Typeface

Technology

MLEngineer

$145–195k ~AI est. Palo Alto, California, United States Remote Friendly
Market Sentiment
HIGH DEMAND

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optimal for Mid candidates.

The Brief

“ML Engineer at Typeface”

Industry & Context.

Technology
Problems you'll solve

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Full Job Description

About Typeface 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. What You’ll Do As a  Machine Learning Engineer, you will be responsible for building machine learning models/systems and innovative web applications that deliver the power of Generative AI to our customers. You will work closely with designers, product managers and other engineers driving the technical designs and implementations. How You’ll Make an Impact 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 What You Bring 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 accomplis

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