Head of Research

Gamut

$50K — $500K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years leading applied ML/NLP research teams in a high-growth environment
  • Deep knowledge of LLM and agent systems, including planning and evaluation methods
  • Experience building evaluation frameworks and linking metrics to product outcomes
  • Expertise in orchestration, tool APIs, and distributed systems
  • Proficient in Python with a hands-on approach to experimentation
  • Familiarity with data curation, focusing on privacy and safety
  • Strong communication skills for cross-function collaboration, especially with engineering

Responsibilities

  • Establish the research strategy for agent planning and orchestration
  • Build and mentor a high-performing applied research team
  • Design and execute rigorous experimental research with defined metrics
  • Manage the evaluation stack including datasets and safety assessments
  • Develop innovative methods for agent planning and coordination
  • Partner with engineering to implement research findings in production
  • Work in-office full-time to foster team collaboration

Benefits

  • Competitive salary, commensurate with experience
  • Meaningful equity options
  • Opportunity to be a founding member of a fast-growing company
Full Job Description
The Role

As Head of Research, you'll own Datawizz's research agenda and build an applied research organization focused on making agents radically more reliable and capable. You'll define the roadmap across agent planning, tool orchestration, evaluation, and safety; lead hands-on experimentation; and partner closely with engineering to productionize breakthroughs that drive measurable quality and reliability wins for customers.

You will:
  • Set the research strategy and roadmap for agent planning, tool orchestration, multi-agent coordination, and evaluation.
  • Build, lead, and mentor a high-caliber applied research team.
  • Design and run rigorous experiments (ablations, offline/online A/Bs), defining clear metrics for reliability, accuracy, and performance.
  • Own our evaluation stack: datasets, benchmarks, human-in-the-loop reviews, and reliability/safety assessments.
  • Develop novel methods (e.g., agent planning algorithms, tool selection strategies, multi-agent coordination, safety/alignment techniques) and ship reference implementations.
  • Collaborate with engineering to transfer research into production and measure real-world impact.
  • This role is in-office, 5 days/week, based in San Francisco.


You might be a great fit if you have experience with:
  • Leading applied ML/NLP research teams and shipping work into production at a startup or high-growth company.
  • LLM and agent internals: prompting strategies, tool use, planning/reasoning architectures, multi-agent systems, and evaluation methodology.
  • Building evaluation frameworks (task suites, synthetic data, human eval pipelines) and tying metrics to product outcomes.
  • Large-scale agent systems: orchestration frameworks, tool APIs, distributed execution, observability, and logging infrastructure.
  • Strong coding skills in Python and a bias toward hands-on experimentation and rapid iteration.
  • Data curation and labeling workflows, with attention to privacy, safety, and robustness.
  • Communicating research clearly and partnering cross-functionally with engineering and product.
  • (Nice to have) Publications or notable open-source contributions; patents; early-stage 01 experience.


Benefits
  • Competitive salary, based on experience level (Annual compensation range: $50,000-$500,000)
  • Meaningful equity
  • Opportunity to be a founding member of a growing company

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