ML Engineer

Typeface•Palo Alto, CA

16h•$135,000 - $160,000•Hybrid

About The Position

We help the world’s biggest brands move from brief to fully personalized campaigns — in days, not months. Founded by Abhay Parasnis and backed by Microsoft, GV, Salesforce, Lightspeed, Madrona and Menlo, we’re building category-defining technology at the intersection of creativity and AI with real impact. Join us to help shape the future of enterprise marketing.

Requirements

Bachelor or Master's degree in computer science or a related field
Experience with building and evolving ML Training and Inferencing systems at significant scale with a purpose of solving real-world problems.
3+ years of prior experience designing, building and scaling systems for training, testing, and running Machine Learning models at scale
Have a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects
Proficiency in Python, C/C++ (or equivalent)
Ability to create self-contained, reusable, and testable modules and passionate about prototyping

Nice To Haves

Prior experience with AzureML, GCP Vertex, AWS Sagemaker or similar platforms
Hands-on experience in deploying and tuning Generative AI models in cloud or on local system
Experience working at a high-growth startup or tech company
Publications and research experiences in ML venues and/or vision/language applications

Responsibilities

Define the roadmap for generation of various content types including text, image, audio and video enabling us to generate brand-affinized, hyper-personalized, and safe content
Own the delivery of key business, product and technology initiatives across design, specification, development, testing, and launch.
Establish and implement processes for model training, fine-tuning, testing, and operating the Generative AI models at significant scale.
Investigate, prototype and deliver innovative solutions
Collaborate with other engineers, Product and Business Teams to identify new ways to improve our product and drive growth
Establish a data-driven development culture by driving the definition, tracking, and operationalizing of feature, product, and company-level metrics