Member of Technical Staff - Research Scientist

Architect Labs
Palo Alto, CA
On-site

Who this role is best for

Aimed at experienced researchers or engineers with a strong background in AI and a builder mindset, who are comfortable working in a fast-paced startup environment focused on cutting-edge AI-driven chip design.

Best fit for

  • Experienced AI researchers with a builder mindset and systems engineering skills
    — “Exceptional systems engineering. You architect and ship reliable, large-scale infrastructure”
  • Candidates with a background in multi-agent systems or agent harness development
    — “Experience designing and improving agent harnesses, including orchestration, tool use, memory, feedback loops, and recovery mechanisms”
  • Individuals excited about applying AI to hardware and willing to learn from chip engineers
    — “Excitement about applying frontier AI to chip design and a willingness to learn deeply from hardware engineers”

Things to consider

  • This role demands a high level of autonomy and ability to work with ambiguous problems
    — “Ability to own ambiguous problems end to end, prototype quickly, and turn promising ideas into production systems”
  • The role requires translating complex hardware challenges into agent capabilities
    — “Translate ambiguous chip-design challenges into concrete agent capabilities that ship”

How to stand out

  • Highlight your experience in creating scalable software infrastructure for AI systems
    — “Build scalable and robust software stacks that transform ideas into production systems seamlessly”
  • Showcase your ability to prototype and iterate quickly in a fast-paced startup setting
    — “Move fast in a 0 to 1 environment: prototype, dogfood, break things, iterate”
  • Emphasize your published research or open-source contributions in agent systems or ML tooling
    — “Meaningful open-source contributions to coding agents, agent harnesses, or ML tooling”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Designing and improving agent harnesses
  • Building scalable software stacks
Typical background
PhD in Computer Science or a related field3+ years of research experience at a frontier AI lab

Skills & requirements

Required

Research ScientistAI And Machine LearningSoftware EngineeringChip Design

Preferred

Open-source ContributionsExperience With Leading Conferences

Stack & domain

AIChip DesignAgent HarnessesMLSoftware EngineeringTransformer-based ModelsLarge-scale ML SystemsProblem-solvingCommunication

About the role

Original posting from Architect Labs via Ashby

ABOUT ARCHITECT LABS

Architect is a frontier AI lab for custom silicon. We partner with frontier labs, clouds / neoclouds, physical AI companies, and advanced fabs to tape-out custom chips co-designed for next-generation AI workloads. Our goal is to compress end-to-end software to silicon timelines, and maximize intelligence per watt and per dollar for the world. We are a small exceptional team across silicon, systems, software and frontier AI. Our team have led research teams at nearly every frontier AI lab, and at some of the most complex SoCs in the world.

What You'll Do

As a Member of the Technical Staff at Architect Labs, you'll sit at the intersection of chip design and frontier AI translating deep hardware engineering expertise into agentic systems that can reason about, generate, and verify real silicon.

  • Research on self-improving harnesses to guide a swarm of agents work autonomously for days / weeks. Stay on top of SOTA frontier research.
  • Partner closely with the ML research, post-training, and infra teams to turn hardware domain expertise into reward signals, benchmarks, and training signals.
  • Build scalable and robust software stacks that transform ideas into production systems seamlessly.
  • Build evals and environments that tackle chip-design tasks, grounding model behavior in real hardware engineering work.
  • Move fast in a 0 to 1 environment: prototype, dogfood, break things, iterate. Translate ambiguous chip-design challenges into concrete agent capabilities that ship.

What We'd Like to See

Qualifications & Skills:

  • Background: PhD in Computer Science or a related field, or 3+ years of research experience at a frontier AI lab.
  • Agent Harness Research: Experience designing and improving agent harnesses, including orchestration, tool use, memory, feedback loops, and recovery mechanisms that enable agents to work autonomously on complex, long-horizon tasks.
  • Research Instinct: Ability to stay current with frontier AI research, critically assess new approaches, and turn promising findings into measurable improvements.
  • Software Engineering: Exceptional systems engineering. You architect and ship reliable, large-scale infrastructure that others build on, and you hold research code to production standards.
  • Builder Mindset: Ability to own ambiguous problems end to end, prototype quickly, and turn promising ideas into production systems. Pragmatic, resourceful, and comfortable moving fast.
  • Interest in Hardware: Excitement about applying frontier AI to chip design and a willingness to learn deeply from hardware engineers.

Strong candidates may also have experience with:

  • Research published at leading top conferences (ICLR, ICML, NeurIPS, etc).
  • Meaningful open-source contributions to coding agents, agent harnesses, or ML tooling, or building a harness from scratch.
  • Designing and deploying production multi-agent workflows and agents that run autonomously for days or weeks.
  • Building evaluations and benchmarks for complex engineering tasks.
  • Familiar with development reward signals, post-training or reinforcement learning methods for language models.
  • Familiar with training or serving transformer-based models and building high-performance, large-scale ML systems.

What We Offer

  • Competitive salary and meaningful equity stake
  • Fast-paced startup with autonomy and visible impact
  • Cutting-edge AI-driven chip design challenges

Source: Architect Labs careers (Ashby)

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