Senior ML Engineer
Palo Alto, CA
- Pay
$188,000–200,000/year · BaseAnnual period assumed — pay source
Base Salary The range for this role is $188,000-$200,000. Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits
Read the full posting- Work setup
Hybrid stated — work setup source
Location This is a hybrid role based in our Palo Alto HQ. We collaborate in-office 3 days a week. Base Salary
Read the full posting- Employment
- Unconfirmed
What you’ll work on
Full postingYou will work closely with designers, product managers and other engineers driving the technical designs and implementations.
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.
From the employer’s posting
What You’ll Do As a Senior 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
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.
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.
What you’ll bring
All qualificationsCore experience
- Master’s or PhD 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.
- 5+ years of prior experience designing, building and scaling systems for training, testing, and running Machine Learning models at scale
- Proficiency in Python, C/C++ (or equivalent)
- Ability to create self-contained, reusable, and testable modules and passionate about prototyping
- Prior experience with AzureML, GCP Vertex, AWS Sagemaker or similar platforms
Qualification wording
Master’s or PhD 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.
5+ years of prior experience designing, building and scaling systems for training, testing, and running Machine Learning models at scale
Proficiency in Python, C/C++ (or equivalent)
Ability to create self-contained, reusable, and testable modules and passionate about prototyping
Prior experience with AzureML, GCP Vertex, AWS Sagemaker or similar platforms
Education & alternatives
What You Bring - Master’s or PhD 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.
Tools in this posting
- Python
- AWS
- Google Cloud (GCP)
- SageMaker
- C++
- C
Source — Tool mentions in context
- 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
- Ability to create self-contained, reusable, and testable modules and passionate about prototyping - Prior experience with AzureML, GCP Vertex, AWS Sagemaker or similar platforms - Bonus: Hands-on experience in deploying and tuning Generative AI models in cloud or on local system
Benefits in the posting
Full benefits wording- Competitive compensation — including salary, equity, and 401(k)
- Full medical, dental, and vision insurance for you and your family
- HSA and FSA options to support your financial wellness
- Flexible time off — including parental leave
- Well-being programs — resources to support your mental and physical health
- Daily lunch & snacks
- Equality Opportunity Statement We welcome and encourage applicants from all backgrounds. Employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, medical condition, veteran status, or any other legally protected status. We comply with applicable laws in every jurisdiction where we operate.
From the employer’s posting.
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 Senior 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
- Master’s or PhD 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.
- 5+ 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
- Prior experience with AzureML, GCP Vertex, AWS Sagemaker or similar platforms
- Bonus: Hands-on experience in deploying and tuning Generative AI models in cloud or on local system
- Bonus: Experience working at a high-growth startup or tech company
- Publications and research experiences in ML venues and/or vision/language applications are a plus
Location
This is a hybrid role based in our Palo Alto HQ. We collaborate in-office 3 days a week.
Base Salary
The range for this role is $188,000-$200,000. Actual compensation may vary based on level, experience, and skillset as assessed in the interview process.
Benefits
- Competitive compensation — including salary, equity, and 401(k)
- Full medical, dental, and vision insurance for you and your family
- HSA and FSA options to support your financial wellness
- Flexible time off — including parental leave
- Well-being programs — resources to support your mental and physical health
- Daily lunch & snacks
- Mentorship & impact — work closely with top AI leaders on products that ship
Equality Opportunity Statement
We welcome and encourage applicants from all backgrounds. Employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, medical condition, veteran status, or any other legally protected status. We comply with applicable laws in every jurisdiction where we operate.
Why You’ll Love Working Here
- Build something big — Be part of a fast-growing startup defining a new category: marketing orchestration powered by Agentic AI.
- Your work will matter — Trusted by Fortune 100 companies, our platform delivers 10x content velocity and 90% faster campaigns.
- A+ team — Collaborate with veterans from Meta, Amazon, Adobe, Google, Microsoft, and top AI companies.
- Backed by the best — GV, Salesforce Ventures, Microsoft, Lightspeed, Madrona and Menlo ($165M raised).
- Recognized for innovation — TIME Best Inventions, Fast Company Next Big Thing in Tech, Gartner Cool Vendor, Adweek AI Company of the Year, LinkedIn Top Startup, Webby Award (AI Work & Productivity).
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
Already applied? Track this application
Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Base Salary The range for this role is $188,000-$200,000. Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits
- Location & working pattern
Palo Alto, CA
Location This is a hybrid role based in our Palo Alto HQ. We collaborate in-office 3 days a week. Base Salary
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Sep 24, 2026
- Recorded sightings
- 6
- Last seen by us
- Oct 12, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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