---
title: 'Software Engineer, Applied Machine Learning at fal'
canonical: 'https://feeny.ai/job/software-engineer-applied-machine-learning-fal-san-francisco-rhz2qr697k2v'
type: 'job'
last_seen: '2026-10-15'
---

# Software Engineer, Applied Machine Learning at fal

- **Company:** fal
- **Location:** San Francisco, CA
- **Compensation:** $180k–$230k
- **Employment:** full-time
- **Posted:** 2026-10-13
- **Last confirmed live:** 2026-10-15
- **Apply:** https://jobs.ashbyhq.com/fal-ai/c351a0de-1826-4968-a023-a5243aba2ec6

## 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: We are seeking a hands-on, production-focused Applied Machine Learning Engineer to take technical ownership of the model layer powering our next-generation generative media platform. In this role, you will bridge the gap between cutting-edge generative research and scalable, consumer-facing products. You will split your time between extending SOTA open-source models with additional capabilities and helping maintain our fleet of generative model APIs. What you’ll do:

- Novel Model Pipelines: Work with our post-training team to extend SOTA image, video, audio, and 3D models with additional capabilities and modalities. Develop novel approaches to model conditioning, generation, and editing, including both training-free methods and model fine-tuning.
- Fine-Tuning: Leverage our massive GPU fleet to fine-tune generative models for novel capabilities. Build and maintain fine-tuning APIs that allow customers to customize models for their specific needs.
- Architecture & Abstraction: Identify common patterns across the models we serve and develop reusable components, abstractions, and building blocks that accelerate the development of new model capabilities and inference pipelines.
- Inference Optimization: Work hand-in-hand with our ML Performance & Optimization team to apply state-of-the-art inference techniques and best practices, ensuring models run efficiently with low latency, high throughput, and optimal GPU utilization.
- Production Deployment: Build, deploy, and maintain scalable, reliable generative model APIs. Anticipate and resolve production challenges to ensure our models serve customers reliably at scale.
- Customer Collaboration: Work directly with customers, including some of the world's largest e-commerce retailers and film and TV production studios, to develop novel solutions to their generative media needs.

Qualifications/Nice-to-haves:

- Experience: 3+ years of professional experience as an Applied ML Engineer, with at least 1–2 years focused on generative media or computer vision.
- Core Frameworks: Expert-level proficiency in Python and PyTorch.
- Generative Media: Deep practical understanding of diffusion and flow-based generative models.
- Open-Source Tooling: Hands-on experience working with open-weight model ecosystems, including Hugging Face, Diffusers, and related tooling.
- Engineering Rigor: Ability to anticipate and solve challenges that arise when deploying ML models to production. Strong engineering judgment in designing systems that are scalable, reliable, secure, safe, and performant.
- Training-Free Model Extensions: Experience designing and implementing training-free extensions to image, video, audio, or 3D generative models, such as novel conditioning methods, inference-time modifications, or new model capabilities.
- Model Post-Training: Experience developing and executing custom post-training or fine-tuning approaches to extend generative models with additional capabilities.
- Startup Experience: Track record of working in fast-paced startup environments or digital media and entertainment industries.
- Ability to Ship: Demonstrated ability to independently take ambitious ML ideas from concept to production.

What we offer at fal:

- Interesting and challenging work
- A lot of learning and growth opportunities
- Health, dental, and vision insurance (US)
- Regular team events and offsites

## Compensation

- $180,000 - $230,000 + 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)

## Other roles at fal

- [Influencer Marketing Manager](https://feeny.ai/job/influencer-marketing-manager-fal-san-francisco-vmqtx4fpnkxv) — San Francisco, CA
- [Infrastructure Accounting Lead](https://feeny.ai/job/infrastructure-accounting-lead-fal-san-francisco-ddfpyd0njt0e) — San Francisco, CA
- [Senior/Staff Software Engineer, Forward Deployed](https://feeny.ai/job/senior-staff-software-engineer-forward-deployed-fal-san-francisco-0jw2vrfsjj4j) — San Francisco, CA
- [Software Engineer, Machine Learning-Backend](https://feeny.ai/job/software-engineer-machine-learning-backend-fal-san-francisco-d3tnnz2gd7xj) — San Francisco, CA
- [Senior Software Engineer, Machine Learning Infrastructure & Automation](https://feeny.ai/job/senior-software-engineer-machine-learning-infrastructure-automation-fal-united-yn92t5ee7v00) — United States
- [Senior Software Engineer, Full Stack (Serverless)](https://feeny.ai/job/senior-software-engineer-full-stack-serverless-fal-san-francisco-cne8pnqchjjy) — San Francisco, CA
- [Field Marketing Manager, Enterprise & ABM](https://feeny.ai/job/field-marketing-manager-enterprise-abm-fal-san-francisco-m05rec34ndeb) — San Francisco, CA
- [Event Marketing Manager](https://feeny.ai/job/event-marketing-manager-fal-san-francisco-hqpptrw1s9j1) — San Francisco, CA
- [Technical Content Marketing Manager, Infrastructure](https://feeny.ai/job/technical-content-marketing-manager-infrastructure-fal-san-francisco-4ezha0ywcwhk) — San Francisco, CA
- [Product Marketer, Infrastructure](https://feeny.ai/job/product-marketer-infrastructure-fal-san-francisco-db7ckz5ww674) — San Francisco, CA