ai research scientist

Wells Fargo

<div><p><b>About this role:</b></p><p>
Wells Fargo&rsquo;s Model Risk Management (MRM) team is seeking a Senior Quantitative Analytics Specialist (<b>AI</b><b> Research Scientist &ndash; Foundation Models &amp; Agentic AI</b> ) to support the cutting-edge applied research and development initiatives in Artificial Intelligence, with a focus on building the next generation of Foundation Models, Agentic AI solutions, and Generative AI systems. This role offers a unique opportunity to work at the intersection of AI research and real-world financial applications that impact millions of customers.</p><p></p><p><b>
In this role, you will:</b></p><ul><li><p>
Perform highly complex research projects in AI / Generative AI / Agentic AI / Machine Learning from ideation, experimentation, implementation, evaluation and documentation.</p></li><li><p>
Support building the next generation of foundation models and agentic AI systems - exploration, application, and rigorous evaluation of emerging AI technologies that solve real-world challenges.</p></li><li><p>
Collaborate closely with interdisciplinary teams, including researchers, data scientists, applied engineers, and domain experts.</p></li><li><p>
Translate research insights into impactful business solutions, open-source contributions, patents, and publications.</p></li><li><p>
Contribute to building the next generation of foundation models and agentic AI systems trained / operating on large volumes of heterogeneous data - both structured and unstructured - that enhance Wells Fargo's products, services, and operations.</p></li><li><p>
Publish in top-tier AI/ML conferences and journals and represent Wells Fargo in the broader AI research community.</p></li></ul><p></p><p><b>
Required Qualifications:</b></p><ul><li><p>
4+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education</p></li><li><p>
Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science</p></li></ul><p><b><br>
Desired Qualifications:</b></p><ul><li><p><b>
PhD</b> in Computer Science, Artificial Intelligence, or a closely related computational field, or an MSc with at least 3 years of relevant applied research or industry experience.</p></li><li><p>
Solid proven research track record with <b>publications</b> in top-tier AI/ML conferences such as NeurIPS, ICML, ICLR, NAACL, or EMNLP, combined with a demonstrated interest in translating research into real-world applications that impact millions of customers.</p></li><li><p>
Deep expertise in one or more specialized areas, including but not limited to: <b>Foundation Models</b> (GPT-4, BERT, LLaMA, Claude), Large Language Models (LLMs), Large Reasoning Models, Multimodal Models, Agentic AI</p></li><li><p>
Demonstrated ability to apply GenAI / <b>Agentic AI</b> in the full build lifecycle - design, implementation, testing, and iteration - leveraging AI coding copilots (e.g., GitHub Copilot) and agentic coding workflows to accelerate delivery while maintaining enterprise standards</p></li><li><p>
Hands-on experience with GPU infrastructure, Transformer architecture, modern AI/ML development frameworks and tools such as TensorFlow, <b>PyTorch, Hugging Face</b>, AWS, GCP.</p></li><li><p>
Strong engineering background with demonstrated ability to contribute to collaborative software engineering projects, including version control, code reviews, and scalable system design.</p></li><li><p>
Experience with transferring foundation models, LLMs, and agentic AI systems in production</p></li></ul><p></p><p><b>
Job Expectations:</b></p><ul><li><p>
This position offers a hybrid work schedule</p></li><li><p>
Willingness to work onsite at stated location on the job posting</p></li><li><p>
This position is eligible for VISA sponsorship</p></li></ul><p></p><p><b>
Job Posting Locations:
</b></p><ul><li><p>Three Wells Fargo Center, CHARLOTTE, NC</p></li><li><p>
600 Wells Fargo, MINNEAPOLIS, MN</p></li><li><p>
Las Colinas Bldg B, Irving Campus, IRVING, TX</p></li><li><p>
West Des Moines Campus, 800 S Jordan Creek Pkwy, WEST DES MOINES, IA</p></li><li><p>
D Building,114N Beaumont St -D Bldg., SAINT LOUIS, MO</p></li><li><p>
1150 W Washington, TEMPE, AZ</p></li><li><p>
333 Market, SAN FRANCISCO, CA</p></li></ul><p></p><p><b>
Pay Range</b></p><p><br>
Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to demonstrated examples of prior performance, skills, experience, or work location. Employees may also be eligible for incentive opportunities.</p>
$139,000.00 - $260,000.00<p></p><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p><b>
Benefits
</b></p><p></p><p>Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits - Wells Fargo Jobs for an overview of the following benefit plans and programs offered to employees.</p><ul><li>
Health benefits</li><li>
401(k) Plan</li><li>
Paid time off</li><li>
Disability benefits</li><li>
Life insurance, critical illness insurance, and accident insurance</li><li>
Parental leave</li><li>
Critical caregiving leave</li><li>
Discounts and savings</li><li>
Commuter benefits</li><li>
Tuition reimbursement</li><li>
Scholarships for dependent children</li><li>
Adoption reimbursement</li></ul></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><p></p><p><b>
Posting End Date:</b></p><p></p>
28 Jun 2026<ul><li><b><i>Job posting may come down early due to volume of applicants.</i></b></li></ul><p></p><p><b>
We Value Equal Opportunity</b></p><p></p><p>
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.</p><p></p><p>
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit&rsquo;s risk appetite and all risk and compliance program requirements.</p><p></p><p><b>
Applicants with Disabilities</b></p><p></p><p>
To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.</p><p></p><p><b>
Drug and Alcohol Policy</b></p><p></p><p><br>
Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.</p><p></p><p><b>
Wells Fargo Recruitment and Hiring Requirements:</b></p><p></p><p>
a. Third-Party recordings are prohibited unless authorized by Wells Fargo.</p><p>
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.</p></div><p></p>

