F

Fal

NLP-based sentiment & anomaly detection

Business Recruiter

Full-Time
$160k - $200k/yr+ Equity
Senior
San Francisco, CA, USA
In Person
People & HRGeneralist Recruiting

About the job

Requirements
  • At least 5 years of full-cycle recruiting experience, including meaningful in-house experience at a high-growth startup.
  • A track record recruiting for both technical roles, including engineering, infrastructure, and machine learning, and non-technical roles, including go-to-market, finance, legal, and operations.
  • Ability to identify and source strong candidates who are not applying.
  • Ability to advise senior leaders, disagree with hiring managers when appropriate, and support recommendations with data.
  • Ability to own offer and compensation conversations and close candidates.
  • Ability to run searches independently without waiting for direction.
  • Genuine interest in artificial intelligence and generative media and motivation to help build a company in this space.
Responsibilities
  • Own searches end to end, including intake, strategy, sourcing, screening, interview process, offer, and close, across engineering, research, go-to-market, finance, legal, and operations.
  • Advise the business on role design and realistic expectations using market data, and inform hiring managers about candidate-market conditions.
  • Identify candidates beyond obvious LinkedIn searches, including people with adjacent backgrounds, under-the-radar builders, and passive candidates.
  • Build candidate pipelines through direct outreach, referrals, communities, events, and artificial-intelligence sourcing tools, and write effective outreach.
  • Represent the company to candidates, understand their priorities, conduct compensation conversations, and secure signed offers.
  • Help calibrate interview loops and screens to prioritize high agency and independent thinking.
  • Improve recruiting processes, templates, and reporting in Ashby, and use artificial-intelligence tools to automate repetitive recruiting work.
Desired Qualifications
  • Experience at an artificial-intelligence, infrastructure, or developer-tools company.
  • Experience hiring for early or first-of-kind roles where the candidate profile needs to be defined.
  • Familiarity with Ashby, artificial-intelligence sourcing tools, and automation tools.

About the company

F

Fal

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Website

Fal.ai helps businesses improve data analytics using NLP and ML, focusing on sentiment analysis and anomaly detection within dbt data models. It analyzes text from customer reviews, support tickets, and surveys to label sentiment as positive, negative, or neutral, and flags unusual patterns in data transformations. The platform integrates with existing data infrastructure using dbt models and is offered via tiered subscriptions that include basic sentiment analysis, advanced anomaly detection, and premium support. Its goal is to help data-driven organizations make informed decisions, improve customer satisfaction, and get continuous analytics updates.

Company Size

51-200

Company Stage

Late Stage VC

Total Funding

$943.9M

Headquarters

Seattle, Washington

Founded

2021

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Simplify Jobs

Simplify's Take

What believers are saying

  • September 2026 H3 Max and Turbo are priced at $0.02-$0.04 per second through September 30.
  • fal says 2.5 million developers use its infrastructure, expanding distribution for new launches.
  • fal Agent and Sound Effects 1.0 broaden workflows from generation into orchestration and audio.

What critics are saying

  • The Maricopa County case names FAL in January 2026 over explicit AI content.
  • H3 Max depends on MiniMax's open weights, exposing fal to supplier leverage and cloning.
  • Model commoditization turns fal into a low-margin router if customers bypass its stack.

What makes Fal unique

  • fal's September 2026 Lucent acquisition deepens creative-workflow control beyond raw model hosting.
  • fal's inference stack serves 1,300+ production endpoints across 1,000+ models, per September 2026 PR.
  • H3 Max combines post-training and inference co-design, winning September 2026 video benchmarks.

Help us improve and share your feedback! Did you find this helpful?

Benefits

  • Health Insurance
  • Dental Insurance
  • Vision Insurance
  • Company Equity
  • Relocation Assistance

Growth & Insights and Company News

6 month growth

-2%

1 year growth

2%

2 year growth

-4%
Unite.AI
Oct 19th, 2026
Fal debuts FLUX 3 Max video model post-trained with Black Forest Labs.

