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Fal AI

Machine Learning Engineer, Safety

Fal AI is hiring a Machine Learning Engineer, Safety in San Francisco, United States. It pays $180k-$250k a year and Level rates it ; you can apply on Fal AI.

Level's read on this job

  • Builds AI ●●●● is how Level rates this machine learning engineer role: the job is building AI systems.
  • Tools and skills the posting cites include Python, Torch and Diffusers.
  • Level classifies it as a mid-level role.
  • Level lists 46 other open roles at Fal AI.

AI in this role

Build and maintain machine learning models and infrastructure for safety and abuse detection systems on the fal generative media platform.

PythonTorchDiffusersKubernetesFal Sdk
machine-learningmlopstrust-and-safetypytorchinfrastructure

fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products.

As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on.

About this role:

fal is looking for a Machine Learning Engineer to own the ML and the ML infrastructure that power our safety systems end-to-end — from the models that detect harmful content and misuse to the pipelines and infrastructure that run them reliably at scale. This is a dedicated, hands-on engineering role sitting on the Trust & Safety team, working alongside our safety engineering function to keep detection capability ahead of a fast-growing platform with 1,000+ models.

What you’ll do:

  • Design, build, and maintain the ML models and the ML infrastructure behind fal's safety and abuse-detection systems, end-to-end

  • Improve the accuracy, coverage, latency, and scalability of detection pipelines across the platform

  • Partner with Security and Infrastructure Engineering to integrate safety systems deeply into core platform infrastructure

  • Evaluate and integrate third-party safety tooling and vendor models where it makes sense

  • Stay current with the ML safety/detection landscape and bring new techniques and infrastructure patterns into fal's stack

  • You will have access to our massive GPU cluster for inference and evaluation

  • Some core technologies we use include Python, torch, diffusers, Kubernetes, and the fal Python SDK

  • You'll work alongside a team dedicated to quickly iterating on and deploying new AI breakthroughs — your job is to make sure that speed never comes at the cost of safety

Qualifications/Nice to have:

  • Prior hands-on experience in trust & safety, content moderation, or abuse/detection systems — required

  • Strong end-to-end engineering fundamentals — comfortable owning both the ML and the infrastructure that serves it in production

  • Comfortable owning ambiguous, high-stakes problems with limited precedent

  • Based in San Francisco; fal works in-person, 5 days a week

What we offer at fal:

  • Interesting and challenging work

  • Competitive salary and equity

  • A lot of learning and growth opportunities

  • We offer relocation assistance to San Francisco.

  • Health, dental, and vision insurance (US)

  • Regular team events and offsite

Comp:

  • 180k - 250k + equity + comprehensive benefits package

U.S. EQUAL EMPLOYMENT OPPORTUNITY INFORMATION:

fal provides equal employment opportunities to applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other classification protected by applicable law.

How we rate this

Machine Learning Engineer, Safety at Fal AI rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Machine learningMLOpsTrust And SafetyPyTorchInfrastructurePythonTorchDiffusers

Also common in machine learning engineer jobs at this level

Pay

This job starts at
$180k
Typical machine learning engineer job
$198k

This posting starts 9% below the typical machine learning engineer job. See machine learning engineer jobs

Questions you could be asked

  1. Tell me about a project where machine learning was part of your work. What did you do?
  2. Tell me about a project where mlops was part of your work. What did you do?
  3. Tell me about a project where trust and safety was part of your work. What did you do?
  4. Tell me about a project where pytorch was part of your work. What did you do?
  5. Tell me about a project where infrastructure was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Machine learning, MLOps, Trust And Safety, PyTorch, and Infrastructure. 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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