Staff ML Engineer

Narrato; Palo Alto (CA); Hybrid; USD 190,000 - 234,000; Full time

Benefits offered by this job

Competitive compensation, equity

Medical, dental, vision insurance

HSA and FSA options

Flexible time off

Well-being programs

Lunch & snacks

Mentorship & impact

Job summary

Narrato is seeking a Staff Machine Learning Engineer/Applied Scientist for a hybrid role at our Palo Alto HQ. You will build scalable ML models and web apps to bring Generative AI capabilities to customers, collaborating with designers, product managers and engineers.

You will own roadmaps across text, image, audio and video content generation, establish model training and evaluation processes, and drive data-driven product metrics to accelerate growth.

Qualifications

• 10+ years of experience designing, building and scaling ML systems.
• Experience with training, evaluating, and deploying ML models at scale.
• Proven ability to translate complex problems into scalable solutions.

Responsibilities

• It is responsible for building ML models/systems and innovative web applications delivering Generative AI to customers.
• Define the roadmap for generation of content types (text, image, audio, video) to enable hyper-personalized, safe content.
• Own delivery of key business, product and technology initiatives across design, spec, development, testing and launch.
• Establish processes for model training, fine-tuning, testing, and operation at scale.
• Collaborate with engineers, Product, and Business teams to improve the product and drive growth.
• Drive data-driven development by defining and tracking product-level metrics.

Education

Master’s or PhD in Computer Science or related field

Tools

AzureML

GCP Vertex

AWS Sagemaker

Python

C/C++

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 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 models at scale
• 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.
• 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
• Bonus: Publications and research experiences in ML venues and/or vision/language applications

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 $190,000-$234,000. 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 Adobe, Microsoft, Google, 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).