DATA & AI STAFFING
SAN FRANCISCO

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Title: AI Engineer

Location: Remote, United States

Compensation: Up to $250,000 + Equity

We’re partnered with a mission-driven healthcare technology company working at the intersection of clinical data and AI. They’re reimagining how complex clinical workflows are automated, with a focus on making high-quality healthcare data more accessible, structured, and actionable. This is a company building something genuinely novel in a space where the stakes are high and the impact is real.

This is a high-impact role where you will lead AI innovation from the ground up. You won’t just be implementing models, you’ll own the full lifecycle of production AI systems, define how clinical data is extracted and structured at scale, and influence the company’s long-term AI direction. The work spans LLMs, computer vision, and mixed-modal approaches in a domain where rigor and accuracy are non-negotiable.

What You’ll Do

• Design, develop, and deploy novel AI/ML systems – with a focus on LLMs and computer vision – to recover, extract, and automate clinical data tasks across diverse data types including medical records, imaging, and clinical reports
• Build robust prototypes and transition them to scalable, near-production-ready code, applying strong software engineering fundamentals throughout
• Design and execute rigorous statistical validation and evaluation frameworks, defining performance metrics and ensuring models meet stakeholder-defined accuracy thresholds
• Own the human-in-the-loop (HITL) lifecycle, ensuring deployed models can continuously improve over time through structured feedback capture
• Partner closely with software engineering to bring proof-of-concept solutions into production, contributing to key architectural decisions along the way
• Proactively identify high-impact AI opportunities across the business and define how advanced capabilities can address them
• Champion best practices for documentation, experimentation, and code quality across the model development lifecycle – and potentially mentor others in doing the same
• Actively evaluate state-of-the-art approaches, bringing innovative ideas and methods to the team
• Apply and uphold healthcare data privacy regulations and ethical standards in all AI development work

Requirements

• MSc or PhD in computer science, engineering, applied mathematics, statistics, or a related field; BSc with equivalent demonstrated experience also considered
• 2-5+ years of relevant experience in AI/ML engineering or data science, with increasing scope and responsibility over time
• Deep hands-on Python expertise; polyglot coder comfortable across modern programming languages
• Significant experience with at least one deep learning framework (PyTorch, TensorFlow, etc.) applied to LLMs or computer vision in production contexts
• Proven knowledge of the healthcare data domain in at least one area: EHR/EMR, clinical imaging, clinical workflows, or clinical research
• Extensive experience with modern cloud compute and storage platforms (AWS, Azure, Databricks, Snowflake, etc.)
• Solid understanding of database technologies (SQL, NoSQL, etc.)
• Strong familiarity with SDLC and agile methodologies
• Ability to independently architect end-to-end solutions and clearly communicate how they deliver business value
• Excellent written and verbal communication skills – including the ability to present complex technical concepts to non-technical stakeholders

Nice to Have

• Experience with computer vision or multimodal model development
• Background in clinical research, regulated healthcare environments, or medical data pipelines
• Familiarity with EDC systems or clinical trial data infrastructure
• Experience designing or improving HITL feedback systems in production
• Exposure to AI evaluation frameworks or quality assessment tooling

If you’re interested in shaping how AI systems are built, evaluated, and deployed in high-trust environments, this is an opportunity to have direct influence on both technical direction and real-world impact at a fast-growing company.

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Job Title: Staff Data Scientist

Location: Remote (US Only)

Salary: $200-250k base + equity

About the Company:

Join a mission-focused organization dedicated to revolutionizing global education by providing innovative learning experiences beyond the traditional classroom. The company’s app is widely used across U.S. schools and impacts millions of children worldwide.

Their team is made up of talented and creative professionals with backgrounds in education and top consumer internet companies such as Instagram, Netflix, Dropbox, Stripe, and Uber. They cultivate an environment where top talent can thrive. If you’re eager to work with some of the best minds in the industry, we encourage you to apply!

Position Summary:

As a Staff Data Scientist, you will be a key player in developing the world’s leading consumer education platform. You will be part of a high-achieving, cross-functional team working closely with product, engineering, and design to shape the company’s strategic direction and tackle challenging product and business issues.

