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Head of Machine Learning Research & Intelligence

Role overview

Qualifications

  • Deep experience building or evolving machine learning systems in production.
  • Strong technical judgment around model behavior, failure modes, and long-horizon trade-offs.
  • Builder’s mindset — focus on systems that work in the real world, not just ideas.
  • Comfort making irreversible or high-impact decisions with incomplete information.

Responsibilities

  • Set and evolve the research direction for A1’s core intelligence.
  • Decide when to design new model architectures versus adapting existing models.
  • Define evaluation frameworks that measure real-world usefulness, robustness, safety, and long-term behavior.
  • Own alignment, safety, and guardrail strategy as product concerns.

About the company

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OnHires

Staffing & Recruiting

Global high-tech Recruitment & Staffing for fast-growing companies We are a global recruitment agency that helps businesses scale by hiring talented tech specialists in 3 weeks. Our Mission To connect great companies with even greater talent. Our Vision To be the leading partner that clients and candidates always choose to connect with. Our Approach We are goals driven team, where culture is more important than formal processes. We have built a work environment that nurtures growth and true teamwork. There is nothing as satisfying as learning and celebrating successes together! Once you get to know us, you’ll know where this drive and energy come from.

Company details

Company typeScaleup
IndustryStaffing & Recruiting
Company size11 - 50

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Job description

We’re hiring on behalf of A1, a high‑talent team building the next generation of AI‑native productivity applications. Their mission is to replace repetitive digital work with AI that can reliably complete real tasks for everyday users.

Rather than building another chatbot, A1 is creating long‑running AI workflows that manage conversations, coordinate actions, maintain context, and interact with external services — all with minimal user input. The product is designed for reliability, persistent context, and real‑world task completion, helping users save up to 90% of their time on everyday digital work.

Role

As Head of Machine Learning Research & Intelligence, you will own the research and intelligence direction of the system. This is a hands‑on, high‑impact role focused on defining how AI reasons, evaluates, and improves in a product used daily at scale.

What You’ll Do

  • Set and evolve the research direction for A1’s core intelligence, including context representation, memory, reasoning, planning, and orchestration.

  • Decide when to design new model architectures versus adapting or leveraging frontier open‑source or commercial models.

  • Define evaluation frameworks that measure real‑world usefulness, robustness, safety, and long‑term behavior.

  • Own alignment, safety, and guardrail strategy as first‑class product concerns.

  • Guide exploration of frontier techniques such as retrieval‑augmented training, mixture‑of‑experts, distillation, multi‑agent orchestration, and multimodal systems.

  • Shape early product intelligence direction in close partnership with product and application engineering.

  • Set the technical bar for research rigor, judgment, and taste across the organization.

Requirements

  • Deep experience building or evolving machine learning systems in production.

  • Strong technical judgment around model behavior, failure modes, and long‑horizon trade‑offs.

  • Builder’s mindset — focus on systems that work in the real world, not just ideas.

  • Comfort making irreversible or high‑impact decisions with incomplete information.

  • Obsession with evaluation, correctness, and long‑term system behavior.

  • High ownership mentality — operate as a founder, not a manager.

This role is not a fit for those primarily focused on publishing, incremental benchmarks, or managing large research organizations.

Tech Stack

  • Python

  • PyTorch / JAX

  • GPU‑based training and inference systems

How They Work

A1 believes the best products are built by small, world‑class teams. They move fast, make decisions collectively, and balance shipping high‑quality work with rapid learning. Joining requires the ability to bring structure, exercise judgment, and execute independently. The goal is to deliver a truly magical product into the hands of millions.

Interview Process

If there’s a fit, expect 3–4 interviews with technical team members, conducted virtually or onsite. The process is transparent and efficient, with prompt decisions. Successful candidates will receive not just a job offer, but an invitation to join a team bringing practical AI benefits to billions globally.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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