Senior AI Engineer
Crate & BarrelAbout the role
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
Responsibilities
- Design, develop, train, and fine-tune complex ML models to solve high-priority business problems
- Own end-to-end model deployment on GCP, ensuring performance, scalability, and stability
- Build and maintain MLOps pipelines for automated training, testing, versioning, and CI/CD
- Design and build agentic AI systems and multi-agent workflows using various frameworks
- Write clean, well-tested, production-grade Python and C# code
- Profile and optimize training and inference speed and cost
- Author technical user stories covering the full ML development lifecycle
- Participate in team ceremonies, sprint planning, and continuous process improvement
Qualifications
- Strong hands-on experience with Google Cloud Platform for ML
- Strong proficiency in Python and C#
- Strong knowledge of Agentic AI frameworks
- Understanding of distributed training and model serving architecture
- Experience with MLOps tools and containerization
- Solid theoretical foundation in machine learning, statistics, and optimization techniques
- Proficient in SQL and large-scale data processing
- Deep understanding of agile methodologies
Skills mentioned
About Crate & Barrel
At Crate & Barrel, we help people build a home with purpose. Founded in 1962, Crate & Barrel Holdings (CBH) is an industry-leading home furnishings specialty retailer, including the brands Crate & Barrel, Crate & Kids, CB2, and Hudson Grace. A leader in omnichannel retail and direct marketing, we believe in the experience of physical stores and embracing the customer experience by offering inspired living across all of our platforms. From curated product sourcing and production to custom delivery and set-up in more than 90 countries, our 7,500 talented associates form the dynamic teams that keep our company running and growing. Today, Crate & Barrel Holdings is owned by the Otto Group, a Hamburg, Germany based global family of retailers and retail-related service providers focused on digital innovation, technology, sustainability and corporate responsibility. We operate more than 100 stores throughout the U.S. and Canada, and hold international franchise locations in nine countries, including six franchise eCommerce platforms. To learn more about Crate and Barrel, visit www.crateandbarrel.com. To become a part of our family of brands, visit our careers site at www.jobs.crateandbarrel.com and www.jobs.cb2.com