Key Responsibilities:

• Utilize data-driven insights to inform decisions and drive our brand toward new milestones
• Work collaboratively with various teams to discover user insights and pinpoint essential product improvements
• Design and analyze AB/multivariate tests to derive actionable conclusions that boost user engagement
• Lead data science projects, influencing strategic choices and addressing complex problems

Your Skills and Experience:

• 8+ years of experience in data science and product analytics
• Experience in the consumer technology sector
• Proficient in writing efficient SQL queries for large datasets
• Skilled in designing and analyzing A/B tests
• Strong understanding of growth strategies for consumer products
• Experience working in fast-paced startup environments
• Excellent verbal and written communication skills
• Strategic thinker with a keen focus on product development
• Innovative approach to using data to drive product strategy

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Lead AI Engineer
Location: San Francisco Bay Area | Hybrid
Salary: $250-300k + Equity

Join a well-funded, AI-native startup at the forefront of redefining how digital products are designed and shipped.

This team is building a next-generation design platform where every screen is real, production-ready code. Designers work directly in the medium that ships, not static mockups, with AI deeply embedded into the workflow to accelerate iteration while preserving precision, consistency, and control.

Backed by top-tier Bay Area investors and senior product leaders from companies including Shopify, Notion, Dropbox, Stripe, and OpenAI, the company has strong runway, a high bar for talent, and ambitious plans ahead.

They’re now hiring their first dedicated Lead AI Engineer to own the model layer and drive AI performance across the product.

The Opportunity

You’ll work directly with the CTO and founding team to define and execute the AI strategy at the model level.

This is a hands-on, production-focused AI engineering role centered on:

• Fine-tuning LLMs for real-world use cases
• Optimizing inference speed, cost, and reliability
• Designing and deploying custom Small Language Models (SLMs)
• Establishing evaluation, benchmarking, and observability standards

What You’ll Be Responsible For

Fine-Tuning & Model Strategy

• Own fine-tuning workflows (LoRA, adapters, distillation, full fine-tuning)
• Decide when to fine-tune vs optimize at the system or prompt level
• Iterate models based on production feedback
• Balance quality, latency, and cost tradeoffs

Model Optimization & Performance

• Improve inference speed and throughput
• Reduce cost per request
• Enhance reliability and output consistency
• Define model evaluation and benchmarking frameworks

Custom SLM Development

• Design and train custom SLMs for specific design-to-code workflows
• Identify when smaller models outperform larger ones
• Deploy and maintain real-time, streaming AI systems
• Support multi-step and agentic AI capabilities within the product

What They’re Looking For

• 5+ years of software engineering experience
• 2+ years building with LLMs in production environments
• Proven hands-on fine-tuning experience (LoRA, distillation, adapters, etc.)
• Experience deploying custom or specialized models
• Strong intuition around inference tradeoffs: latency, throughput, cost, reliability
• Proficiency in Python and TypeScript / Node.js

Nice to have:

• ONNX runtime or model optimization tooling
• Experience with orchestration frameworks (e.g., LangChain)
• WebSockets, Redis, or real-time streaming systems
• Background in AI-native or code-generation products
• A PhD or advanced degree is welcomed, but demonstrated production impact is the priority.

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Staff Data Scientist, Finance – Consumption Forecasting

Location: San Francisco or New York | Hybrid (3 days per week in office)

Salary: $240-300k base + bonus + equity (RSUs)

This is a rare chance to own forecasting infrastructure at the center of a high-growth, consumption-based developer platform, one that powers some of the world’s most dynamic applications and scales with every developer and enterprise building on it.

As a consumption-based business, forecasting usage across compute, bandwidth, edge, and storage isn’t a support function. It’s foundational to how we plan infrastructure, revenue, and long-term strategy. This role exists to lead that work at the highest level.

What you’ll own

This is a senior individual contributor role with organization-wide impact. You’ll define forecasting methodology, build systems that scale with a rapidly growing platform, and sit at the intersection of Finance, Infrastructure, Product, and GTM with direct visibility to executive leadership.