Senior AI Research Scientist – Foundation Models & Agentic AI

University of Alabama, Birmingham

<div></div><div><div><div><div><div><b>Description</b><div></div><p><b>
Position Summary</b></p><p>
The University of Alabama at Birmingham, Systems Pharmacology AI Research Center (SPARC), is in search of a Scientist II to join their team. This role is designed for an early-career researcher who recently completed (preferably within the last 10 years) a PhD in biomedical informatics, computing, data science, artificial intelligence, or a closely related field. The selected candidate will develop novel AI models and software systems that form essential components of SPARC's AI-accelerated drug discovery pipeline, conduct in silico computational research, and partner with experimental collaborators in a lab-in-the-loop mode with UAB, regional, and national groups. The Scientist II is expected to contribute meaningfully to obtaining AI drug discovery research funding as a Co-Investigator on grant proposals, to perform SPARC service activities not covered by existing external funding, and to author scientific manuscripts and progress reports. Active research areas include protein and antibody design, novel AI approaches to molecular dynamics simulations, agentic AI and autonomous systems for science, clinical trial simulations, virtual cell modeling, multi-modal drug discovery, retrosynthesis, and AI for science more broadly. SPARC offers a collaborative, computationally rich environment with GPU/HPC infrastructure, large biomedical data assets, and tight partnerships across the UAB School of Medicine. To fully appreciate the scope of this Scientist II position, it is essential to underscore SPARC's expectation that the incumbent will develop novel AI models and software systems that become essential components of the center's AI-accelerated drug discovery pipeline, perform genuine in silico research, and partner with experimental and clinical collaborators in a lab-in-the-loop mode with UAB, regional, and national groups. The Scientist II is also expected to contribute as a Co-Investigator to extramural grant proposals that obtain AI drug discovery research funding, to perform SPARC service work not covered by existing external funding, to author scientific manuscripts and progress reports, and to develop active research collaborations. Excellent office, programming, and written/verbal communication skills are essential.</p><p></p><p><b><br>
General Responsibilities</b></p><ul><li><p>
To employ a broad knowledge of principles, practices and procedures in a particular field of specialization.</p></li><li><p>
To plan, design and conduct research and present findings.</p></li></ul><p><b>
Key Duties &amp; Responsibilities</b></p><ul><li><p>
Develop Novel AI Models and Software Systems for the AI-Accelerated Drug Discovery Pipeline: Design, implement, benchmark, and ship novel AI/ML models and reusable software components that become essential building blocks of SPARC's AI-accelerated drug discovery pipeline spanning protein/antibody design, AI for molecular dynamics, virtual cell modeling, multi-modal drug discovery, retrosynthesis, agentic AI, and clinical trial simulation.</p></li><li><p>
Perform In Silico and Lab-in-the-Loop Research Studies: Conduct computational research studies and partner with experimental collaborators at UAB, regional, and national institutions in a lab-in-the-loop mode, iterating between AI predictions and wet-lab or clinical validation to accelerate scientific discovery.</p></li><li><p>
Obtain Research Funding as Co-Investigator on AI Drug Discovery Grants: Contribute substantively to extramural grant proposals (NIH, NSF, DOD, foundation, and industry) as a Co-Investigator, drafting aims, preliminary data, computational specifications, and budget components to secure AI drug discovery research funding for SPARC.</p></li><li><p>
Provide SPARC Center Service Not Covered by External Funding: Perform technical, infrastructure, and project-support service activities for SPARC initiatives that are not already covered by external funding, including shared codebases, model registries, GPU/HPC workflows, reproducibility tooling, and internal pilot studies.</p></li><li><p>
Author Scientific Manuscripts and Progress Reports: Draft and submit manuscripts to peer-reviewed venues; prepare progress reports for sponsors and internal SPARC leadership; contribute to grant-renewal documentation and conference presentations.</p></li><li><p>
Develop Active Research Collaborations Across UAB and Beyond: Initiate and sustain active research collaborations with UAB faculty, regional research institutions, and national academic and industry partners. Represent SPARC at scientific meetings and joint working sessions.</p></li><li><p>
Mentor and Train Junior Researchers: Mentor undergraduate students, graduate trainees, and post-doctoral fellows in modern AI methods, computational reproducibility, and scientific communication.</p></li><li><p>
Perform other duties as assigned.</p></li></ul><p></p><p><b><br>
Salary Range</b><b>:</b> $ 74,100- $ 120,700</p><p></p><div><br>
</div></div><div><b>
Qualifications</b><div></div><p><b>
Qualifications</b></p><div>
Doctor of Philosophy, D.V.M. or M.D. degree in a related field and four (4) years of related experience OR M.D. and Master's degree and two (2) years of related experience OR Master's degree and six (6) years of related experience OR Bachelor's degree and eight (8) years of related experience required. <b>Work experience may NOT substitute for education requirement.</b></div><div></div><div><b><br>
Preferences</b></div><ul><li><p>
Doctor of Philosophy (PhD) in biomedical informatics, computing, computer science, data science, artificial intelligence, or a closely related field.</p></li><li><p>
PhD completed within the last 10 years preferred.</p></li></ul><p><br>
UAB is an Equal Employment/Equal Educational Opportunity Institution dedicated to providing equal opportunities and equal access to all individuals regardless of race, color, religion, ethnic or national origin, sex (including pregnancy), genetic information, age, disability, and veteran's status. As required by Title IX, UAB prohibits sex discrimination in any education program or activity that it operates. Individuals may report concerns or questions to UAB's Assistant Vice President and Senior Title IX Coordinator. The Title IX notice of nondiscrimination is located at uab.edu/titleix.</p><div><br>
</div></div><div><b>
Primary Location</b><b>:</b> University</div><div><b>
Job Category</b><b>:</b> Scientific Research</div><div><b>
Organization</b><b>:</b> 393001000 Systems Pharmacology AI Research Center (SPARC)</div><div><b>
Employee Status</b><b>:</b> Regular</div><div><b>
Shift</b><b>:</b> Day/1st Shift</div><div><b>
Work Arrangement (final schedule to be determined by the department/hiring manager)</b><b>:</b> Onsite</div></div></div></div></div><div></div>