Fal debuts FLUX 3 Max video model post-trained with Black Forest Labs. Published October 19, 2026 Jonas Reeve, Cognitive AI & AGI AI Research Agent fal announced FLUX 3 Max on October 19, 2026, a video generation model post-trained by fal Research in collaboration with Black Forest Labs on the FLUX 3 foundation model. The model became available the same day through fal's inference platform, and fal reports that it combines top-tier image-to-video quality with generation speeds far faster than competing models at similar quality ratings. How fal Research and Black Forest Labs built the model. The launch pairs two research teams with distinct roles: Black Forest Labs, which developed the FLUX 3 foundation model, and fal Research, whose work spans post-training, reinforcement learning, inference optimization, and systems engineering. fal Research worked directly with the FLUX 3 model, continuing its training to improve visual fidelity, motion coherence, prompt adherence, and overall generation performance. In the announcement, Black Forest Labs co-founder and CEO Robin Rombach said FLUX 3 was built as a foundation for others to build on, and he described fal's customization of the model for developers and enterprises on fal's platform as the kind of collaboration FLUX was designed for. fal CEO Burkay Gur said the launch combines Black Forest Labs' foundation model with his team's research into quality and inference performance, adding that he believes some of the most important advances in generative AI will come from optimizing models and the systems that run them together. Black Forest Labs' homepage carries a banner stating that FLUX 3 Max is 22 times faster than Seedance 2.5 at the same quality, and it directs visitors to fal's product page. fal's FLUX 3 Max product page describes three layers of work behind the model: post-training conducted with Black Forest Labs; inference optimization that changed how the model executes to cut generation latency and raise throughput while preserving quality; and systems engineering that tuned the serving path on fal's own inference engine for production workloads. FLUX 3 Max follows H3 Max, fal Research's previously released post-trained video model. fal said H3 Max produced video in 3.49 seconds in its benchmark, which it described as faster-than-real-time generation, while achieving top-tier image-to-video quality in independent evaluations. The product page notes that H3 Max, at 7.55 seconds, is the only faster model in its published comparison. fal Head of Research Kaan Oktay said the team achieved a 50-point Elo improvement while making inference more than 11 times faster, and that fal Research is continuing to post-train the model. fal describes this launch as the first iteration of FLUX 3 Max, with further improvements to visual quality, generation speed, and overall performance underway. Reported quality and speed figures. fal reported that FLUX 3 Max reached a 1,139 Elo rating across 4,868 votes in preliminary independent human preference evaluations on Artificial Analysis Video Arena, a result the company said places the model among the highest-quality image-to-video systems evaluated. fal's latency benchmark in the release measured generation of a 10-second video at 10.95 seconds, which the company described as 22 times faster than Seedance 2.5's 277.80 seconds at the same reported Elo rating and 11.5 times faster than the original FLUX 3's 126.44 seconds. The release also reports a 50-point image-to-video Elo gain over the original FLUX 3, from 1,089 to 1,139. The product page publishes a different latency figure. It lists a 12.45-second average for a 10-second 720p video, describing the improvement over FLUX 3 as roughly 10 times faster, and a comparison table listing Gemini Omni Flash 1.1 at 1,134 Elo and 47.37 seconds, MiniMax H3 at 768p at 1,141 Elo and 83.26 seconds, Wan 3.0 at 1,127 Elo and 180.16 seconds, Seedance 2.5 at 1,139 Elo and 277.80 seconds, and the original FLUX 3 at 1,089 Elo and 126.44 seconds. The page identifies the Elo figures as Artificial Analysis's preliminary AA-Video-I2V v1.1 ratings and the generation times as averages for a 10-second 16:9 video, and it describes FLUX 3 Max as tied for first place in image-to-video quality while noting that MiniMax H3 is listed first on that board. Artificial Analysis's image-to-video leaderboard, which ranks models by Elo derived from blind pairwise human preference votes cast by validated evaluators, listed FLUX 3 Max at 720p with a 1,138 Elo rating plus or minus 15 across 5,054 samples, ranked second behind MiniMax H3 at 768p with 1,140 Elo. The board lists Seedance 2.5 at 1,138 Elo and the original FLUX 3 at 1,086 Elo, and it dates FLUX 3 Max's release to October 2026. Availability and launch pricing. FLUX 3 Max is served through fal's inference platform under a unified API. The announcement describes access to text-to-video, image-to-video, and keyframes-to-video generation, while the product page lists two endpoints at launch, text to video and image to video, both at 720p. According to the page, content generated through the fal.ai API may be used in commercial projects under fal's terms. Launch pricing is set at $0.0425 per second of 720p output video, billed per second with no minimums and no subscription. The product page states that the rate is 75 percent off the $0.17-per-second list price and runs until November 7, 2026, and fal's release describes the discount as running for the first three weeks. Jonas Reeve is an AI-generated research agent at Unite.AI, focusing on cognitive AI, artificial general intelligence (AGI), and the theoretical foundations of machine intelligence. His work explores how learning, reasoning, memory, and abstraction emerge in both biological and artificial systems, drawing connections between modern AI architectures and long-standing questions in cognitive science and philosophy of mind. With a conceptual and reflective approach, Jonas examines frameworks such as reasoning models, agentic systems, emergent cognition, and alignment theory, aiming to clarify what progress toward AGI actually means - and what it does not. Rather than chasing timelines or hype, he emphasizes first principles, conceptual rigor, and the limits of current models. Articles authored by Jonas Reeve are AI-generated and reviewed by Unite.AI's editorial team to ensure accuracy, clarity, and responsible discussion of advanced AI concepts.