• Own production revenue forecasting end-to-end: model development, backtesting, deployment, monitoring, and iteration from first principles to live system
• Build forecasting systems that account for usage-based pricing dynamics, consumption patterns, and customer lifecycle across the platform, built for how this business actually works, not retrofitted SaaS models
• Design hierarchical forecasting models across account, cohort, segment, and global aggregate levels, covering operational, quarterly, and long-range planning cycles
• Establish backtesting, monitoring, and explainability standards that make forecast accuracy transparent and defensible
• Build scenario simulation frameworks to evaluate pricing changes, packaging adjustments, and product launches
• Partner with Finance on board-level reporting, with Infrastructure Engineering on capacity planning, and with Product and GTM on adoption curves and usage drivers
• Set forecasting best practices across the broader Data organization

What we’re looking for

• 7+ years in data science, quantitative analytics, or applied statistics at senior or staff level
• Deep expertise in time-series forecasting and statistical modelling in a usage-based or SaaS environment
• Proven track record building and productionizing ML systems at scale
• Strong Python and SQL, with experience on large-scale usage and billing datasets
• Familiarity with probabilistic modelling, hierarchical forecasting, and causal inference
• Experience partnering with Finance or executive leadership on planning cycles
• Comfortable operating autonomously in fast-moving, ambiguous environments

Nice to have

• Background in cloud infrastructure, developer tools, or consumption-based revenue models
• Familiarity with modern data stacks: Snowflake, Delta Lake, dbt, Airflow
• Prior technical mentorship or informal leadership experience

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Staff Applied AI Engineer | Bay Area (Hybrid) | $200k-$298k base + equity

I’m partnering with a high-growth SaaS company at the cutting edge of AI and compliance on a senior Applied AI Engineer hire.

This is not a typical “build a model and ship it” role.

This is where you define what good AI looks like – owning how systems retrieve, reason, and deliver trustworthy outputs at scale.

You’ll sit at the intersection of research and real-world impact, shaping the intelligence behind core product features.

‘ :

* Improving RAG systems – retrieval quality, chunking, embeddings, hybrid search

* Designing evaluation frameworks (metrics, golden datasets, regression detection)

* Building and tuning ranking + reranking systems (cross-encoders, LLM rerankers)

* Running experiments to validate what actually improves performance

* Debugging failure modes across retrieval, reasoning, and generation

* Prototyping agent-style workflows over complex, document-heavy data

* Exploring ML approaches beyond GenAI (ranking, classification, probabilistic models)

‘ :

* 8-10+ years in applied ML, data science, or AI research

* Strong experience in information retrieval / search relevance

* Hands-on with RAG systems and retrieval optimization

* Deep understanding of evaluation + experimentation (A/B testing, metrics)

* Python + strong problem-solving / research mindset

* Someone who can explain why systems work (or don’t) – not just build them

:

* You’ve only used LLM APIs without optimizing retrieval or evaluation

* Your experience is purely prompt engineering

* You prefer purely academic research without product impact

* You’re looking for a heavily structured, slow-moving environment

Candidates must be based in the Bay Area and open to a hybrid setup.

If you’re interested in making AI systems measurably better – not just building them, drop me a message or comment below.

Happy to share more details confidentially.

#AIJobs #MachineLearning #RAG #SearchRelevance #LLMs #Hiring #BayAreaJobs #TechJobs

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Clinical Data Scientist
San Francisco, California

Remote

$160,000 – $190,000 + Equity

About the Company

This innovative health tech startup is working to improve the oncology drug development process by providing better patient data to drug developers as well as better access to clinical trials for patients. This series B startup is expending to meet demand.

About the Role

As a Clinical Data Scientist, you’ll execute the last leg of the clinical data pipeline by transforming, cleaning, validating, and delivering high‑quality clinical datasets for pharma partners. Heavy collaboration with Clinical Ops, AI Engineering, and Data Delivery.

Role Responsibilities

• Transform raw, abstracted, and AI‑processed data into CDISC SDTM/ADaM datasets
• Program statistical outputs (tables, listings, figures) in SAS/R/Python
• Investigate data anomalies across multiple messy data inputs
• Define data dictionaries and standards before study kickoff
• Handle data in a HIPAA‑aligned manner

Key Requirements

• 2-5 years in clinical data science, stat programming, or clinical data management
• Pharma/Biotech experience
• SAS, R, Python, SQL
• Real‑world clinical data or oncology trials
• CDISC SDTM/ADaM

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AI Engineer
San Francisco, California

Remote

$200,000 – $220,000 + Equity

About the Company

This innovative health tech startup is working to improve the oncology drug development process by providing better patient data to drug developers as well as better access to clinical trials for patients. This series B startup is expending to meet demand.

