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.

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.

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.

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.

Responsibilities:

• Working with a small team of engineers, designers, and data scientists to ideate, design, and build a new product.

• Experimenting with new techniques to improve our transcreation algorithms.

• Thinking creatively to propose new methods of boosting the quality of the transcreated campaigns.

• Adapting the models to adjust to the requirements of different publishing platforms.

• Mentoring your teammates, creating opportunities for their growth, and fostering a collaborative culture.

Benefits:

• Remote first

• Comprehensive benefits

• Learning and development

• Paid time off

Experience Requirements:

• Proven experience as a Prompt Engineer or similar role in AI development.

• Proficient in designing and developing high-quality prompts for AI, particularly in conversational systems.

• Strong knowledge and experience in NLP and AI model fine-tuning.

• Excellent collaborative skills, with the ability to work closely with stakeholders to meet desired outcomes.

• Familiarity with recent advancements in AI technologies, such as Langchain, GPT-Index, and Agent GPT.

Responsibilities:

• Design, develop, and refine prompt patterns for AI applications to facilitate efficient and meaningful conversations.

• Collaborate with stakeholders to identify key prompt requirements and incorporate them into AI design.

• Test, troubleshoot, and optimize prompts to meet desired outcomes and to improve conversational quality and consistency.

• Design, develop, and maintain natural language processing (NLP) models, particularly for generating high-quality prompts for conversational AI systems such as ChatGPT, AutoGPT, and Turn-based Agents.

Benefits:

• Flexible hours

• Remote work

• Competitive compensation

• Opportunity to learn and work in AI, and to make a positive impact on the development of the AI industry

• Opportunity to expand to other AI-related projects

Experience Requirements:

• Must be eligible to work in United Kingdom

• US English language speaker with good writing and proofreading skills

• Good knowledge of Finance subjects and the ability to craft original responses

• Excellent attention to detail

• A learning mindset - no prior experience in AI is needed

Responsibilities:

• Your main responsibility will be to create, evaluate, and refine pairs of prompts and responses for a sophisticated LLM.

Responsibilities:

• Training large scale Diffusion (transformer) models for image and video

• Rigorously ablating design choices and communicating results & decisions with the broader team

• Reasoning about the speed and quality trade-offs of neural network architectures

Responsibilities:

• Run the development and training of state-of-the-art multimodal vision-language models within the FLUX technology stack

• Design and implement specialized fine-tuning strategies for VLMs to address specific use cases and performance requirements

• Develop and optimize LLM implementations for prompt enhancement, content moderation, and novel applications

Experience Requirements:

• 4+ Years Exp.

• Programming Languages: Python, R, or Java

• Data Analysis and Modeling: sci-kit-learn, TensorFlow, PyTorch

• Database and Data Manipulation: Big data technologies like Apache Spark

• Data Visualization: Tableau, Matplotlib, or Seaborn.Data Engineering: Understanding of data pipeline architecture and development.Machine Learning Deployment: Knowledge of deploying machine learning models into production. | Docker

Responsibilities:

• Data Science Engineer I - Analyze data, drive insights, and innovate solutions

Benefits:

• Flexible working arrangement remotely or hybrid

Education Requirements:

• Bachelor’s degree in Statistics, Data Science, Computer Science, Mathematics, or a related field

Experience Requirements:

• 3+ years of experience in data analysis, preferably within ESG or Sustainability domain

Other Requirements:

• Proficiency in data analysis tools such as Python, R, or SQL

• Experience with data visualization tools like Power BI, Tableau, or equivalent

• Strong statistical knowledge and the ability to interpret complex data sets

• Excellent communication skills with the ability to translate data insights into business recommendations

• Ability to work both independently and as part of a team

Responsibilities:

• Perform detailed analysis on structured and unstructured datasets to identify trends, correlations, and insights

• Work closely with cross-functional teams to understand data requirements and business objectives

• Use statistical techniques to interpret and visualize data trends

• Generate reports and dashboards to communicate findings to stakeholders

• Identify and suggest improvements in data collection, reporting, and analysis processes