TixelJobs
T
Typefacevia Greenhouse

Senior Staff ML Engineer

Palo Alto, CA$200K - $247K/yrPosted 2w ago
ML EngineerStaff+Full-time#ai-lab

Not sure if you're a good fit?

Upload your resume and TixelJobs AI will compare it against Senior Staff ML Engineer at Typeface. Get a match score, missing keywords, and improvement tips before you apply.

Free preview · Your resume stays private

About the Role

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 Senior Staff Machine Learning Engineer, you will operate at the company level—defining technical strategy, driving architectural decisions, and shaping the future of generative AI at Typeface. 

You will lead the design of large-scale ML systems and shared platforms that power all generative capabilities across agents, text, image, audio, and video. This role requires a strong combination of deep technical expertise, product intuition, and the ability to influence teams and leadership. 

How You'll Make an Impact

  • Define and drive the long-term technical vision for generative AI across Typeface’s product ecosystem 
  • Lead architecture and design of scalable ML platforms (training, evaluation, inference, safety) used across multiple teams 
  • Drive company-level ML strategy, aligning technical investments with product and business priorities 
  • Influence and partner with executive leadership, product, and design to shape high-impact initiatives 
  • Mentor senior engineers and raise the technical bar across the ML organization 
  • Architect and lead development of large-scale generative AI systems powering agentic orchestration and multimodal content generation 
  • Define and evolve shared ML infrastructure and platforms for training, fine-tuning, evaluation, and serving 
  • Drive cross-team initiatives spanning multiple ML systems and product areas 
  • Establish best practices for ML system evaluation, safety, reliability, and performance at scale 
  • Identify and incubate 0→1 opportunities in generative AI with high business impact 
  • Make high-leverage technical decisions that unlock velocity across teams 
  • Mentor and guide engineers across levels, influencing 
    Share