PR Newswire
Sep 14th, 2026
fal Acquires Lucent, Welcomes Co-Founders Dimi Panagiotopoulos and Alex Koumpas to the team

/PRNewswire/ -- Dimi Panagiotopoulos Lucent's Co-founder and CTO, is a blend of engineer and creative technologist. By the age of 21 he had built and shipped...

Online Casino Reports
Sep 13th, 2026
AI video Generation pushes us closer to the world of Blade Runner 2049.

AI video Generation pushes Online Casino Reports closer to the world of Blade Runner 2049. Shane. - September 13, 2026 Ready to live in the world of Blade Runner? AI can now create video faster than you can watch it. Online Casino Reports explore what could be when instant AI video supports generative online casinos, interactive entertainment and even virtual social experiences. Earlier this year, Shanghai-based AI company MiniMax built an exciting new AI model. MiniMax H3 was considered a breakthrough in generative AI in the video space and was described as follows: MiniMax H3 is an open-weights, general-purpose multimodal AI model that generates up to 15 seconds of high-definition 2K video with native stereo audio from text, image, video, and audio inputs. Then an American-based competitor, Fal, adapted the model and elevated it to new heights with the release of their own version called MiniMax H3 Max. The Max iteration pushed the capabilities of the original model significantly further, delivering: * Lightning Speed: Generates any 5-second video clip in less than 3 seconds, making it 35 to 50 times faster than the base model. * Native Audio: The model creates synchronised stereo sound and dialogue during the same pass. * Resolution Options: The model supports 480p and 768p outputs at 24 frames per second. * Generation Modes: Create videos using both Text-to-Video and Image-to-Video. This means it can generate new content faster than humans can watch it. In a world where seamless integration and the appearance of live engagement are key, this is a watershed moment. Incredible live stream test. A Fal engineer showcased the potential of MiniMax H3 Max by using it to run a live stream. He revived an old idea, channel flipping, by connecting the AI to different tabs, each running its own ongoing stream of randomised prompts, and then simply flipping between them. Each flip of the "channel" presented him with a completely new scene from a completely new show. This turns Bruce Springsteen's "57 Channels and Nothin' On" from a tongue-in-cheek song lyric into science-fiction reality. Then came the really interesting part: viewers in the chat could type in their own ideas and instructions, and the AI would begin incorporating them into the video. The audience could effectively determine the direction of the content, influencing the scenes, events and even the eventual outcome of something being created in real time. Imagine not liking how Game of Thrones Season ended and simply prompting your own conclusion. Have AI create the action-packed, storyline-wrapping finale you always felt the show deserved while you watch. Better yet, ever complained that there's just nothing worth watching anymore? This technology could eventually allow anyone to create their own channels for private viewing, or even distribute them to a wider audience. Suddenly, everyone could claim the title of arteur. Have Claude write you a story. Feed it into MiniMax H3 Max. While you're at it, have ChatGPT design you a business card that reads: Indie AI Filmmaker & Showrunner And congratulations. You're officially a one-man studio. Future online casino application. While most conversations around this technology are focused on television and movie production, for the online gambling industry it represents something potentially much more interesting: a step toward truly interactive, AI-hosted casinos. Online Casino Reports has already seen impressive work from companies such as RAVATAR in creating virtual hosts with distinct personalities, voices and other characteristics. Once those virtual characters become the blueprint for AI video that can respond to user engagement on the fly, Online Casino Reports could have an AI host that players can actually speak to and joke with, without ever needing to type into a chat window. With near-instant video responses to spoken interaction, the experience moves beyond what Online Casino Reports currently see with chatbots and starts to resemble K (played by Ryan Gosling) interacting with his virtual companion Joi (played by Ana de Armas) in Blade Runner 2049. This virtual "person" would know your preferences. Remembers your previous conversations. Responds instantly. Develops a personality around your interactions. And, over time, builds up a shared history with you. There is also the wishlist Online Casino Reports drew up years ago when Online Casino Reports discussed the future of AI and casino gaming. Give an AI access to the mathematical models powering different game types, and it could potentially begin creating custom gambling experiences on demand. Feel like fishing that day? Ask your AI host to create a casino game where you fish the Great Lakes, pulling different species from the water for different prizes. Want something that feels more like a video slot? Use a slot-game engine. Prefer fixed odds? Use a fixed-odds engine. This evolves an online casino from a collection of premade games of chance into something that can generate an entirely new experience every time you sign into your player account. The future is coming, but what a price tag. As exciting as all of this is, there is one major hurdle the technology has to clear before it can become an everyday reality: the exorbitant cost. At the moment, running the model can cost more than $1,000 per hour, meaning it simply isn't ready to be deployed as a mainstream commercial product. But, as Online Casino Reports has seen with everything from "AI can't do hands" to "AI people could never fool us," new technology can move remarkably quickly from an impressive idea to an accessible, everyday tool. While the future of fully interactive AI-powered gaming may not be here quite yet, there is already plenty for you to explore today. 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HyperAI
Sep 5th, 2026
MIT phd Li Muyang launches Nunchux AI to accelerate multimodal inference.

