Staff Engineer, ML/AI Platform

About the role

Attentive is seeking a Staff Software Engineer to enhance its Machine Learning Platform team as a key individual contributor. In this role, you will be responsible for architecting and constructing the foundational infrastructure that empowers ML engineers and data scientists to efficiently train, deploy, and manage models and intelligent systems at scale. This position provides a unique opportunity to influence the architectural evolution of AI and ML within the organization, transitioning the platform to support a variety of models, including traditional approaches, deep learning, reinforcement learning, and agentic workloads for a subscriber base exceeding half a billion.

Key facts

What you'll do

• Design the architecture of the ML platform, encompassing data pipelines, training systems, and serving layers, utilizing technologies such as Ray, MLFlow, Metaflow, Argo, and Spark.
• Develop and sustain a production-ready, low-latency model serving infrastructure, incorporating lifecycle management features like champion/challenger testing, automated rollouts, versioning, and rollback capabilities.
• Spearhead the development of the agentic stack from inception, ensuring robust performance and scalability.
• Provide insights from an ML infrastructure perspective during multi-quarter AI strategy discussions across various teams.
• Mentor and guide platform and ML engineers, fostering their professional development and growth.
• Establish shared interfaces, architectures, and design patterns, including data access layers and prediction serving APIs, to align platform functionalities with product needs.
• Collaborate with cross-functional teams to ensure seamless integration of ML capabilities into existing products and services.
• Monitor and optimize the performance of ML models in production, ensuring they meet the required service level agreements (SLAs).

Requirements

• A minimum of 7 years of experience specifically in ML Platform or MLOps roles.
• Proven track record of ownership over essential ML platform components, utilizing tools such as Spark, Ray, MLFlow, Kubeflow, or Metaflow.
• Practical experience in building and managing high-throughput agentic stacks, including data infrastructure, context stores, orchestration, and prompt layers.
• Proficient in Python for both batch processing and online service development.
• Familiarity with designing and managing both online and offline inference systems, along with a solid understanding of their respective trade-offs.
• Strong problem-solving skills and the ability to work independently as well as collaboratively in a team environment.

Nice to have

• Experience with champion/challenger shadow testing and automated pipelines for model promotion.
• Background in scaling real-time feature streaming for low-latency, high-volume reinforcement learning applications.
• Knowledge of best practices in data governance and compliance in the context of ML and AI.

Skills & tools

• Backend: Proficient in Java, Kotlin, Spring Boot microservices, Gradle, DynamoDB, Aurora, AirFlow, Postgres, and Redis.
• Infrastructure: Experienced with Kubernetes on AWS EKS, Istio, Datadog, Terraform, CloudFlare, and Helm.
• Frontend: Familiar with React, TypeScript, GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright.
• ML/AI: Skilled in Python, Metaflow, HuggingFace, PyTorch, TensorFlow, Pandas, and both custom and open-source ML models, including industry-leading LLMs.

Practical notes

• The base salary range for this position in the United States is between $200,000 and $300,000 annually, in addition to equity and benefits.
• Compensation is determined based on the specific role, level of experience, and geographic location.
• Attentive has employee hubs located in New York City, San Francisco, London, and Sydney, while also supporting a distributed global workforce.
• The company collaborates with over 8,000 clients across more than 70 industries, including notable names like Crate and Barrel, Urban Outfitters, and Carter's.
• Attentive has been recognized on the Deloitte Fast 500 list for four consecutive years and has appeared on the Forbes Cloud 100 list for five years running.
• Candidates who may not meet every listed requirement are still encouraged to apply, as the company values diverse experiences and perspectives.
• Reasonable accommodations are available for candidates with disabilities throughout the application process.