TzafonPosted 14mo ago

Member of Technical Staff – Applied AI

Member of Technical Staff – Applied AI at Tzafon scores 100 out of 100 on AI centrality, which makes it a Level 4 role on this board.

San FranciscoleadFullTime$150k-$400k

AI in this role

pytorchmlflowweights-and-biases

fine-tuningai-evaluation

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 [email protected]).

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Fine TuningAI EvaluationPyTorchMlflowWeights And Biases

Questions you could be asked

Walk me through fine-tuning a model: what data did you use, and how did you check the result?
How do you decide that one model's output is better than another's for a given task?
What are the limits of PyTorch that you've run into, and how did you work around them?
What's a project where you used Mlflow hands-on?
Walk me through how you've used Weights And Biases in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Fine Tuning, AI Evaluation, PyTorch, Mlflow, and Weights And Biases. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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