ML Research Engineering Manager

WHO WE ARE

We are looking for talent to build the global standard for video understanding AI together!

Twelve Labs is creating the world's best video-specific AI models that effectively process vast amounts of video data to provide video-specific search, analysis, summarization, and insight generation capabilities.

Major sports leagues use Twelve Labs models to quickly and accurately select highlights from vast game footage, providing hyper-personalized viewing experiences. Domestic integrated control centers efficiently search CCTV footage with Twelve Labs to respond quickly to crisis situations. Major broadcasters and studios worldwide utilize Twelve Labs models for content production for billions of viewers.

Twelve Labs is a Deep Tech startup with offices in San Francisco and Seoul, recognized as one of the top 100 AI startups globally by CB Insights for four consecutive years. We have secured over $110 million in funding from world-class VCs and corporations including NVIDIA, NEA, Index Ventures, Databricks, and Snowflake. Our models are the only AI models developed in Korea to be serviced through Amazon Bedrock. We build innovative products with exceptional colleagues and grow with customers worldwide.

Twelve Labs works around the following core values:

• An attitude of honesty and reflection towards oneself and the team
• Perseverance and humility, unafraid of failure and feedback
• A mindset of continuously learning and enhancing the team's capabilities together

If you enjoy the process of growing by solving challenging problems together, your opportunity is here at Twelve Labs.

ABOUT THE TEAM

This team is responsible for the research and development of Twelve Labs' multimodal embedding model, Marengo. We research and develop models that integrate various modalities such as video, audio, and text into a single embedding space.

We cover diverse research topics including contrastive learning, temporal video understanding, and multimodal representation learning. We are responsible for the entire model development process, from building large-scale training data pipelines to designing model architectures, optimizing distributed training, and designing evaluation frameworks. We conduct large-scale experiments rapidly with access to world-class GPU resources like NVIDIA B300.

In an environment where the gap between research and production is very short, we collaborate closely with the Search, Product, and Infrastructure teams to continuously improve the quality of models used by thousands of customers worldwide.

ABOUT THE ROLE

As an ML Research Engineering Manager on the Marengo team, you will build and lead the research engineering group responsible for Twelve Labs' multimodal embedding models, owning both the team's technical roadmap and the growth of the engineers on it.

This is a player-coach role. You will manage a team of ML research engineers working on model architecture, training infrastructure, and data pipelines, while staying technically engaged enough to make sound architectural decisions and evaluate research direction. We're looking for someone who has built and shipped production ML systems themselves, and now wants to multiply their impact by enabling a team to do the same.

IN THIS ROLE, YOU WILL

• Manage and develop a team of ML research engineers: hire, onboard, run 1:1s, drive career growth, and build a high-performance engineering culture
• Own the team's technical roadmap and execution plan, aligning research priorities with product and business goals
• Define team structure, hiring plans, and resourcing across next-generation model development and training operations
• Make key technical trade-off decisions across model architecture, training methodology, data strategy, and infrastructure investment
• Drive hiring: define role profiles, evaluate candidates, and build a pipeline of strong research engineers
• Ensure research quality and engineering rigor through design review, experiment review, and setting clear standards for reproducibility and evaluation
• Coordinate cross-functionally with Search, Product, and Infrastructure teams on model integration, timelines, and dependencies
• Remove blockers, manage scope, and keep execution focused on highest-impact work

YOU MAY BE A GOOD FIT IF YOU HAVE

• 7+ years of industry experience in ML engineering or research engineering, with at least 2 years managing engineers or tech-leading a team
• Hands-on background building and shipping production ML systems: you've done the work yourself before asking others to do it
• Strong technical foundation in representation learning, contrastive learning, or large-scale model training, deep enough to evaluate research direction and make architectural calls
• Experience hiring and growing ML engineers: you've built teams, not just inherited them
• Track record of translating ambiguous research goals into concrete team roadmaps with clear milestones
• Strong communication skills: you can represent the team's work to leadership, align with cross-functional partners, and give direct, constructive feedback
• Proficiency in Python and PyTorch; you can still read and review code and experiment designs

This role is a strong fit for someone with an MS and deep industry experience who has transitioned from a top-performing IC into engineering leadership: someone who chose management because they wanted to multiply impact through people, not because they stopped wanting to be technical.

PREFERRED QUALIFICATIONS

• Experience managing research-oriented engineering teams (not just pure software engineering)
• Experience scaling a team through a high-growth phase (hiring 3+ engineers in a year)
• Experience with distributed training infrastructure and training operations at scale
• Background in multimodal learning, video understanding, or information retrieval
• Experience running performance cycles, calibrations, and career development frameworks
• Prior startup experience: comfort with ambiguity, speed, and wearing multiple hats

WHAT MAKES THIS ROLE UNIQUE

The gap between research and production is remarkably short here. Models you build will be used by thousands of companies worldwide within months. We work as a unified team toward the broader goal of video understanding, rather than solving isolated problems. Our research philosophy balances rigorous experimentation with real-world application: we aim to build multimodal systems that are powerful, trustworthy, and genuinely useful.

OTHERS

Work Location: Seoul Itaewon office + Pangyo satellite office

Even if you don't check every box, we encourage you to apply. If you're a zero-to-one achiever, a ferocious learner, and a kind team player who motivates others, you'll find a home at TwelveLabs.

HIRING PROCESS

Application Review → Recruiter Interview (비대면/30분) → Loop Interview [Hiring Manager Interview&Live Coding Test Interview] (대면/약 90분) → Loop Interview [System Design&Leadership-Final Round Interview] (비대면/약 120분) → Reference Check → Offer

BENEFITS AND PERKS

• Global Team growing with global B2B customers
• Hybrid work with both autonomy and collaboration
• MacBook and 700,000 KRW worth of remote work equipment for all employees, with latest equipment replacement every 3 years
• Corporate card with a monthly limit of 600,000 KRW for free use on meals, transportation, etc.
• Office snack bar (providing snacks, coffee, fresh food)
• 2-week winter break operation at the end of the year
• Annual health check-up support
• English education program support