Head of Research

Valency Systems•Berkeley, CA

2d•Hybrid

About The Position

Valency Systems is a small, dynamic team of engineers, scientists, and researchers building the global hub for the agentic research era. We're based in Berkeley, California, and we're building something that matters. If you care about open science, advancing research at the speed of thought, and using AI to accelerate discovery, we'd love to talk. Our team is hybrid. We come together in person 3 days a week, with the option for 2 days of remote work. As our Head of Research, with a PhD or advanced degree in Computer Science, Statistics, or a related field, you will set the research agenda, shaping how and what we build, and directly influencing the trajectory of the product. This role reports directly to the CEO. You'll be hands-on, collaborating with engineering and product leadership to make sure we're solving the right problems before we build the wrong things. If you thrive in a small, fast-moving environment where deep technical research has direct and immediate impact, this role was built for you.

Requirements

PhD or advanced degree in Computer Science, Statistics, or a related field
Strong command of graph databases and graph algorithms
A track record of running independent research programs and turning findings into engineering decisions — not just papers
Comfortable operating with autonomy in a fast-moving, resource-constrained environment
Candidates must be legally authorized to work in the United States.

Nice To Haves

Experience with bibliometrics and/or research evaluation methodologies — this is a meaningful plus given our domain
Record of academic publications
Hands-on experience designing and deploying large-scale ML systems in production
Familiarity with cost modeling and performance benchmarking for ML infrastructure

Responsibilities

Set and drive the research agenda
Define the research roadmap, prioritizing work that reduces technical risk and accelerates delivery
Anticipate hard problems before they become expensive ones — running ahead of the engineering team to validate approaches and surface unknowns early
Establish research practices and standards that will scale as the team grows
Leverage graph database, algorithm, and recsys knowledge to tackle complex data representation and retrieval challenges
Drive measurable improvements in system efficiency and operational cost through research-led optimization
Apply expertise in large-scale ML systems to improve model performance, system efficiency, and cost at scale
Be a true partner to the Head of Engineering and Head of Science — not a hand-off relationship, but a tight collaborative loop
Work in close alignment with those in product and customer-facing roles to maintain methodological rigor across research output
Translate complex research findings into clear, actionable guidance for engineers and non-technical stakeholders alike
Manage and mentor (world class) junior researchers
Contribute to building a culture where curiosity, rigor, and pragmatism coexist