Machine Learning Engineer, Safety
- Pay
- $180,000 – $250,000 per year
- Location
- San Francisco, CA · On-site
- Job type
- Full-time
- Level
- Mid-level
- Listed
- 23 days ago
Skills & highlights for this role
- PyTorch
- Kubernetes
- trust and safety detection systems
- model inference at scale
Also useful
- diffusers
- content moderation
Stated benefits & perks
- Health
- Dental
- Vision
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
About fal
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.
Equal opportunity and legal notices
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.
From fal's careers page, first listed on Rolev.ai on October 17, 2026. Rolev.ai is not the employer.
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Common questions
What is the salary for the Machine Learning Engineer, Safety role at fal?
The Machine Learning Engineer, Safety posting at fal states compensation of $180,000 – $250,000 per year. It is listed as a full-time position. Final pay may depend on location, experience, and interview evaluation on fal's official career site.
Where is the Machine Learning Engineer, Safety job at fal located?
This Machine Learning Engineer, Safety position at fal is located in San Francisco, CA (On-site). Always check fal's application page for specific state eligibility or relocation policies.
What qualifications are required for Machine Learning Engineer, Safety at fal?
For the Machine Learning Engineer, Safety role, fal highlights experience with PyTorch, Kubernetes, trust and safety detection systems, model inference at scale. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
How do I apply for the Machine Learning Engineer, Safety position at fal?
This listing links directly to fal's Ashby application page. You can apply directly on fal's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Ashby application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.