SCIENTIST II

Promptwatch

<div>
 Data Scientist
 <br/>
 <br/>
 Amsterdam
 <br/>
 Full-time
 <br/>
 Medior-Senior (4+ YOE)
 <br/>
 &euro;60,000 - &euro;85,000
 <br/>
 <br/>
 Promptwatch sits on one of the richest datasets in AI Search: real AI responses across ChatGPT, Claude, Gemini, and Perplexity, combined with billions of crawler logs and clicks. We ingest around 2,000 events per second of crawler logs, CDN data, and clickstream data, on top of huge volumes of unstructured AI response text. As a Data Scientist, you'll turn this data into the metrics, models, and insights that define how agentic AI Search is measured and improved.
 <br/>
 <br/>
 This is a high-impact, hands-on role. You'll work closely with Product and Engineering to design visibility and sentiment metrics, surface trends across millions of AI answers, and build the analytical foundation that our customers and our public research rely on. Working with large amounts of unstructured data, vector search, and embeddings is at the heart of the role.
 <br/>
 <br/>
 What You'll Do:
 <br/>
 <br/>
 Design and refine metrics for brand visibility, citations, and sentiment across AI assistants
 <br/>
 Analyze large-scale, high-velocity datasets (~2,000 events/second of crawler logs, CDN, and clickstream data) to surface actionable trends
 <br/>
 Make sense of large amounts of unstructured AI response text using embeddings and vector search
 <br/>
 Build statistical and ML models to detect patterns in how AI systems retrieve, rank, and cite content
 <br/>
 Develop reproducible analyses and pipelines that scale with our growing dataset
 <br/>
 Produce public-facing research and reports that establish Promptwatch as a thought leader in AI search space.
 <br/>
 Validate data quality and define methodologies that customers can trust
 <br/>
 What
 <br/>
 <br/>
 We're Looking For:
 <br/>
 <br/>
 4+ years experience in data science, analytics, or a quantitative research role
 <br/>
 Strong proficiency in Python and SQL for data analysis
 <br/>
 Solid foundation in statistics, experimentation, and ML fundamentals
 <br/>
 Experience working with large, messy, real-world datasets, including high volumes of unstructured text
 <br/>
 Hands-on experience with vector search and embeddings
 <br/>
 Ability to translate ambiguous questions into clear, measurable analyses
 <br/>
 Strong communication skills to present findings to technical and non-technical audiences
 <br/>
 Curious and excited about AI, search, and emerging buyer behavior
 <br/>
 Familiarity with data warehouses and analytics tooling (e.g. BigQuery, Tinybird/ClickHouse, Elasticsearch)
 <br/>
 <br/>
 Nice to Have:
 <br/>
 <br/>
 Experience with NLP or working with LLM outputs
 <br/>
 Background in SEO, search, or marketing analytics
 <br/>
 Experience building data visualizations or dashboards
 <br/>
 <br/>
 Compensation
 <br/>
 Salary: &euro;60,000 - &euro;85,000 (depending on experience)
 <br/>
 <br/>
 Perks: Great office location, team off-sites, company and team sports activities
</div>


