Join fal as a Machine Learning Engineer to enhance safety systems in a hands-on role within a growing AI platform.
Posted by employer 1 day ago
First seen on Joblaze 1 day ago
Last verified on the company career page 1 day ago
Skills & Technologies
What you'll build
- Design ML models for safety systems
- Build and maintain ML infrastructure
- Improve detection pipelines
- Integrate safety systems into core infrastructure
- Evaluate third-party safety tooling
Must have
- Prior hands-on experience in trust & safety
- Strong end-to-end engineering fundamentals
Nice to have
- Comfortable owning ambiguous problems
Practical constraints
- Based in San Francisco; in-person, 5 days a week
Role intensity
70% hands-on coding
AI in the day-to-day
Engineers work on ML models and infrastructure for safety systems, integrating new techniques and tools.
Not disclosed in this posting: years of experience, visa sponsorship.
Benefits
Joblaze summary
In this role, the Machine Learning Engineer focuses on developing and maintaining the machine learning models and infrastructure that underpin fal's safety systems, ensuring effective detection of harmful content. Key skills include proficiency in Python, PyTorch, and Kubernetes, along with a solid understanding of trust and safety protocols. This position is ideal for someone with hands-on experience in content moderation or abuse detection, capable of tackling complex, high-stakes challenges. The role is part of a dedicated team that prioritizes safety while rapidly deploying AI advancements.
Joblaze insights
- Listed yesterday — first seen on Joblaze September 29, 2026. Last confirmed on Fal's careers page September 29, 2026.
- Salary band is in line with the typical range for AI/ML roles (median ~$190,000).
- Starts above 69% of 81 comparable mid ai/ml roles in United States that list AI/ML we track (median $152,000 across 36 companies). See AI/ML salary trends
- AI/ML appears in 51% of 445 comparable mid ai/ml roles in United States; Kubernetes appears in 11.7% of 445 comparable mid ai/ml roles in United States.
Quick facts
- Is the Machine Learning Engineer, Safety role remote?
- No — this is an on-site role in San Francisco, California, United States.
- What's the salary range?
- Fal lists $180,000–$250,000 for this role.
- Where is the role based?
- Fal is hiring for this position in San Francisco, California, United States.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AI/ML, Kubernetes, Python, Torch.
- What seniority level is this role?
- Fal targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Machine Learning Engineer, Safety role at Fal.
From the original posting
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
Standard company text repeated across Fal's postings is omitted here.