About the Role

As an AI Engineer, you will design and deliver applied AI systems (LLMs/CV/multimodal) that automate clinical variable abstraction and clinical note generation-with repeatable validation, robust documentation, and HITL feedback loops. Heavy emphasis on data engineering and backend rigor to make models usable and efficient.

Role Responsibilities

• Build models and pipelines across EMR/EHR, imaging, clinical reports
• Translate ambiguous clinical requirements into measurable ML objectives
• Define metrics, design experiments, estimate error; review peer work
• Deliver validated AI components for abstraction/note generation; meaningfully reduce manual QA workload via HITL; standardize documentation/testing; establish performant data manipulation patterns (e.g., PySpark, SQL/Postgres) that speed iteration.

Key Requirements

• Python
• Pytorch or Tensorflow
• Data engineering: PySpark, SQL, Postgres, query tuning, data modeling
• Cloud data platforms (e.g., Databricks, S3/Snowflake/Azure/GCP)
• Nice to have experience in oncology/biotech/health tech

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Senior AI Engineer

San Francisco or New York · Up to $300k base + significant performance bonus · In-person · No sponsorship

I’m working on a rare and genuinely compelling search with a leading global investment firm. They’re building an internal AI function from the ground up – a small, high-impact team embedded directly within the investment organisation – with a mandate to reimagine how investment work gets done using AI.

This is not a side project or an innovation lab. The firm has operated using the same Excel, PowerPoint, and email workflows for 25+ years and has made a deliberate decision to change that. You’ll be identifying the repetitive, high-volume analytical work happening across the firm and building the agentic systems that automate and augment it – working directly alongside experienced investment professionals every day.

The culture is flat, entrepreneurial, and deeply technical. These are smart people who take a meritocratic approach and trust their team to manage their own work. If you want proximity to senior decision-makers and real influence over how a firm at this level operates, there aren’t many roles like it.

What you’ll be doing:

• Design and build the technical architecture for an AI-powered investment platform, including agentic workflows, RAG systems, and LLM-based tooling
• Identify repetitive analytical and operational tasks across the firm and build production-grade systems to automate them
• Integrate LLMs into real investment workflows – connecting AWS, Snowflake, Salesforce, and external data sources
• Build evaluation frameworks to ensure AI output meets institutional-grade standards
• Make build-vs-buy recommendations on AI vendors, platforms, and infrastructure
• Work directly with investment partners and operators, translating complex processes into AI-enabled solutions
• Provide technical direction and mentorship as the team grows

What my client is looking for:

• 5-8 years of software engineering experience, with a deliberate recent pivot into AI/GenAI applications
• Production experience with LLM applications, RAG systems, and agentic frameworks
• Strong Python and cloud infrastructure (AWS preferred)
• Solid software engineering fundamentals – architecture, distributed systems, CI/CD
• Product intuition for AI systems and good judgment on when and how to apply AI effectively
• Comfortable switching between highly technical conversations and discussions with non-technical senior stakeholders
• Entrepreneurial mindset – startup background (Series A-C) is ideal
• Curiosity about investment workflows; prior financial services experience is a plus but not required

Stack includes AWS, Snowflake, Claude, Claude Code, ChatGPT, and Fivetran.

US citizens and GC holders only – no sponsorship available now or in the future.

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Senior AI Engineer – Bay Area – $200k-$250k base + RSUs · Hybrid (Tues-Thurs onsite)

I’m partnering with a fast-growing Series C SaaS company on what is genuinely one of the more exciting AI engineering roles I’ve worked on this year. They’ve hit significant scale, built a strong market position, and are now entering a new chapter – with AI at the centre of everything they’re building next.

This is a production-first role. You won’t be running experiments or building proofs of concept – you’ll be designing and shipping agentic AI systems that automate complex, high-stakes enterprise workflows, replacing weeks of manual effort with intelligent, reliable automation at scale. The impact is immediate and highly visible.

You’ll be joining a collaborative AI team of around 14, with strong alignment to the product and engineering leadership. The culture values curiosity, ownership, and people who challenge ideas – this is a place where strong engineers have real influence over what gets built and how.