MIT phd Li Muyang launches Nunchux AI to accelerate multimodal inference. Nunchux AI has officially launched as a new player in the generative AI infrastructure space, founded by MIT doctoral graduate Li Muyang, Carnegie Mellon University associate professor Zhu Junyan, and researchers Yujun Lin and Zhekai Zhang. The company targets the growing industry demand for efficient, low-cost, and reliable multimodal inference as deployment scales rapidly. Backed by early-stage investments from Emergence Capital and E14 Fund, MIT Media Lab, Nunchux AI builds upon a decade of research into neural network compression and system optimization. Li's academic work, particularly the SVDQuant framework for 4-bit weight and activation quantization, forms the technical foundation of the venture. This research materialized in Nunchaku, an open-source inference engine that drastically reduces memory footprint and latency, enabling high-resolution image generation on consumer hardware. The engine has secured significant developer adoption, recording nearly 4,000 GitHub stars and native compatibility with major open-source models and development frameworks. Commercially, the startup will debut Modelverse, a unified API platform integrating over thirty image, video, and virtual avatar models. The service offers two operational tiers: Radical Speed for ultra-low latency and Radical Value for cost optimization. Unlike existing inference aggregators that primarily manage GPU orchestration, Nunchux AI pursues vertical integration by combining custom quantization algorithms with optimized inference kernels. This approach delivers superior performance and lower overhead on identical hardware. The Nunchaku core will remain open-source, while commercial revenue will be driven by premium API access, enterprise-grade customization, and dedicated developer support. The venture extends the entrepreneurial legacy of MIT professor Han Song's HAN Lab, which previously spawned companies such as DeePhi Tech, OmniML, Eigen AI, and Inco AI. Academic production continues in parallel, with recent publications including the FourTune paper explicitly listing the company as an affiliation. In a crowded inference market featuring competitors like fal.ai and Replicate, Nunchux AI differentiates itself through algorithmic efficiency rather than mere aggregation. The founding team maintains that reducing latency and deployment costs is critical for preserving creative velocity and democratizing access to advanced generative models, while strictly preserving output fidelity. This news is intelligently aggregated by AI to deliver industry updates efficiently. It does not constitute opinions or advice. MIT Technology Review

PR Newswire
Sep 1st, 2026
fal launches H3 Max video model with faster-than-real-time generation, ranks #1 on Design Arena and Artificial Analysis benchmarks

Fal, a generative media platform, has launched H3 Max, a new video generation model that ranks first on independent benchmarks from Artificial Analysis and Design Arena. The model generates five-second videos in approximately three seconds, achieving faster-than-real-time generation. Built on the open-weights MiniMax H3 model, H3 Max was developed through post-training for improved prompt adherence and visual quality. Fal reports the system delivers roughly 35 times the throughput of the official MiniMax H3 endpoint and averages 15 times faster than comparable quality models. H3 Max is available through the fal API and Playground. During a promotional launch period ending 7 September, pricing starts at $0.04 per second at 768p resolution, rising to $0.08 per second thereafter. Fal developed the model by co-designing training and inference optimisation, treating them as a single problem rather than separate layers.