR tech community on responsible use of AI, ethical AI, advancements in NLP to assess role fit, and appropriate measurement of ML assessments

• Support Sales and Customer Success Teams: Act as a trusted advisor to ensure we deliver on client and market expectations for scientific validity and compliance, particularly in regulated markets. Act as a thought partner and trusted consultant for customers on the use of AI in recruitment, helping them navigate ethical considerations, bias mitigation, and the implementation of AI-driven assessments for fair and effective hiring.

• Be the product owner for assessment governance, including ethical use of AI, adverse impact testing and validity analysis, working with the Data Science (DS) team

• Partner with Product and Data Science for Assessment Innovation Collaborate with Product and Data Science teams to implement best practices in organizational psychology, enhancing the validity and reliability of Sapia.ai’s AI interview platform.Integrate research findings on hiring outcomes, adverse impact, and mobility into the product strategy to refine predictive assessment tools.Conduct validation studies on assessment effectiveness and provide actionable recommendations for continuous improvement.Serve as the subject matter expert (SME) for Sapia Labs as they advance to Chat 2.0.Collaborate with Sapia Labs, product, and engineering teams to drive AI-driven innovation in assessment design, ensuring alignment with emerging research, ethical guidelines, and industry best practices.Engage regularly in market forums that will build trust in our brand of science. These could be SIOP, regulatory settings, and customer forums.

Education Requirements:

• PhD in Machine Learning

• Statistics

• Industrial Engineering

• Operations Research

• Optimization, or an equivalent quantitative field.

Experience Requirements:

• 10+ years of overall experience in machine learning and statistical modeling, including exposure to time series forecasting and large-scale data analysis.

Responsibilities:

• Provide Thought Leadership: Steer the strategy and vision for Keystone’s Core AI team by championing deep learning innovations in time series forecasting, supply chain optimization, and inventory control.

• Lead & Mentor: Oversee a multidisciplinary team of data scientists and ML engineers, guiding them in model development, best practices, and impactful project delivery.

• Develop Advanced Models: Design and refine deep learning architectures that accurately forecast demand, manage inventories, and extract actionable insights from complex data sets across industries.

• Collaborate Cross-Functionally: Work closely with product managers, data scientists, economists, research scientists, software engineers, and ML engineers to create scalable, end-to-end AI solutions that address real business needs.

• Drive Innovation: Contribute to the evolution of Keystone’s foundation forecasting capabilities by exploring novel techniques, ensuring our solutions remain on the cutting edge.

Education Requirements:

• B.S./M.S. in Biochemistry, Biophysics, or a related field

Experience Requirements:

• minimum 1 year of academic or industry lab experience.

Responsibilities:

• Design and execute routine biophysical assays from beginning to end using methods such as SPR, DSF, and other biophysical techniques to characterize small molecule-protein interactions.

• Routinely and independently analyze & QC experimental data.

• Program, validate, and operate liquid-handling automation (Biomek Liquid handler, Multidrop Combi, Integra Viaflo & Voyager) for 384-well plate-based assays and use instrumentation such as plate readers for reproducible, publication-quality data generation.

• Communicate results efficiently & precisely in written format by maintaining electronic lab notebook.

• Presents work to supervisor, lab and/or project meeting.

Benefits:

• Competitive Pay

• Health Care Plans (including Medical, Dental, and Vision, fully covered for the employees)

• Stock Option Eligibility

• 401(k) Plan

• Open PTO Policy Paid Company Holidays Free lunch and snacks at our offices

Education Requirements:

• A BSc, MSc, or PhD degree in immunology, molecular and cell biology, biochemistry or a related field

Experience Requirements:

• 8+, 5+ or 2+ years of relevant industry experience, respectively.

Responsibilities:

• Autonomously plan, design, and execute biochemical and cell-based experiments to support our I&I pipeline.

• Maintain a hands-on approach while being an open-minded, flexible team player.

• Analyze, interpret and integrate complex datasets across multiple assay types.

• Document data meticulously using ELN and state-of-the-art analyses.

• Stay at the forefront of latest research through literature review and critical evaluation of available data sources.

Education Requirements:

• Currently enrolled in a PhD program in Computer Science, Machine Learning, or related fields.

Responsibilities:

• Lead a research project, which will be broadly focused on a problem related to generative or predictive modeling of molecular systems.

• Navigate the latest deep learning literature, extracting insights from generative modeling in adjacent domains (language, images, 3D graphics, etc.), develop novel models and training techniques for molecular data, and communicate your findings to the team.

• Carefully design and run experiments at scale to validate most promising approaches and hypotheses.