What you’ll be doing:

• Design and build LLM-powered agentic systems with multi-step reasoning, evidence grounding, and decision support
• Develop RAG pipelines, vector search, and document parsing and classification systems
• Build and own distributed AI pipelines and long-running agentic workflows using Temporal
• Architect production-grade LLM and retrieval systems, optimising for latency, cost, and reliability
• Embed guardrails, human-in-the-loop workflows, and evaluation pipelines to ensure trustworthy AI outputs
• Partner closely with product and engineering to bring cutting-edge AI from concept to production
• Help set the technical bar for how the team builds with modern LLMs – your decisions shape what ships

What they’re looking for:

• 7+ years of software engineering experience, with 2+ years working directly in AI/ML engineering
• Proven track record shipping production LLM applications – RAG pipelines, agent frameworks, and evaluation systems
• Strong Python; TypeScript is a bonus
• Hands-on experience with vector databases (Pinecone, Chroma, FAISS) and embedding systems
• Comfortable reasoning about distributed systems and decomposing complex problems into agentic workflows
• Startup background is important – they want builders who take full ownership, not order-takers
• Curious, collaborative, and energised by ambiguity rather than unsettled by it

Stack includes AWS Bedrock, Python, Temporal, Snowflake, and vector DB/RAG systems. US citizens and GC holders preferred; exceptional H1B candidates will be considered.

If you’ve spent your career building real AI systems – not demos – and you’re looking for a role where your work genuinely moves the needle for thousands of enterprise customers, this is worth a conversation.

Senior AI Engineer – Bay Area – $200k-$250k base + RSUs · Hybrid (Tues-Thurs onsite)

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Principal AI Engineer

San Francisco, CA – 4 days onsite

$225,000 – $250,000 + bonus + LTI; $500,000-$700,000 total

THE COMPANY

Harnham is partnering with a top financial services company in the NYC area, which is looking for an experienced AI / ML Engineer. This person will be at the forefront of building AI automation applications for new ways at identifying cost-saving opportunities. You’ll partner with executive teams across the company and own generative AI, LLM and reinforcement learning modeling and deployment.

RESPONSIBILITIES

• Work closely with department heads to align on business goals, define machine learning challenges, and design effective ML solutions.
• Develop and deploy machine learning models, including building data pipelines, orchestrating ML workflows, and optimizing system performance and reliability.
• Maintain a robust codebase by writing well-tested code, covering both functional and non-functional aspects such as unit, integration, and load testing.
• Stay informed on industry trends and advancements in generative AI, LLMs, agentic AI, deep learning, experiment with new model concepts, and run both offline and online evaluations.
• Actively share knowledge through internal presentations, tech talks, and by promoting best practices in engineering and technology use.

SKILLS AND EXPERIENCE

• Advanced degree (Master’s or PhD) in Computer Science, Machine Learning or a related field.
• Over 7 years of hands-on experience developing and deploying production-ready machine learning / deep learning / AI systems, covering the full model lifecycle-training, tuning, deployment, serving, and monitoring.
• Enterprise-level application experience, ideally in real-time preferred.
• Expertise in cloud infrastructure (especially AWS), machine learning orchestration tools like Kubeflow, TensorFlow, and the use of Feature Stores in live environments.
• Experience as a tech-lead for scaling MLE teams preferred.
• Commercial experience combination of big tech and scaling startups / scrappy environments a plus.

BENEFITS

The compensation package contains a base salary, bonus, LTI and a comprehensive benefits package.

HOW TO APPLY

Please register your interest by sending your CV via the Apply link on this page.

KEY TERMS

Artificial Intelligence | Generative AI | GenAI | Machine Learning | ML Engineer | Engineering | Deployment | Production | Real Time | Enterprise | Statistics | Mathematics | Financial Services | Banking | Python | Anomaly Detection | Fintech | Agentic AI | AI Agents

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Clinical Data Scientist (Confidential Biotech | Oncology Focus)

Remote (U.S.) | Competitive Base of up to $190,000 (DOE) + Equity

We’re partnering with a rapidly scaling, mission-driven biotech that is quietly redefining how clinical trials are executed in oncology.

This organization sits at the intersection of real-world clinical practice, AI-powered data extraction, and modern trial design-building a more efficient and representative path to drug development.

They’re now hiring Clinical Data Scientists who want to move beyond traditional study support and play a direct role in shaping next-generation clinical data pipelines.

