We inspire purpose-filled living that brings joy to the modern home. With a team of more than 8,000 associates spanning 130 store and distribution locations across the U.S. and Canada, we achieve together, drive results and innovate to inspire. Drawn together by a shared passion for our customers and a spirit of fun, we deliver high-quality home furnishings that are expertly designed, responsibly sourced and bring beauty and function to people’s homes. From the day we opened our first store in Chicago in 1962 to the digital innovations that engage millions of customers today, our iconic brand is nearly 60 years in the making—and our story is still unfolding.
We are looking for a Senior AI Engineer to serve as a key individual contributor, responsible for designing, building, and deploying machine learning systems that directly impact our core product capabilities. You will be integral to the implementation, model optimization, and reliability of our production AI services. This role is perfect for a hands-on engineer who thrives on solving complex technical challenges and driving projects autonomously from conception through deployment, making a tangible difference with every line of code.
This position is fully remote
This role is an Individual Contributor
A day in the life as a Senior AI Engineer...
Design, develop, train, and fine-tune complex ML models (deep learning and classical techniques) to solve high-priority business problems, with deployment targeted primarily on Google Cloud Platform
Own end-to-end model deployment on GCP (Vertex AI, GKE, Cloud Run), ensuring performance, scalability, and stability under low-latency production requirements
Build and maintain MLOps pipelines on GCP (Vertex AI Pipelines, Cloud Build, Artifact Registry) for automated training, testing, versioning, and CI/CD
Design and build agentic AI systems and multi-agent workflows using frameworks such as Google ADK, LangChain, LlamaIndex, or AutoGen, integrated with GCP services (Vertex AI, Gemini models)
Write clean, well-tested, production-grade Python and C# code; participate actively in code reviews to uphold engineering standards.
Profile and optimize training and inference speed and cost, particularly for large datasets and distributed/constrained environments on GCP infrastructure
Author technical user stories covering the full ML development lifecycle
Actively participate in and help drive team ceremonies, sprint planning, and continuous process improvement
Partner with Data Engineering to define data infrastructure, features, and pipelines (BigQuery, Dataflow, Pub/Sub) needed for training and serving
Partner with DevOps and Cloud teams to build reliable, cost-optimized ML solutions on GCP
Collaborate continuously with product owners and stakeholders to refine technical solutions and roadmaps within an agile framework
Implement monitoring dashboards (Vertex AI Model Monitoring, Cloud Monitoring) to track drift, accuracy, latency, and cost, addressing issues proactively
Proactively identify, develop, and validate new features to improve model performance and generalization
Mentor engineers on ML and GCP best practices, and provide technical leadership on architecture decisions.
What you'll bring to the table...
Strong hands-on experience with Google Cloud Platform for ML: Vertex AI (Training, Pipelines, Model Registry, Endpoints, Model Monitoring), BigQuery, Cloud Run, GKE, and Cloud Build
Strong proficiency in Python and C#, with deep experience in core ML frameworks (TensorFlow, PyTorch, scikit-learn)
Strong knowledge of Agentic AI frameworks: Google ADK, AutoGen, LangChain, LlamaIndex, and experience integrating with Gemini/Vertex AI foundation models
Strong understanding of distributed training, model serving architecture, and best practices for scaling ML applications on GCP
Hands-on experience with MLOps tools (Vertex AI Pipelines, MLflow, DVC, Kubeflow) and containerization (Docker, Kubernetes/GKE)
Direct experience building and deploying ML solutions on Google Cloud (Vertex AI required); familiarity with AWS SageMaker or Azure ML a plus
Solid theoretical foundation in machine learning, statistics, and optimization techniques
Proficient in SQL (BigQuery), Pandas, and large-scale data processing (Dataflow/Apache Beam, Spark)
Deep understanding of agile methodologies
Strong communication, collaboration, and technical leadership skills
Proven ability to mentor and guide other engineers
Strong software engineering fundamentals: coding standards, code reviews, source control, testing, and operations
Excellent problem-solving and cross-functional communication skills
We'd love to hear from you if you have...
Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related field (or equivalent practical experience)
5+ years of experience in machine learning engineering
Proven track record of successfully designing, implementing, and deploying at least 2-3 significant ML models into a high-availability production system
Euromarket Designs, Inc., which does business as Crate and Barrel and CB2, will be referred to as “the Company”. The Company is deeply committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation for any part of the application process, or in order to perform the essential functions of a position, please contact the location you are applying to here and ask to speak with a manager regarding the nature of your request.
The Company is an equal opportunity employer; applicants are considered for all positions without regard to race, color, religious creed, sex, national origin, citizenship status, age, physical or mental disability, sexual orientation, gender identity, marital, parental, veteran or military status, unfavorable military discharge, or any other status protected by applicable federal, state or local law.
The Company participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the US.
State / City Compliance: The Company will consider for employment qualified applicants with criminal history, including arrest and conviction records, in accordance with the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance.
Bachelor's degree or equivalent practical experience, 5+ years in machine learning engineering, production ML deployments, strong Python and C#, GCP, ML frameworks, MLOps, distributed training, and technical leadership experience.
Key Responsibilities
- developing ML models
- deploying models
- building pipelines
Skills & Tools
Google Cloud Platform, Vertex AI, GKE, Cloud Run, Vertex AI Pipelines, Cloud Build, Artifact Registry, Google ADK, LangChain, LlamaIndex, AutoGen, Gemini, Python, C#, TensorFlow, PyTorch, scikit-learn, MLflow, DVC, Kubeflow, Docker, Kubernetes, AWS SageMaker, Azure ML, SQL, BigQuery, Dataflow, Pub/Sub, Apache Beam, Spark, Pandas, Cloud Monitoring
Job Details
- Category: Software Development
- Seniority: Senior Level
- Commitment: Full Time
- Workplace: Remote — Illinois, United States
- Languages: English
About Crate and Barrel
An international retailer of modern furniture, housewares, and decor operating stores and distribution centers across North America. — Industry: Retail and Wholesale