4 months ago

Member of Technical Staff

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 6 hours agoStatus: Live

Job Summary

Lead and collaborate on cutting-edge machine learning research at the intersection of deep learning, neuro-symbolic methods, and automated theorem proving, focusing on mathematical discovery and reasoning. Lead discovery projects, publish high-impact papers, mentor junior researchers, and translate research insights into business value within an engineering-focused team.

Location: Palo Alto

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key 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.

Key Requirements

•Python and modern ML frameworks (PyTorch, JAX, TensorFlow) with advanced coding skills.
•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: experimental design, rigorous analysis, and a track record of peer-reviewed publications.
•Exceptional scientific writing and presentation abilities; proven collaboration in interdisciplinary teams and leadership in mentorship.

Experience:Machine learningNeuro-symbolicAutomated theorem proving

Skills:CommunicationLeadershipWritingMentorshipTeamwork

Tech Stack:PythonPyTorchJAXTensorFlowLeanCoqIsabelle

Company Brief

Axiom Math

Axiom Math builds AI-driven math tutoring and practice tools that deliver personalized learning paths, adaptive problem sets, and real-time feedback to help students improve understanding and outcomes across K-12 and early college math topics.

Industry: EdTech

Website

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Axiom Math

4 months ago

Member of Technical Staff

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 6 hours agoStatus: Live

Job Summary

Location: Palo Alto

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key 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.

Key Requirements

•Python and modern ML frameworks (PyTorch, JAX, TensorFlow) with advanced coding skills.
•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: experimental design, rigorous analysis, and a track record of peer-reviewed publications.
•Exceptional scientific writing and presentation abilities; proven collaboration in interdisciplinary teams and leadership in mentorship.

Experience:Machine learningNeuro-symbolicAutomated theorem proving

Skills:CommunicationLeadershipWritingMentorshipTeamwork

Tech Stack:PythonPyTorchJAXTensorFlowLeanCoqIsabelle

Company Brief

Axiom Math

Industry: EdTech

Website