---
title: 'Machine Learning Engineer, Safety at fal'
canonical: 'https://feeny.ai/job/machine-learning-engineer-safety-fal-san-francisco-kjtcfjs1d0s0'
type: 'job'
last_seen: '2026-10-15'
---

# Machine Learning Engineer, Safety at fal

- **Company:** fal
- **Location:** San Francisco, CA
- **Compensation:** $180k–$250k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-09-28
- **Last confirmed live:** 2026-10-15
- **Apply:** https://jobs.ashbyhq.com/fal-ai/ae1ab033-5e45-46da-9f20-55ac350eb0e9

## Job description

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.

## About fal

## Company Overview
- **One-liner**: fal provides a serverless generative media platform for developers, enabling lightning-fast inference for image, video, audio, and 3D AI models.
- **Entity Type**: Private (Series D)
- **Headquarters**: San Francisco, California, USA
- **Founded**: 2021
- **Founders**: Burkay Gur, Gorkem Yurtseven

## Core Business
- **Industry**: Technology, Information, and Internet (Generative AI Infrastructure)
- **Target Customers**: B2B — developers, enterprises, and research labs building generative AI applications.
- **Mission**: Build the world’s first generative media platform for developers, enabling real-time AI content creation at scale.

## Products & Services
- **fal Inference Engine™**: A globally distributed serverless runtime optimized for large ML models on thousands of GPUs (H100, H200, B200). Up to 10x faster than alternatives, with 99.99% uptime and no cold starts.
- **Model Gallery**: A library of 1,000+ production-ready generative media models (image, video, audio, 3D) accessible via a unified API and SDKs.
- **Dedicated Compute Clusters**: On-demand or reserved GPU clusters for fine-tuning, training, or running custom models, with access to 1000s of Blackwell GPUs.
- **fal Compute**: Hourly GPU pricing for dedicated VMs, starting at $1.89/hr for high-end hardware.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (most recent round: $140M Series D)
- **Key Metric**: $140M Series D raised
- **Total Funding**: At least $163M across rounds (Pre-Seed $9M, Series A $14M, Series D $140M)
- **Notable Investors/Partners**: Sequoia Capital, Andreessen Horowitz (a16z), Bessemer Venture Partners, Kleiner Perkins, NVIDIA
- **Growth Signals**:
    - Headcount grew 246% year-over-year to ~84 employees
    - Trusted by 1.5M+ developers and leading enterprises
    - Powers AI features for public companies and hypergrowth startups
    - SOC 2 compliant and enterprise-ready

## Competitive Advantages
- **Serverless, globally distributed inference engine** purpose-built for generative media, eliminating GPU configuration and cold starts.
- **Massive scale**: Capable of handling 100M+ daily inference calls with enterprise-grade reliability.
- **Proprietary distributed data-feeding engine** and deep optimization for diffusion models.
- **Deep ecosystem**: 1,000+ pre-integrated models and strong partnerships with NVIDIA and top-tier VCs.
- **Developer-first experience**: Unified API, SDKs, and per-output pricing model reduce barriers to deployment.

## Strategic Focus
- **Global infrastructure scaling**: Expanding GPU fleet across regions to meet accelerating demand for generative media.
- **Enterprise adoption**: Strengthening compliance (SOC 2, SSO), private endpoints, and dedicated support for large customers.
- **Generative Media Fund**: Investing in the next generation of companies building in the space.
- **Talent acquisition**: Aggressively hiring across engineering, go-to-market, and operations to keep pace with growth.

## Why Work Here
- **Engineering culture**: Fast-paced, high-agency environment focused on infrastructure and ML performance. Teams own critical systems from day one.
- **Work model**: Primarily in-person at downtown San Francisco office. Remote opportunities available for exceptional candidates.
- **Visa sponsorship**: Offered with relocation support to San Francisco.
- **Benefits**: Competitive salary and equity, health/dental/vision insurance, regular team events and offsites.
- **Growth trajectory**: Company is scaling rapidly (headcount +246% YoY) with ambitious goals to 1000x usage, offering significant career growth opportunities.
- **Impact**: Work on the foundational platform powering generative AI for millions of users and leading enterprises.

## Sources
1. [fal.ai](https://fal.ai/)
2. [fal Careers](https://fal.ai/careers)
3. [fal Blog - Series D Announcement](https://blog.fal.ai/our-series-d-scaling-fal/)
4. [LinkedIn - fal](https://www.linkedin.com/company/features-and-labels)
5. [Greenhouse Jobs Board](http://job-boards.greenhouse.io/fal)

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