Benefits:

• Full workstation

• Malpractice insurance

• AI-optimized workflow

Experience Requirements:

• Must have 1+ year(s) of work experience interpreting studies

Other Requirements:

• Must be ABR or AOBR board-certified

• Fellowship training is preferred, but not required

Responsibilities:

• Reading X-ray, ultrasound, and CT studies for Outpatient and Urgent Care settings

Benefits:

• Full workstation

• Malpractice insurance

• AI-optimized workflow

Experience Requirements:

• Must have 1+ year(s) of work experience interpreting studies

Other Requirements:

• Must be ABR or AOBR board-certified

• Fellowship training is preferred, but not required

Responsibilities:

• Reading X-ray, ultrasound, and CT studies

Benefits:

• 25 days paid annual vacation

• flexible working hours

• opportunity to work from home when needed

• Health Insurance

• Subsidized Multisport card

Education Requirements:

• A degree in a relevant area (Computer Science, Statistics, Applied Mathematics, or related field)

Experience Requirements:

• At least 5 years of experience in software engineering and data science fields

• Strong knowledge of software engineering of scalable (vertical and horizontal) production systems related to data science applications such as statistical modeling, machine learning, and optimization techniques

• Excellence with programming languages – Python is a plus

• Strong knowledge of design patterns, OOP, multithreading, and databases

• Good experience in building processes and automated deployments

Responsibilities:

• Design, Develop, and implement a framework for the implementation of repetitive automated data science models and algorithms deployed in production

• Collaborate with product and engineering teams to identify and prioritize opportunities to improve our solutions

• Conduct research to stay up-to-date with the latest developments in the implementation of data science and machine learning techniques in production in both cloud and server-based environments

• Develop proof-of-concept and prototypes to demonstrate the feasibility and value of new technologies

• Design and implement experiments to validate models and algorithms

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

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.

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

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

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:

• 전산학 석사 이상 혹은 그에 준하는 유관 분야 전공 학위를 소유하고 계신 분 (졸업 예정자 분도 가능합니다)

Responsibilities:

• 사용자의 정보 탐색 과정을 효과적으로 돕기 위해 서비스에 적용되는 AI 모델 및 파이프라인의 전반적인 성능은 사용자 경험에 핵심적인 영향을 미칩니다.

• 머신러닝 리서치 엔지니어는 서비스 사용자의 요구사항을 이해하고 정보 인출 (Information Retrieval) 및 대형 언어 모델 (Large Language Model)을 개발하며, 다양한 상황과 제약조건에 적합한 ML 모델의 학습, 추론방법을 결정할 수 있으며, 학습 및 평가 데이터 디자인에 대한 적절한 의견을 제시할 수 있습니다.

• 서비스에 적용되는 핵심적인 기술이 아닌 영역이 아니면서 회사 차원의 기술적 방향성과 걸맞는 부분에 대해서 팀 차원의 연구 프로젝트를 진행하고 Top Tier 컨퍼런스 논문을 출판하기도 합니다.

Benefits:

• Interesting and challenging work

• Work-life balance

• Competitive salary and equity

• Employee-friendly equity terms (early exercise, extended exercise)

• We are currently hiring in downtown San Francisco. We prefer to work in-person but we also offer remote work opportunities for exceptional candidates.

Education Requirements:

• Masters or PhD

Responsibilities:

• Conduct research on advanced machine learning models, particularly in computer vision.

• Develop and fine-tune models using state-of-the-art techniques.

• Collaborate with our engineering team to integrate research findings into our platform.

• Contribute to open-source projects and share your findings with the broader AI community.

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.

Experience Requirements:

• Experience working as a mechanic or panel beater in cars' technical maintenance stations, or as a car accident commissioner for an insurance company.

• Deep understanding of vehicle functioning and possible damages that can occur during car incidents (both inside and outside).

Responsibilities:

• Reviewing car images to identify and mark damages for the purpose of AI learning.

• Checking the AI algorithm's output to ensure its proper education by reviewing the results of image processing.

• Supporting automotive product development projects as an expert in the field.

Benefits:

• Supportive team environment

• flexible schedule

Education Requirements:

• BSc/BA in Engineering, Computer Science, or a relevant field

Experience Requirements:

• At least 2 years of proven experience as a data analyst

Responsibilities:

• Develop and enhance the analytics dashboard for deeper insights.

• Design, implement, and manage ETL processes to extract data from various sources, transform it for analysis, and load it into our databases.

• Generate internal daily reports and dashboards for comprehensive business analysis, ensuring data accuracy and accessibility for decision-making.

• Collate information from business stakeholders to generate insightful reports.

• Conduct A/B testing to analyze and improve product performance.

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:

• 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.

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.

Benefits:

• Competitive compensation package that includes salary and equity.

• Comprehensive health benefits: Medical, Dental, and Vision (covered 100% for the employees).

• 401(k) plan.

• Open (unlimited) PTO policy.

• Free lunches and dinners at our offices.

Responsibilities:

• Lead transformative research projects that enhance the Genesis AI platform's capabilities, focusing on generative models for 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 work closely with engineers to ship state-of-the-art models to production.

• Contribute to the research community by publishing some of our findings in the form of research papers and blog posts at top tier AI/ML venues (NeurIPS, ICML, ICLR, etc.), attending conferences and workshops, and engaging in continuous learning and knowledge exchange.

Education Requirements:

• PhD in Computer Science, Machine Learning, Physics, or a related field.

Experience Requirements:

• 4+ years of professional experience in machine learning research, with at least 1+ years in a tech or people leadership role.

Responsibilities:

• Develop and implement the strategic vision for an ML Research team, ensuring alignment with company goals.

• Serve as a thought leader in state-of-the art ML research, using the latest approaches in diffusion models, equivariant neural nets and predictive ML

• Guide the team in designing, implementing, and validating novel machine learning models tailored to drug discovery challenges, including molecular property prediction, generative modeling, and protein-ligand interactions.

• Prioritize and balance short-term project deliverables with long-term foundational research initiatives.

• Ensure high standards of scientific rigor and reproducibility in research outputs.

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:

• PhD in Computational Chemistry, Structural Biology, or a related field.

Experience Requirements:

• Minimum of 1-2 years of industry experience as a CADD scientist in pharma or biotech, with hands-on experience in active drug discovery programs.

Responsibilities:

• Utilize a combination of industry-standard and proprietary AI-powered CADD tools to guide small molecule drug discovery programs across a diverse target portfolio, including novel targets with limited chemical precedents.

• Use approaches like virtual screening, molecular simulation, and potency and ADMET prediction to support key decision-making in drug discovery efforts.

• Collaborate closely with medicinal chemists in molecular design and the development of project-specific computational approaches.

• Act as a cross-team connector, effectively communicating between our computational chemistry and medicinal chemistry teams to ensure seamless information flow and collaborative decision making.

Education Requirements:

• PhD in Computer Science, Machine Learning, Physics, or a related field.

Experience Requirements:

• 4+ years of professional experience in machine learning research, with at least 1+ years in a tech or people leadership role.

Responsibilities:

• Develop and implement the strategic vision for the ML Research group, ensuring alignment with company goals.

• Serve as a thought leader in state-of-the art ML research, using the latest approaches in diffusion models, equivariant neural nets and predictive ML

• Guide the team in designing, implementing, and validating novel machine learning models tailored to drug discovery challenges, including molecular property prediction, generative modeling, and protein-ligand interactions.

• Prioritize and balance short-term project deliverables with long-term foundational research initiatives.

• Ensure high standards of scientific rigor and reproducibility in research outputs.