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-language 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 $77 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 differences 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.
About the role
As the Lead ML Systems Engineer at Twelve Labs, you will lead the ML Engineering team, driving the development of optimal machine learning systems for video foundation (VFM) and language model (VLM) in production. Your role encompasses the entire spectrum of machine learning engineering, from optimizing and scaling the inference infrastructure, which involves extensive video processing both in the cloud and on-premise, to model deployment and operations, and data infrastructure. VFMOps & VLMOps is central to our user experience as it dictates the latency and deployment speed of the trained model.
For the first 3 to 6 months, you will be hands on and actively contribute as an individual contributor in our development process. As the lead, you will set the technical strategies and goals, recruit top talent, and be responsible for your team’s success, ensuring our machine learning systems exceed user expectations in terms of speed, efficiency, and reliability. Your expertise will be key in overcoming challenges related to processing vast amounts of video data and deploying sophisticated models in production. Together with your team, you will work to enhance our VFMOps & VLMOps, contributing to a superior user experience that distinguishes Twelve Labs from its competitors. Your leadership, technical expertise, and commitment to excellence will be critical to our team’s success and our users’ satisfaction.
In this role, you will
- Prioritize the team’s work in building and improving our machine learning systems in production for video foundation and language model (VFM & VLM), in collaboration with senior engineers and other stakeholders
- Inference Infrastructure: Construct the most performant, scalable, and reliable inference engine optimized for Twelve Lab’s video foundation and language models.
- ML Deployment & Operations (VFMOps / VLMOps): Lead the initiative in serving the model in the most optimized manner, deploying the pipeline, and automating the model training to deployment process.
- Data: Oversee the data infrastructure and preparation of high-quality video data for our training runs.
- Design processes (e.g. postmortem review, incident response, on-call rotations) that help the team operate effectively
- Coach and develop your reports to decide how they would like to advance in their careers and help them do so
- Run the team’s recruiting efforts through a period of rapid growth
You may be a good fit if you have
- 10+ years of software development experience, including experience in machine learning engineering
- 5+ years of experience in building end-to-end machine learning systems encompassing infrastructure, MLOps, and data management
- You have experience working with engineers at different levels and have coached them in their career development
- 2+ years of experience managing high output engineering teams
- Proficiency in working with video processing and data pipelining
- Experience in establishing and maintaining secure software and system development environments
Desired experience
- MS or PhD in Computer Science, Math, or equivalent real-world experience
- Fast-paced startup engineering experience
- Experience working with large scale models
- Experience working with both cloud and on-premise environment
- ML research experience would be helpful, as this role requires interchangeable effort on both research side and software side
- Experience in handling large-scale computing system and firm understanding on scale-up and scale-out approach in cloud environment
Relevant tech stack
- Language: Python, Golang, C++, CUDA
- ML / Platform: PyTorch, Docker, Kubernetes, Terraform
- ML Demo page: Gradio, Streamlit
- MLOps: MLFlow, Weights and Biases
- Data: Pachyderm, DVC
- Automation: Airflow, Kubeflow
- Model serving: Triton, FasterTransformer
Interview and Onboarding Process
Recruiter Phone Screen -> Phone Interview -> Technical Screen -> Onsite Interview -> Reference Checks
We’re also excited to share that we’ll do global onboarding in Seoul for all new hires (company-sponsored travel).
Even if there are a few checkboxes that aren’t ticked through your prior experience, we still encourage you to apply! If you are a 0-to-1 achiever, a ferocious learner, and a kind and fun team player who motivates others, you will find a home at Twelve Labs.
We welcome applicants from all walks of life and are committed to equal-opportunity employment. We cherish and celebrate diversity not just because it is the right thing to do, but because it makes our company much stronger.
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.
🏙 Remote-flexible, offices in San Francisco and Seoul and coworking stipend
🛂 VISA support (such as H1B and OPT transfer for US employees)
