Staff ML Engineer

What You'll Do

As a Staff Machine Learning Engineer/Applied Scientist, you will build machine learning models/systems and innovative web applications that deliver Generative AI to customers. You will work with designers, product managers, and engineers on 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 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 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 product and drive growth
• Establish a data-driven development culture by driving definition, tracking, and operationalizing of 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 for real-world problems
• Track record of new ideas or improvements in machine learning, demonstrated by 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
• Experience working at a high-growth startup or tech company
• Publications and research experiences in ML venues and/or vision/language applications

Base Salary

The range for this role is $218,000-$234,000. Actual compensation may vary based on level, experience, and skillset.