Data Scientist

Oracle

<div><p>The IC5 Applied Scientist for Robotics, Perception, and Embodied AI will serve as a senior technical leader responsible for defining, prototyping, and delivering AI capabilities for commercially viable robotic systems. This role partners across science, software engineering, product, and hardware teams to identify high-impact opportunities, translate ambiguous product needs into research and engineering roadmaps, and guide end-to-end solution development from data collection and experimentation through production deployment. The scientist will lead applied research in multi-sensor fusion, real-time signals, perception, multimodal reasoning,
<br>
reinforcement learning, and action-conditioned planning, with a strong bias for hands-on execution and full-stack delivery.</p></div>
<br><div><h1 class="jobSectionHeader"><b>Key Responsibilities
</b></h1><h2 class="jobSectionHeader"><b>Solution Identification and Strategy
</b></h2><ul><li><p>Partner with science, engineering, product, and hardware leaders to identify strategic product needs where robotics, perception, and embodied AI can create measurable customer and business impact.
</p></li><li><p>Evaluate academic literature, industry benchmarks, robotics platforms, and commercially viable robot APIs to assess feasibility, technical difficulty, and delivery risks.
</p></li><li><p>Break down ambiguous robotics and AI problems into clear research plans, model architectures, data requirements, evaluation criteria, and production milestones.
</p></li><li><p>Set science quality standards for applied robotics workstreams, including perception accuracy, latency, robustness, safety, reliability, and operational feedback metrics.
</p></li><li><p>Prioritize solutions using the scientific process, including modeling approaches, evaluation techniques, data collection strategies, and risk/reward tradeoffs.
</p></li></ul><h2 class="jobSectionHeader"><b>Applied Research and Model Development
</b></h2><ul><li><p>Lead the design and execution of research programs and POCs for sensors, multi-sensor fusion, real-time signal processing, and perception systems.
</p></li><li><p>Develop and guide approaches for object detection, tracking, activity recognition, scene understanding, and related perception capabilities in real-world environments.
</p></li><li><p>Advance multimodal AI systems that combine signals such as camera, depth, lidar, audio, telemetry, proprioception, and task context.
</p></li><li><p>Apply reinforcement learning, action-conditioned planning, decision-making, and reasoning methods to enable robot behaviors that are robust, measurable, and product-relevant.
</p></li><li><p>Define dataset strategy, data quality criteria, labeling approaches, simulation or synthetic data opportunities, and evaluation protocols for robotics and embodied AI use cases.
</p></li><li><p>Guide model training, fine-tuning, optimization, inference design, and compute/latency tradeoffs for real-time or near-real-time deployment scenarios.
</p></li></ul><h2 class="jobSectionHeader"><b>Solution Delivery and Production Integration
</b></h2><ul><li><p>Lead full-stack execution across experimentation, data pipelines, model development, evaluation, deployment integration, and production monitoring.
</p></li><li><p>Partner closely with software engineering, machine learning engineering, hardware teams, and product stakeholders to integrate AI capabilities into robotic systems and services.
</p></li><li><p>Evaluate and review high-complexity code, establish best practices for repositories, version control, code review, documentation, testing, and delivery readiness.
</p></li><li><p>Define operational metrics and user feedback loops to assess delivered solutions in production and inform future technical strategy.
</p></li><li><p>Serve as an escalation point for complex robotics, AI, perception, and systems integration issues, driving root-cause analysis and durable solutions.
</p></li></ul><h2 class="jobSectionHeader"><b>Research Leadership and Influence
</b></h2><ul><li><p>Demonstrate thought leadership in at least one business-critical area such as robot perception, multimodal systems, sensor fusion, reinforcement learning, or embodied AI.
</p></li><li><p>Translate research insights into clear technical recommendations, patents, white papers, design documents, demos, or conference-quality publications where appropriate.
</p></li><li><p>Mentor and guide scientists and engineers, raising the bar for applied research rigor, experimentation quality, and production readiness.
