Member of Technical Staff

Axiom; Palo Alto (CA); On-site; USD 180,000 - 250,000; Full time

Job summary

Axiom is seeking a senior ML researcher to lead core discovery projects at the intersection of deep learning, neuro-symbolic methods, and formal mathematics. You will design large-scale experiments, collaborate with research mathematicians to define benchmarks, and translate insights into business value through publications and open-source releases.

You will also mentor junior researchers, provide technical guidance, and foster a culture of excellence and collaboration in a high-performance team

Qualifications

• Advanced coding in Python and ML frameworks (PyTorch, JAX, TensorFlow).
• Deep expertise in large-scale training, reinforcement learning, program synthesis.
• Strong foundation in higher mathematics (algebra, analysis, combinatorics) and formal proof systems (Lean, Coq, Isabelle).
• Demonstrated research acumen: experiment design, rigorous analysis, peer-reviewed publications.

Responsibilities

• Lead core discovery projects, set research agendas, and design large-scale experiments.
• Collaborate with research mathematicians to identify open problems and build reproducible ML benchmarks.
• Communicate results through peer-reviewed publications, talks, open-source releases, and internal briefings.
• Mentor and coach junior researchers, providing technical guidance and career development support.

Job description

Applicable Field of Work

• Machine Learning & AI for Mathematical Discovery and Reasoning — R&D at the intersection of deep learning, neuro-symbolic methods, automated theorem proving, and pure/applied mathematics.

Duties & Responsibilities

• Lead core discovery projects (e.g., successors to PatternBoost): set research agendas, design and run large-scale experiments to reveal latent mathematical structures, and publish high-impact papers in top AI and mathematics venues.

• Collaborate with research mathematicians to identify open problems to tackle, formulate them into benchmarkable ML objectives, build reproducible pipelines, and iterate toward state-of-the-art solutions.

• Communicate results broadly through peer-reviewed publications, conference talks, open-source releases, and internal briefings that translate research insights into business value.

• Mentor and coach junior researchers by providing technical guidance, rigorous code reviews, and career development support, fostering a culture of excellence and collaboration.

Professional Skills & Competencies

Hard Skills

• Advanced coding in Python and modern ML frameworks (PyTorch, JAX, TensorFlow).

• Deep expertise in large-scale training, reinforcement learning, program synthesis, and neuro-symbolic techniques.

• Strong foundation in higher mathematics (algebra, analysis, combinatorics) and formal proof systems (Lean, Coq, Isabelle).

• Demonstrated research acumen: experiment design, rigorous analysis, and a track record of peer-reviewed publications.

Soft Skills

• Exceptional scientific writing and presentation abilities, tailoring complex ideas to diverse audiences.

• Proven collaborator who thrives in interdisciplinary teams with mathematicians, engineers, and product stakeholders.

• Leadership and mentorship strengths—able to inspire, guide, and elevate a high-performance research culture.