Tzafon
Member of Technical Staff - Verification
Tzafon, San Francisco, California, United States, 94199
Tzafon is a research firm building scalable compute systems and advancing machine intelligence, with offices in San Francisco & Tel Aviv. We recently raised $9.7m in pre-seed funding to advance our mission of expanding the frontiers of machine intelligence.
We’re a team of engineers and scientists with deep backgrounds in ML infrastructure & research. Founded by IOI and IMO medalists, PhDs, and alumni from leading tech companies, we train models and build infrastructure for swarms of agents to automate work across real-world environments. You'll be part of a new research team focused on verification for increasingly advanced and intelligent models, and in RL environments. Your Role
As part of our research team, you'll design and implement
robust verification systems
to ensure reliability and alignment of our increasingly capable models. This role will bridge rigorous formal methods and practical machine learning. You’ll work on theorem proving, formal verification, evaluation tooling, and reinforcement learning environments — all with the aim of ensuring model safety and correctness as capabilities scale. What You’ll Do
Develop formal verification frameworks and theorem-proving benchmarks
Design scalable evaluation harnesses for both deterministic (e.g. code/math) and fuzzy (workflow-oriented) environments
Integrate with model training loops to improve reliability during pre-training, fine-tuning, and RL phases
Collaborate closely with research and engineering to embed safety and correctness across the ML pipeline
Build tooling in Python for automated testing, analysis, and verification of LAMs (Large Action Models)
Who You Are
Strong background in mathematics, formal methods, theorem proving, or physics (IMO/PhD is a plus)
Experience with verification tools (Coq, Lean, Isabelle) or property testing in ML
Deep understanding of reinforcement learning environments and verification strategies within them
Strong Python skills and experience building verification or evaluation infrastructure
Practical understanding of ML training pipelines, fine-tuning, and dataset quality
Passionate about aligning AI behavior with mathematical and real-world reliability
Ready to do your life's most meaningful work before AGI and ASI arrive
Life at Tzafon
Full medical, dental, and vision coverage, plus 401(k)
Office in SF and Tel Aviv
Early-stage equity in a future-defining company
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. Compensation Compensation starts at $150k-$425k and equity package. We also offer a referral bonus of $20k for referral of successful hires (send to careers@tzafon.ai).
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We’re a team of engineers and scientists with deep backgrounds in ML infrastructure & research. Founded by IOI and IMO medalists, PhDs, and alumni from leading tech companies, we train models and build infrastructure for swarms of agents to automate work across real-world environments. You'll be part of a new research team focused on verification for increasingly advanced and intelligent models, and in RL environments. Your Role
As part of our research team, you'll design and implement
robust verification systems
to ensure reliability and alignment of our increasingly capable models. This role will bridge rigorous formal methods and practical machine learning. You’ll work on theorem proving, formal verification, evaluation tooling, and reinforcement learning environments — all with the aim of ensuring model safety and correctness as capabilities scale. What You’ll Do
Develop formal verification frameworks and theorem-proving benchmarks
Design scalable evaluation harnesses for both deterministic (e.g. code/math) and fuzzy (workflow-oriented) environments
Integrate with model training loops to improve reliability during pre-training, fine-tuning, and RL phases
Collaborate closely with research and engineering to embed safety and correctness across the ML pipeline
Build tooling in Python for automated testing, analysis, and verification of LAMs (Large Action Models)
Who You Are
Strong background in mathematics, formal methods, theorem proving, or physics (IMO/PhD is a plus)
Experience with verification tools (Coq, Lean, Isabelle) or property testing in ML
Deep understanding of reinforcement learning environments and verification strategies within them
Strong Python skills and experience building verification or evaluation infrastructure
Practical understanding of ML training pipelines, fine-tuning, and dataset quality
Passionate about aligning AI behavior with mathematical and real-world reliability
Ready to do your life's most meaningful work before AGI and ASI arrive
Life at Tzafon
Full medical, dental, and vision coverage, plus 401(k)
Office in SF and Tel Aviv
Early-stage equity in a future-defining company
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. Compensation Compensation starts at $150k-$425k and equity package. We also offer a referral bonus of $20k for referral of successful hires (send to careers@tzafon.ai).
#J-18808-Ljbffr