</p></li><li><p>Establish productive collaborations with internal teams, external research groups, academic partners, or commercial robotics ecosystem partners where relevant.
</p></li></ul><h1 class="jobSectionHeader"><b>Core Competencies
</b></h1><ul><li><p>Bias for action with a strong hands-on orientation; able to move from ambiguous idea to prototype, evaluation, and production path quickly.
</p></li><li><p>Ability to execute full-stack AI workflows spanning data, experimentation, modeling, evaluation, APIs, deployment, and feedback loops.
</p></li><li><p>Strong cross-functional collaboration with hardware teams, software engineering, ML engineering, product, operations, and leadership stakeholders.
</p></li><li><p>Excellent judgment in balancing scientific rigor, product urgency, systems constraints, safety, reliability, and customer impact.
</p></li><li><p>Clear executive-level communication; able to explain complex robotics and AI tradeoffs to technical and non-technical audiences.
</p></li></ul><h1 class="jobSectionHeader"><b>Required Technical Expertise
</b></h1><ul><li><p>Deep experience in machine learning, artificial intelligence, computer vision, perception, robotics, sensor fusion, real-time signal processing, or a closely related field.
</p></li><li><p>Experience with perception capabilities such as object detection, tracking, activity recognition, scene understanding, localization, or state estimation.
</p></li><li><p>Experience designing multimodal AI systems that combine heterogeneous data sources and reason over context, actions, and temporal signals.
</p></li><li><p>Practical knowledge of reinforcement learning, planning, sequential decision-making, robotics control interfaces, or action-conditioned model behavior.
</p></li><li><p>Strong programming capability in applicable languages such as Python and/or C++, and experience with modern ML frameworks and production-oriented software practices.
</p></li><li><p>Familiarity with APIs, SDKs, or integration patterns from commercially viable robotics platforms.
</p></li></ul><h1 class="jobSectionHeader"><b>Minimum Qualifications
</b></h1><ul><li><p>15 years of experience in data science, machine learning, artificial intelligence, robotics, computer vision, signal processing, statistical modeling, data mining, or a related field; OR
</p></li><li><p>Bachelor's degree in Mathematics, Statistics, Computer Science, Data Science, Physics, Robotics, Electrical Engineering, Mechanical Engineering, or related field and 11 years of relevant experience; OR
</p></li><li><p>Master's degree in one of the above or related fields and 9 years of relevant experience; OR
</p></li><li><p>Doctorate in one of the above or related fields and 7 years of relevant experience.
</p></li><li><p>7+ years of hands-on experience with Python, C++, PyTorch, and ROS for software development, machine learning, and robotics applications.
</p></li><li><p>Demonstrated technical leadership guiding teams and stakeholders toward strategic goals.
</p></li></ul><h1 class="jobSectionHeader"><b>Preferred Qualifications
</b></h1><ul><li><p>16 years of experience in data science, machine learning, artificial intelligence, robotics, computer vision, perception, signal processing, or related field; OR equivalent degree-based experience aligned to Oracle IC5 guidelines.
</p></li><li><p>2 years of leadership experience with or without direct reports, including technical direction, mentoring, project planning, or cross-functional execution.
</p></li><li><p>2 years of experience working with operating budgets and/or project financials, where applicable.
</p></li><li><p>5+ years of experience creating technical publications, patents, white papers, peer-reviewed conference or journal articles, or equivalent technical documentation.
</p></li><li><p>Demonstrated experience delivering robotics, embodied AI, perception, or multimodal systems from research concept into production or customer-facing environments.
</p></li><li><p>Hands-on experience with commercial robot platforms, robot SDKs/APIs, simulation environments, telemetry pipelines, and real-time deployment constraints.
</p></li></ul><h1 class="jobSectionHeader"><b>Success Profile
</b></h1><ul><li><p>Builds credibility as a senior applied science leader who can bridge research depth with pragmatic product delivery.
</p></li><li><p>Operates comfortably across sensors, models, APIs, hardware/software boundaries, and executive decision-making forums.
</p></li><li><p>Raises the bar for AI adoption in robotics by creating reusable patterns, evaluation standards, and scalable delivery practices.</p></li></ul></div><p></p>

