Applied AI Researcher

The Opportunity: A New Breed of Scientist

• This is not a traditional research role. You will not be focused on publishing papers for academic prestige or working on long-horizon theoretical problems. You are a hands-on builder and a strategic technologist, a new breed of scientist operating at the nexus of frontier AI, finance, and value creation.

• As an Applied AI Scientist, you will be a key member of the R&D and enablement engine for a dedicated AI Intervention Unit, a team purpose-built to generate "scalable, repeatable AI-driven alpha" across a portfolio of companies. You will scout, prototype, and help codify the most advanced AI solutions, contributing directly to the firm's intellectual property and technological edge. Your success will be measured by the tangible P&L impact and enterprise value you help create. This is a unique opportunity to apply your skills to high-stakes business problems and see your work directly fuel a proven, field-tested investment thesis.

What You'll Do

• Scout and Analyze AI Technologies: Contribute to the scouting, testing, and evaluation of frontier technologies and strategic partners (e.g., OpenAI, Microsoft, Google), providing analysis that helps shape our integration strategy.

• Develop and Prototype AI Solutions: Design and build prototypes for "Hero Missions" within our "simulation sandboxes," translating the most critical business challenges of our portfolio companies into working AI models and de-risking technology before full-scale deployment.

• Contribute to AI Playbooks and Knowledge Sharing: Document best practices, create reusable code libraries, and develop reference architectures that form the core of our "living playbooks." Support the AI Academy by helping create training materials that foster AI fluency across the firm.

• Collaborate with Technical and Business Teams: Work closely with our cross-functional delivery pods, offering technical guidance on model selection, architecture, and implementation. Partner with the AI Operations Center to analyze real-world model performance and drive continuous improvement.

What You'll Need

• 3+ years of industry experience in an applied science or machine learning role, with a track record of contributing to production-level AI/ML systems.

• A Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field, or a Bachelor's degree with equivalent practical experience.

• Proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow).

• Hands-on experience building applications using Large Language Models (LLMs), with knowledge of techniques like RAG, fine-tuning, and prompt engineering.

• Experience with the MLOps lifecycle (e.g., experimentation, deployment, monitoring) on a major cloud platform (AWS, Azure, or GCP).

• A P&L-oriented mindset, with an eagerness to connect technology to business value and financial results.

• Strong communication skills, with the ability to explain complex technical concepts to different audiences.

• A delivery-focused mindset with a bias for action and shipping "shippable solutions, not experiments".

Nice-to-Haves

• A PhD in a relevant field.

• Experience in financial services, private equity, or at a top-tier management consulting firm.

• Experience mentoring junior scientists or leading project workstreams.

• A publication record in top-tier AI conferences (e.g., NeurIPS, ICML, ICLR).

• Experience working with business stakeholders to define technical requirements.