Staff ML Engineer
Typeface - Palo Alto, CA
Posted Aug 19, 2025
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
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- Deadline
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Where they hire
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About this role
Staff ML Engineer Palo Alto, CA About Typeface We he lp 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 Staff Machine Learning Engineer/Applied Scientist , 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 - 10+ years of prior experience designing, building and scaling systems for training, testing, and running Machine Learning
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