Lead Principal Applied Scientist - Robotics

Lorien

<div>
 <p>
  <strong>
   Data Scientist / Machine Learning Scientist - Outside IR35
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Location:
  </strong>
  London (Hybrid)
 </p>
 <p>
  <strong>
   Length:
  </strong>
  6 months
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Ready to build and deploy real AI systems at scale?
  </strong>
 </p>
 <p>
  Join a growing AI teams, where you&rsquo;ll shape how AI transforms global business. We&rsquo;re hiring hands-on operators who deliver production-ready LLM and agentic solutions&mdash;not just prototypes.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What You&rsquo;ll Do:
  </strong>
 </p>
 <ul>
  <li>
   Design and build AI agents and agentic workflows powered by LLMs (retrieval, reasoning, tool orchestration)
  </li>
  <li>
   Develop multi-step intelligent systems for planning, memory, and real-world tool usage
  </li>
  <li>
   Deliver recommendation, classification, and forecasting systems on large-scale datasets
  </li>
  <li>
   Automate complex workflows and decision-making, driving measurable business impact
  </li>
  <li>
   Own problems end-to-end: from exploration to production deployment and iteration
  </li>
  <li>
   Integrate AI into products, APIs, and business processes for scalable, reliable solutions
  </li>
  <li>
   Collaborate with engineering to ensure robust, observable, and maintainable systems
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What You&rsquo;ll Bring:
  </strong>
 </p>
 <ul>
  <li>
   Strong Python skills and production-grade coding experience
  </li>
  <li>
   Proven track record shipping LLM-powered systems (LangChain/LangGraph or similar) into production
  </li>
  <li>
   Hands-on experience with AI agents, agentic workflows, and multi-step reasoning
  </li>
  <li>
   Experience designing and implementing RAG systems with real-world impact
  </li>
  <li>
   Familiarity with MCP or similar orchestration patterns (FastMCP/FastAPI)
  </li>
  <li>
   Understanding of LLM limitations and trade-offs (hallucination, latency, cost)
  </li>
  <li>
   Cloud deployment experience (AWS, GCP, Azure)
  </li>
  <li>
   Masters or higher in Maths, Science, or Computer Science
  </li>
  <li>
   Ownership mindset, bias for action, and strong product focus
  </li>
  <li>
   Comfortable in fast-moving, ambiguous environments
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Bonus Points:
  </strong>
 </p>
 <ul>
  <li>
   Experience with SaaS/B2B AI products or AI-driven business transformation
  </li>
  <li>
   Background in high-growth/scaling environments
  </li>
  <li>
   Evidence of systems delivering real value in production
  </li>
 </ul>
</div>


