Twelve Labs Inc.
Staff Machine Learning Engineer, Partnerships
Twelve Labs Inc., San Francisco, California, United States, 94199
Who We Are
At TwelveLabs, we are pioneering the development of frontier multimodal foundation models that can see, hear and understand the world as humans do. Our models have redefined the standards in video-language modeling, allowing developers to build programs with state-of-the-art semantic search, summarization and analysis capabilities.
About The Role As a Staff Machine Learning Engineer, Partnerships at TwelveLabs, you will drive company growth in our highest leverage go-to-market channel: development of our core technology and models on partner platforms (AWS, Snowflake, Databricks, and others). AWS Bedrock (https://aws.amazon.com/bedrock/twelvelabs/) is one such partner platform.
Applying your ML and cloud engineering expertise to catalyze our business and product partnerships is the essence of the role. This role is a perfect fit for experienced engineers with some past machine learning experience who want to scale product impact by leveraging internal and external collaboration.
See our CEO Jae's keynote from AWS Re:invent for more on the expansion of TwelveLab's partnership with AWS: https://www.youtube.com/watch?v=ggfWAg4RnGg
In This Role, You Will:
Productize Twelve Labs’ video foundation models & products into fault-tolerant, low-latency, scalable systems suitable for partner deployments
Design and deliver deep technical integrations with partner platforms such as AWS, Snowflake, Databricks, etc.
Own technical execution for partner integrations, serving as the subject matter expert for complex engineering and production concerns
Collaborate directly with engineering and product teams from our partners to co-design capabilities and influence joint roadmaps
Mentor junior engineers/researchers, and hold a high bar around code quality / engineering best practices
Lead by example in interviewing, hiring, and onboarding passionate and empathetic engineers
You May Be A Good Fit If You Have:
10+ years of relevant industry experience
Led organization- and/or company- level ML infrastructure projects from brainstorming and inception to realized product impact
Defined technical roadmap and prioritization for large
#J-18808-Ljbffr
About The Role As a Staff Machine Learning Engineer, Partnerships at TwelveLabs, you will drive company growth in our highest leverage go-to-market channel: development of our core technology and models on partner platforms (AWS, Snowflake, Databricks, and others). AWS Bedrock (https://aws.amazon.com/bedrock/twelvelabs/) is one such partner platform.
Applying your ML and cloud engineering expertise to catalyze our business and product partnerships is the essence of the role. This role is a perfect fit for experienced engineers with some past machine learning experience who want to scale product impact by leveraging internal and external collaboration.
See our CEO Jae's keynote from AWS Re:invent for more on the expansion of TwelveLab's partnership with AWS: https://www.youtube.com/watch?v=ggfWAg4RnGg
In This Role, You Will:
Productize Twelve Labs’ video foundation models & products into fault-tolerant, low-latency, scalable systems suitable for partner deployments
Design and deliver deep technical integrations with partner platforms such as AWS, Snowflake, Databricks, etc.
Own technical execution for partner integrations, serving as the subject matter expert for complex engineering and production concerns
Collaborate directly with engineering and product teams from our partners to co-design capabilities and influence joint roadmaps
Mentor junior engineers/researchers, and hold a high bar around code quality / engineering best practices
Lead by example in interviewing, hiring, and onboarding passionate and empathetic engineers
You May Be A Good Fit If You Have:
10+ years of relevant industry experience
Led organization- and/or company- level ML infrastructure projects from brainstorming and inception to realized product impact
Defined technical roadmap and prioritization for large
#J-18808-Ljbffr