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Applied AI Engineer, Field Engineering

ZipRecruiter
Full-time
On-site
San Francisco, California, United States
Who we are

At Twelve Labs, we are pioneering the development of cutting-edge multimodal foundation models that have the ability to comprehend videos just like humans do. Our models have redefined the standards in video- modeling, empowering us with more intuitive and far-reaching capabilities, and fundamentally transforming the way we interact with and analyze various forms of media. With a remarkable $107 million in Seed and Series A funding, our company is backed by top-tier venture capital firms such as NVIDIA’s NVentures, NEA, Radical Ventures, and Index Ventures, and prominent AI visionaries and founders such as Fei-Fei Li, Silvio Savarese, Alexandr Wang and more. Headquartered in San Francisco, with an influential APAC presence in Seoul, our global footprint underscores our commitment to driving worldwide innovation. We are a global company that values the uniqueness of each person’s journey. It is the in our cultural, educational, and life experiences that allow us to constantly challenge the status quo. We are looking for individuals who are motivated by our mission and eager to make an impact as we push the bounds of technology to transform the world. Join us as we revolutionize video understanding and multimodal AI. The role

As an

Applied AI Engineer , you will be a hands-on technical expert helping customers turn TwleveLabs’ full stack video understanding AI into production-ready solutions. You’ll prototype, integrate, and optimize AI applications built on TwelveLabs’ models and products, collaborating closely with our Science, Product, and Engineering (SPE) teams to extend model capabilities and build repeatable patterns for real-world adoption. This role sits at the intersection of

AI research and applied engineering : you’ll help customers explore what’s possible, then roll up your sleeves to make it practical, scalable, and secure. What you’ll do

Prototype and build

applications and workflows using TwelveLabs models and products.

Experiment and tune

TwelveLabs models using customer data.

Integrate into customer stacks : Bring TwelveLabs powered solutions to customers in a format consumable by their teams.

Develop evaluation frameworks

for accuracy, latency, cost, and robustness in production workloads.

Create reusable assets

(code samples, reference apps, documentation) to accelerate adoption across multiple accounts.

Collaborate with SPE : co-design experiments, validate new capabilities, and influence roadmap through applied field insights. Innovation starts in the field.

Required experience

5+ years in software engineering, machine learning engineering, applied machine learning, or a related field with a focus on building model driven, production workloads.

Deep familiarity with data science fundamentals

Working knowledge of linear algebra and its application to embeddings

Ability to analyze customer data, design experiments, and interpret results for both technical and non-technical stakeholders.

History of rich internal documentation and communication

Nice to have

Experience dealing with video at scale using tools such as ffmpeg and a fundamental understanding of how video compression and processing techniques

Strong proficiency in

Python

and common AI/ML libraries

Proficiency in C, C++, Rust, or a similar lower-level, performance oriented

Familiarity with

LLM/multimodal workflows : embeddings, retrieval-augmented (RAG), prompt engineering & orchestration, agentic systems, and/or evaluation frameworks

Experience deploying AI/ML systems in

cloud environments

(AWS, GCP, or Azure), including containerization

Benefits and Perks

An open and inclusive culture and work environment. Work closely with a collaborative, mission-driven team on cutting-edge AI technology. Full health, dental, and vision benefits Extremely flexible PTO and parental leave policy. Office closed the week of Christmas and New Years. VISA support (such as H1B and OPT transfer for US employees)

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