AI Jobs

Education Requirements:

• A PhD degree holder in Computer Science or related disciplines.

Other Requirements:

• Excellent verbal and written communication skills in English.

• Extensive knowledge in machine learning and AI algorithms, especially in natural language processing (NLP), speech recognition, and/or related areas is preferred.

• Strong mathematical/analytical foundation, problem solving skills.

• Experience in software developments for machine learning/AI algorithms are highly preferred.

Responsibilities:

• Perform research directed toward investigation, evaluation, and application of known machine learning theories and principles, especially deep learning techniques.

• Plans and conducts, or direct engineering personnel performing complex engineering analyses and experiments to test, prove, or modify theoretical propositions on basis or research findings and experiences of others researching in related technological areas.

• Evaluate findings to develop new concepts, products, or processes, or to develop applications of findings to new uses.

• Write technical papers to be published in prestigious conferences and journals.

• Prepare technical reports for use by engineering or management personnel for long- and short-term planning.

Benefits:

• Competitive salary and benefits package.

• Culture focused on talent development with quarterly promotion cycles and company-sponsored higher education and certifications.

• Opportunity to work with cutting-edge technologies.

• Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards.

• Annual health check-ups.

Education Requirements:

• Bachelor’s degree in computer science, Statistics, Mathematics, or related field.

Experience Requirements:

• Minimum of 5 years of proven experience in delivering Data Science solutions in a professional environment.

Responsibilities:

• Responsible for cleansing, filtering, and refactoring complex data from different sources, further analyzing, and investigating it to identify how they can be used to generate a model with high accuracy.

• Experience is model development and in performing model validation to support the integrity and improve the accuracy of the model

Education Requirements:

• Master's or PhD in Data Science, Computer Science, Statistics, Mathematics, or a related field, or equivalent work experience.

Responsibilities:

• Lead the design, development, and implementation of machine learning models, AI algorithms, and Large Language Models (LLMs) for various business applications.

• Collaborate with cross-functional teams (product, engineering, business) to understand the problem domain and define model objectives.

• Analyze large datasets to identify patterns, trends, and insights, and use these findings to develop predictive models and actionable business solutions.

• Build, test, and refine machine learning models using state-of-the-art techniques, including supervised and unsupervised learning, reinforcement learning, deep learning, and natural language processing (NLP).

• Develop and optimize LLMs (e.g., GPT, BERT, etc.) to improve language understanding, text generation, and other NLP applications.

Education Requirements:

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.

Experience Requirements:

• 5+ years of hands-on experience in machine learning, with a focus on anomaly detection.

Responsibilities:

• Develop and implement machine learning models focused on anomaly detection in industrial IoT data.

• Design algorithms for predictive maintenance and condition monitoring.

• Work closely with data engineers to create robust data pipelines for real-time analytics.

• Analyze large datasets, extract insights, and provide actionable recommendations.

• Optimize models to improve detection accuracy and reduce false positives.

Benefits:

• Health & Commuter Benefits

• Flexible PTO

Education Requirements:

• Degree within Computer Science, Data Engineering, or a related field.

Experience Requirements:

• 2-4+ years of industry experience in applying AI/ML, preferably on well-known consumer data products or services.

• Hands-on experience in delivering production-ready code (Python, Java, etc.)

• Hands-on experience using modern big data pipelines (AWS, Google Cloud, Snowflake)

• AI/ML models, Natural language process (NLP) and data mining experience

Other Requirements:

• Are you ready to work (hybrid) out of our downtown Manhattan office 3 days a week (Tuesday-Thursday)? (no relocation benefits)

• Do you require any form of visa sponsorship or immigration support? (Includes new or transfer H1, O1, PERM, F1-OPT, STEM extensions, etc.)

Responsibilities:

• Process, cleanse, and verify the integrity of data used for downstream analytics products

• Apply advanced machine learning, graph analytics, data mining, statistical methods, algorithms, and time series models to vast amounts of user data to derive insights based on the knowledge graph (ontology)

• Participate in strategic planning and be responsible for the team roadmap and its execution.

Experience Requirements:

• least 5-7 years of experience as a Senior Data Scientist

Benefits:

• Remote-First Culture

• Cutting-Edge Technology

• Growth Opportunities

• Team Collaboration

• Mission-Driven Work

Benefits:

• Remote-First Culture

• Cutting-Edge Technology

• Growth Opportunities

• Team Collaboration

• Mission-Driven Work

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

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.

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:

• 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.

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.

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.

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:

• Remote first

• Comprehensive benefits

• Learning and development

• Paid time off

Benefits:

• Medical/Dental/Vision, 401K match, PTO, and federally recognized holidays

• Competitive salaries with performance incentives

• Generous vacation policy and paid holidays

• Comprehensive health, dental, and vision insurance

• 401(k) with company match

Education Requirements:

• Bachelor's in Intelligence Studies, Computer Science, Data Analytics, or a related field, or an Associate degree with significant operational experience

Experience Requirements:

• At least five years in intelligence analysis within the U.S. intelligence community, preferably with exposure to military or other intelligence sectors

Other Requirements:

• U.S. Citizenship with Top Secret/SCI Clearance

• Must meet ICD 704 eligibility criteria without waivers or conditions

• This role requires a commitment to maintain a Final TOP SECRET SCI Clearance. Dual citizenship is not permitted, and the position mandates sole U.S. citizenship, following strict federal compliance guidelines

Responsibilities:

• bring your sharp analytical skills and extensive intelligence experience to fortify our operations

• be stationed at our client site in Camp Springs, MD, leveraging your expertise in intelligence analysis to navigate complex data landscapes

• Your role will be pivotal in synthesizing actionable insights from varied intelligence sources, including cybersecurity and border security sectors