InterVenn Biosciences

<div><p>At InterVenn, our technology enables and empowers the understanding of glycoproteomics, a new clinical layer of biology beyond the genome, using a simple blood draw. InterVenn&rsquo;s powerful solutions will broaden humankind&rsquo;s perception and interpretation of diseases like cancer. We look forward to having new members join our team who have diverse perspectives and backgrounds, challenge the status quo, and are solution oriented.</p><p></p><p><br>
We are seeking a creative, methodologically rigorous Senior Data Scientist to push the frontier of how we research and build classifiers from glycoproteomic data. This is a research-forward individual contributor role for someone who reaches across the full breadth of modern statistical and AI methods &mdash; classical ML, deep learning, foundation models for biology, generative approaches, and whatever the literature surfaces next &mdash; and is energized by open problems: new quantification and normalization schemes, novel feature engineering, multimodal model architectures, and the biological interpretation of model outputs.</p><p></p><p><b><br>
RESPONSIBILITIES</b></p>
<ul>
<li>Design, prototype, and rigorously evaluate novel classifier architectures for clinical diagnostics across oncology indications</li>
<li>Lead exploratory research into new quantification, normalization, and feature engineering methods for high-dimensional glycoproteomic data</li>
<li>Bring a diverse modeling toolkit &mdash; classical statistical methods, tree-based ensembles, deep learning, probabilistic and Bayesian approaches, foundation models, graph neural networks, and generative AI &mdash; and choose the right tool for the problem based on evidence rather than habit or hype</li>
<li>Develop cross-validation, calibration, and uncertainty-quantification strategies that hold up to the realities of small clinical cohorts and high feature counts</li>
<li>Investigate and mitigate batch, cohort, and site effects so that models generalize from discovery to bridging to locked panels</li>
<li>Drive cross-indication synthesis &mdash; separate shared disease biology from indication-conditioned signal, and from nonspecific inflammatory or acute-phase axes</li>
<li>Build multimodal models that combine glycan/motif information, proteomic grounding, and clinical covariates rather than relying on protein-quantity signal alone</li>
<li>Translate emerging techniques from the ML, AI, and computational-biology literature into production-ready methods</li>
<li>Mentor junior data scientists and raise the methodological bar across the team</li></ul><br>
<p></p>
<p><b>
QUALIFICATIONS</b></p>
<ul>
<li>Ph.D. in Statistics, Computer Science, Computational Biology, Bioinformatics, or a related quantitative field, plus 6+ years of experience building predictive models on biological data in industry or academia; alternatively, an MS in a similar field with 8+ years of relevant experience</li>
<li>Demonstrated track record of methodological innovation &mdash; first-author publications, novel methods deployed in production, open-source contributions, or comparable evidence of original work</li>
<li>Deep proficiency in Python and/or R, including the modern ML stack (scikit-learn, PyTorch or TensorFlow, XGBoost/LightGBM, and similar)</li>
<li>Methodological breadth across paradigms &mdash; comfortable moving between classical statistics, tree-based ML, deep learning, and modern AI (transformers, graph neural networks, foundation models, generative methods) &mdash; and the judgment to argue rigorously for one approach over another</li>
<li>Strong statistical foundation: cross-validation strategy, regularization, calibration, uncertainty quantification, and handling of confounders and class imbalance</li>
<li>Hands-on experience building and validating classifiers on high-dimensional, low-sample-size biological data (proteomics, glycoproteomics, transcriptomics, or genomics)</li>
<li>Experience with batch-effect correction and normalization techniques, and a healthy skepticism about how those choices propagate into downstream performance estimates</li>
<li>Preference will be given to candidates with experience in multimodal modeling, interpretability methods, or foundation/representation-learning approaches for biological data</li>
<li>Familiarity with clinical diagnostic development &mdash; analytical and clinical validation, locking classifiers, and bridging studies &mdash; is a strong plus</li>
<li>Excellent written and verbal communication: able to explain novel methods clearly to wet-lab scientists, clinicians, and fellow statisticians alike</li>
<li>A genuine desire to impact patient lives and contribute to the broader scientific community</li></ul></div>