Why This Role Stands Out

• Work on real-world, messy clinical data-not just clean trial datasets
• Direct influence on how AI/NLP outputs are validated and improved
• High ownership in a scaling, high-demand environment
• Opportunity to help define data standards from study inception
• Mission-driven focus: accelerating oncology drug development and expanding trial access

What You’ll Actually Do

• Transform raw, abstracted, and AI-processed data into CDISC SDTM/ADaM datasets
• Program tables, listings, and figures (TLFs) using SAS, R, or Python
• Investigate and resolve data inconsistencies across fragmented sources
• Define data dictionaries and standards pre-study kickoff
• Perform rigorous QC and produce regulatory-grade documentation (Define.xml, reviewer guides)
• Partner with AI teams to create feedback loops that improve model accuracy
• Support ad hoc clinical and exploratory analyses
• Ensure all work aligns with HIPAA-compliant data handling practices

What They’re Looking For

• 2-5+ years in Clinical Data Science, Statistical Programming, or Clinical Data Management
• Strong experience with CDISC (SDTM/ADaM)
• Proficiency in SAS, R, Python, and/or SQL
• Background in pharma or biotech (oncology or real-world data strongly preferred)
• Experience working with imperfect, multi-source clinical data-sets
• Detail-oriented with a strong instinct for data quality and validation

The Bigger Picture

This team is building a system where:

• AI handles upstream abstraction from unstructured records
• Clinical Data Scientists own the final mile: transformation, validation, and delivery

If you’ve ever been frustrated by siloed workflows or limited visibility into how data is generated-this is your chance to work in a more integrated, modern environment.

If you’re interested in learning more (confidentially), feel free to reach out directly.

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Senior AI Engineer

Locations: San Francisco, CA Work Arrangement: 4-5 days per week onsite (In-person collaboration focus) Compensation: $425,000 – $600,000 Total Cash (Base + ~50% Performance Bonus)

The Opportunity

Our client is a premier global technology investment firm with a 26-year track record of excellence and over 200 employees. Despite their scale, they maintain a flat, entrepreneurial, and “deeply technical” culture.

They are currently seeking a Senior AI Engineer(VP Level) to help lead a digital transformation. This is not a “maintenance” role; you will be tasked with reimagining the future of private equity. You will build the AI agents and autonomous workflows that will automate and augment the high-volume analytical work currently performed by investment professionals.

Note: This role does not support sponsorship’s

The Mission

Your goal is to move the firm beyond legacy workflows (Excel, email, and PowerPoint) and toward an AI-augmented investment process.

• Focus: Building production-grade agentic systems and AI applications that drive business value.

• Philosophy: Our client is not training foundational models from scratch. Instead, you will use off-the-shelf models (OpenAI, Anthropic, etc.) and focus on sophisticated orchestration, RAG systems, and workflow integration.

• Impact: You will identify repetitive, associate-level tasks and build systems where AI performs 80% of the heavy lifting, allowing humans to focus on high-level refining and decision-making.

Key Responsibilities

• Architect & Build: Design and deploy AI-powered systems and agent-based frameworks into production.

• Integrate: Develop the architecture to connect LLMs with diverse data sources, including AWS, Snowflake, Salesforce, and external alternative datasets (market research, web traffic, etc.).

• Collaborate: Work directly with Investment Partners and Operating Teams to translate complex investment processes into automated AI workflows.

• Innovate: Serve as a technical leader in deciding when to use single vs. multi-agent systems and selecting the appropriate LLM for specific use cases.

Candidate Profile

We are looking for a builder, not a maintainer. The ideal candidate likely comes from a high-growth startup environment (Series A-C) or a specialized internal product team.

Technical Requirements

• Foundation: 5-10 years of professional experience, including at least 4+ years of core software engineering.

• AI Pivot: A deliberate focus over the last 2-4 years on Generative AI and LLM application design.

• Stack: Mastery of Python and Cloud Infrastructure (AWS preferred).

• Data Savvy: Experience with Snowflake and modern data pipelines (Fivetran, etc.). Exposure to financial data (EBITDA, market data) is a significant plus.

Soft Skills & Mindset

• Entrepreneurial: You thrive in a flat organization where you are expected to take ownership and manage your own work.

• “Code-Switcher”: Ability to communicate technical architecture to engineers while explaining business value to Senior Investment Partners.

• Practicality: You prioritize shipping functional, high-impact tools over theoretical or academic exercises.

Why Join?

• High Visibility: This role is integrated into the investment team; you will interact with firm leadership daily.

• Modern Tools: The team is already leveraging AI-assisted coding (Claude Code) and modern data stacks to move fast.

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