Staff Machine Learning Engineer

Whisker•Auburn Hills, MI

4h•Onsite

About The Position

Whisker is redefining what it means to live with cats—designing intelligent systems that remove friction, elevate the everyday, and celebrate the quiet brilliance of feline companionship. Today, Litter-Robot leads the category. Tomorrow, an entire ecosystem that expands what’s possible for cats and the people who love them. We believe the future is feline. And we’re imagining that future today. We work onsite 4+ days a week, with our team based in Auburn Hills, Michigan, and Juneau, Wisconsin. Our team of 700+ passionate pet people thrives on collaboration, innovation, and the occasional office cameo from a four-legged friend. The Staff Machine Learning Engineer will lead the design, development, and deployment of production-grade AI and machine learning models, owning the end-to-end lifecycle from data ingestion and feature engineering through training, evaluation, inference, and continuous improvement in production. This role is responsible for defining scalable, secure, and high-performance AI architectures, including MLOps, automated CI/CD, model monitoring, and governance to ensure reliable real-world impact. The Staff Machine Learning Engineer will provide deep technical leadership and mentorship to engineering and data science teams, setting standards and best practices for building, operating, and scaling AI-powered systems across the organization.

Requirements

Bachelor’s, Master’s degree or PhD in Computer Science, Software Engineering, or a related field
15+ years of professional experience in Software Engineering
5+ years of proven experience as a software architect, demonstrating successful design, release and delivery of complex, scalable systems.
Technical expertise in the following areas:
5+ years of experience with Amazon S3
5+ years of experience with DynamoDB
4+ years of experience with AWS Lambda
3+ years of experience with IoT Core
2+ years of experience with Timestream
In-depth understanding of software design principles, patterns, and best practices
Expertise in Java, Python, or C++, particularly for complex, function-oriented software that interfaces with IoT devices
Experience supporting medium to large-scale, highly available, service-oriented, distributed production systems
Proficiency with object-oriented programming concepts, patterns and problem decomposition
Experience with cloud platforms, microservices architecture, and a strong grasp of system integration.
Excellent problem-solving skills and the ability to address technical challenges in a dynamic environment.
Strong leadership, communication, and interpersonal skills.
Proficient in using architecture modeling and design tools.
Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders.
Project management skills with a track record of successfully driving projects to completion.
A passion for staying updated on industry trends and continuously improving technical expertise.
Maintains confidentiality of proprietary information
Ability to maintain a professional atmosphere in a fast-paced environment with numerous interactions and interruptions
Ability to establish and maintain cooperative working relationships with Team Members and colleagues
Comfortable with office pets (cats, dogs)

Nice To Haves

Experience with CloudWatch, AppSync, Relational Databases, Kinesis Stream, CloudTrail, API Gateway, Cognito or VPC

Responsibilities

Leads the end-to-end architecture of production AI systems, including data pipelines, feature engineering, model training, evaluation, deployment, and inference, ensuring scalability, performance, and alignment with Whisker’s business objectives
Builds and ships AI models, contributing hands-on code across data preparation, model development, training workflows, and inference services, setting a high bar for production-quality AI engineering
Partners closely with product, data, and engineering leaders to translate business and customer needs into applied AI solutions, balancing model accuracy, latency, cost, and operational reliability
Provides technical leadership and mentorship across AI, data science, and software engineering teams, establishing best practices for model development, MLOps, testing, deployment, and ongoing model maintenance
Evaluates, prototypes, and recommends emerging AI and ML technologies, frameworks, and tooling that accelerate model development, improve production robustness, and advance Whisker’s AI capabilities
Ensures the integrity, security, and reliability of AI systems, including data governance, model versioning, monitoring, drift detection, and responsible AI practices throughout the lifecycle
Owns the full AI development lifecycle, from problem framing and experimentation through production deployment, monitoring, iteration, and continuous improvement of AI-powered products
Conducts regular code reviews and provides constructive feedback to ensure code quality
Designs, develop, lead implementation of robust, scalable security solutions across multiple platforms
Will perform additional responsibilities when required