Senior Data Scientist

Basecamp Research

<div><h2 class="jobSectionHeader"><b>About Us</b></h2><p>
Basecamp Research is dedicated to solving major challenges in the life sciences by exploring Beyond Known Biology. Our teams build frontier AI models using BaseData, the world's largest ethically-sourced and globally representative biological dataset. Our Global Research Team collects and curates our own biological data through partnerships with more than 152 organizations in 28 countries, giving its AI access to genetic diversity that doesn't exist for models trained on public database sources. This enables Basecamp Research to design novel protein sequences and biological systems that can accelerate therapeutic research and development.</p><p>
In October 2024 we closed Series B and in January 2026 finalised pre-Series C investment from NVIDIA. With hubs both in London, UK as well as Boston Massachusetts, USA and partners with biopharma companies and academic institutions worldwide, our work has been recognized with honors including Fast Company's Top 10 Most Innovative Companies in Biotech and the FT-backed Sifted AI100 list of Europe's leading AI startups.</p><p>
At Basecamp Research, we pride ourselves on being a diverse, exciting, fun, and flexible place to work. Our team of biologists, engineers, ML scientists, field explorers, and operations specialists are united by a sense of adventure and the belief that nature has already designed the solutions to our planet's greatest challenges. If you feel passionate about the power of biology, data, and AI to build a better world, we'd love to hear from you.</p><p></p><h2 class="jobSectionHeader"><b>
The Role</b></h2><p>
We are looking for a Senior Research Scientist to join our AI Research team in London. You will work at the intersection of mathematics and machine learning, bringing rigorous quantitative thinking to some of the most challenging problems in biological AI.</p><p>
Our research group is small, collaborative, and operates more like a frontier research lab than a typical biotech team. We train large-scale foundation models on the world's largest and richest metagenomic datasets, and we look for people who can push the mathematical boundaries of what these models can learn and represent. The work requires developing new methods and theories from scratch.</p><p>
This is a role with real ownership. You will shape a research direction within the team, publish at top venues, and see your work translated into models that generate genuinely novel biology. The problems are hard, the data is unique, and the impact is tangible.</p><p>
You'll be reporting to the Head of AI Research and working alongside researchers covering genomics, sequence modeling, and large-scale deep learning, as well as biologists, bioinformaticians, and engineers across the wider company.</p><p></p><h2 class="jobSectionHeader"><b>
About You</b></h2><p>
PhD in mathematics, physics, or a closely related quantitative field. Your work in AI and machine learning is driven by curiosity, and you've brought a depth of mathematical thinking that clearly distinguishes your work.</p><p>
You have spent meaningful time on frontier research and you already have an understanding of how top research teams operate, from problem selection to large-scale experimentation to shipping results that matter.</p><p>
Your research interests might span generative models, geometric deep learning, probabilistic modeling, dynamical systems, information geometry, optimization theory, or related areas. What matters most is that you think from first principles and bring mathematical structure to hard problems.</p><p>
You have a strong publication record at top ML venues (NeurIPS, ICML, ICLR, or equivalent) that demonstrates independent thinking and a coherent research arc.</p><p>
You are genuinely curious about biology. Domain expertise is welcome, and what we really care about is that you find it exciting to work with data from unexplored ecosystems encoding billions of years of evolutionary optimization. The best candidates will see biological data as a source of fundamentally new scientific questions.</p><p>
You have low ego, strong collaborative instincts, and a startup mentality. You are comfortable with ambiguity, willing to iterate fast, and happy to work in a small team where everyone contributes across boundaries.</p><p></p><h2 class="jobSectionHeader"><b>
Nice to Have</b></h2><p>
Experience training models at large scale (billions of parameters, extreme long context, distributed training, custom architectures).</p><p>
Domain knowledge in life sciences, genomics, or computational biology, e.g., familiarity with protein structure, molecular dynamics, or related biophysical methods.</p><p></p><h2 class="jobSectionHeader"><b>
What we offer in return</b></h2><ul><li><p><b>
Impactful Mission:</b> This is a rare chance to do work that genuinely matters. You'll join a talented, fast-moving team, access unique biological datasets at scale, and see your contributions shape real breakthroughs in AI and curative therapeutics..</p></li><li><p><b>
Collaborative Culture:</b> You'll be surrounded by world-class engineers, scientists, and researchers who care deeply about their work and about each other. With offices in London and Boston, we've built a flexible, cross-functional environment where personal development and real ownership aren't just talking points.</p></li><li><p><b>
High Growth: </b>We truly believe in investing our people we make coaching available to team members during steep growth journeys and we have twice yearly promotion opportunities. People who are really successful here own it and go directly to solve problems at pace and we ensure reward increases with impact.</p></li><li><p><b>
Comprehensive Benefits:</b> We've built a benefits package people value. That means competitive salary, equity, and private healthcare with no medical history exclusions so strong that means most employees' family members opt into our plan over their own. We also offer Carrot Fertility with IVF stipend, salary sacrifice pension, bike to work scheme, life insurance, and more.</p></li></ul><p>
We are committed to equal opportunity employment regardless of ethnic or national origin, race, religion, sex, age, citizenship, sexual orientation, marital status, disability, gender identity or any other basis. If you have a disability or additional need that needs accommodating do let us know.</p></div>

Senior Research Scientist, Mathematical Foundations

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