Member of Technical Staff – Applied AI

Tzafon; San Francisco (CA); On-site; USD 150,000 - 400,000; Full time

Benefits offered by this job

Full medical, dental, and vision coverage

401(k) in the US

Early‑stage equity

Job summary

Tzafon is seeking a skilled engineer to enhance their machine intelligence systems in San Francisco. As part of the team, you'll be responsible for building evaluation infrastructure, designing data pipelines, and implementing fine-tuning processes. Ideal candidates have expertise in Python and machine learning frameworks, a solid track record of shipping ML systems, and strong opinions on evaluation methodologies. The position offers competitive compensation starting at $150k with equity options and full medical coverage.

Qualifications

• Deep experience with LLM fine‑tuning and evaluation infrastructure.
• Experience with RLHF/Constitutional AI/DPO.
• Contributions to open source ML infrastructure.

Responsibilities

• Build evaluation infrastructure for agent systems.
• Create benchmarks that measure real capability.
• Design data pipelines for behavioral data collection.

Skills

Expert-level at Python

ML frameworks (PyTorch)

Experience with wandb, MLflow

Track record of shipping ML systems

Strong opinions on eval criteria

Job description

Tzafon is a foundation model lab building scalable compute systems and advancing machine intelligence, with offices in San Francisco, Zurich & Tel Aviv. We’ve raised over $12m in 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 work between our product and post-training teams to ship Large Action Models that actually work. Build evals, benchmarks, and fine-tuning pipelines. Define what good model behavior means and make it happen at scale.

What you’ll do

• Build evaluation infrastructure for agent systems
• Create benchmarks that measure real capability
• Design data pipelines for behavioral data collection and analysis
• Implement fine‑tuning pipelines (wandb, distributed training infrastructure)
• Work with post‑training team on RLHF and behavioral optimization
• Build tools for model introspection and capability mapping
• Ship continuous evaluation systems that catch regressions before users do

We’re looking for

• Expert-level at Python and ML frameworks (PyTorch)
• Deep experience with LLM fine‑tuning and evaluation infrastructure
• Track record of shipping ML systems to production
• Strong opinions on what makes a good eval
• Experience with wandb, MLflow, or similar experiment tracking

Preferred Experience

• Built eval frameworks at AI labs or LLM companies
• RLHF/Constitutional AI/DPO implementation experience
• Published work on model evaluation or benchmarking
• Contributions to open source ML infrastructure
• Experience with multi‑agent systems or tool‑use models

Life at Tzafon

• Full medical, dental, and vision coverage, plus 401(k) in the US
• Office in SF, Zurich 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 starts at $150k‑$400k + equity package, depending on experience & location.

We also offer a referral bonus of $5k for referral of successful hires (send to [e-mail]).