Qureos Mentor

Alexander Chapman

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 I&rsquo;m currently working with a global financial services and investment platform with a strong presence across capital markets and research, who are looking for an
 
 Equity Research Associate
 
 to join their Industrial, Power Technology and Infrastructure team in
 
 New York
 
 .
 
 
 
 
 
 What makes this platform particularly interesting is the direct integration between research, trading, and capital markets activity, where research is closely tied to live market flow and actively informs investor positioning across institutional clients, giving analysts meaningful market impact rather than standalone published coverage.
 
 
 
 
 
 The role sits within a highly regarded research platform covering the energy transition, power markets, and infrastructure related technologies, with a strong emphasis on fundamental analysis, sector deep dives, and the development of differentiated investment views across both public and private market themes.
 
 
 
 
 
 They are looking for someone with strong financial modelling capabilities, solid exposure to power or infrastructure sectors, and a genuine interest in the evolving energy and technology landscape.
 
 
 
 
 
 If this sounds like a fit, I&rsquo;d be happy to share more detail and discuss further.
 
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Equity Research Associate - Industrials and Infrastructure

<div>
 
 Connect with me and feel free to apply if you&rsquo;re a Researcher or Machine Learning Engineer and aren&rsquo;t sure you&rsquo;re the perfect fit.
 
 
 
 
 
 I&rsquo;m currently working with two elite, well-funded teams in the Bay Area (SF &amp; Palo Alto) that are taking Reinforcement Learning in polar opposite, but equally ambitious, directions:
 
 
 
 
 
 
 1. The Foundational Research Lab (San Francisco)
 
 Founded by "old-school" RL PhDs, this lab believes the field is scaling prematurely while ignoring core issues like data inefficiency and long action horizons. Backed by
 
 Vercel and South Park Commons
 
 , they are building a research-driven environment to scale RL-LLM hybrids by orders of magnitude.
 
 
 
 
 <ul>
 <li>
 
 The Mission:
 
 Moving past DPO/RLHF to create agents that genuinely generalize.
 </li>
 <li>
 
 The Team:
 
 Talent from
 
 DeepMind, Meta, and NVIDIA
 
 .
 </li>
 </ul>
 
 
 
 
 
 2. The "Ground Truth" Reasoning Startup (Palo Alto)
 
 A
 
 Stanford spinout
 
 solving for long-horizon reasoning by moving RL into a space where physics and logic provide a non-negotiable ground truth:
 
 Chip Design.
 
 They are building a "Cursor for Verilog" where agents must plan, critique, and verify their own code against real execution feedback.
 
 
 
 
 <ul>
 <li>
 
 The Mission:
 
 Collapsing the 3-year hardware design cycle through automated reasoning.
 </li>
 <li>
 
 The Team:
 
 Led by the former
 
 Head of AI (Trust &amp; Safety) at Anthropic
 
 , with peers from
 
 xAI and OpenAI
 
 .
 </li>
 <li>
 
 The Backing:
 
 Top-tier VCs with support from figures like Jeff Dean.
 </li>
 </ul>
 
 
 
 
 Both teams are looking for "founding-level" engineers who can ship production-grade systems, not just run experiments.
 
 
 
 
 
 If either of these philosophies:
 
 foundational scaling
 
 or
 
 physical verification
 
 align with where you want to take your next career move, feel free to apply.
 
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Research Scientist

Join Alexander Chapman and explore 2   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Alexander Chapman

About Company

Equity Research Associate - Industrials and Infrastructure

Research Scientist