AI/ ML Engineer

Crate and Barrel; Northbrook (IL); Hybrid; USD 80,000 - 120,000; Full time

Job summary

Crate and Barrel is looking for an AI / Machine Learning Engineer with 2-5 years of experience to enhance our production machine learning systems. The role involves developing data pipelines, implementing core models, and ensuring the operation of AI services. This position is ideal for engineers eager to learn MLOps and contribute to valuable user-facing features.

The role allows for independent work while being part of a collaborative team environment. If you have strong Python skills and experience in machine learning, we encourage you to apply.

Qualifications

• 2+ years of experience in machine learning engineering or data science.
• Solid understanding of core machine learning concepts.
• Good grasp of software development principles.

Responsibilities

• Write and test machine learning algorithms and models.
• Develop and maintain data pipelines for model training.
• Conduct A/B testing and validation experiments.
• Work within MLOps frameworks to deploy models.
• Diagnose and resolve issues related to model performance.
• Maintain model monitoring tools to track production metrics.

Skills

Proficiency in Python

Familiarity with essential ML libraries

SQL experience

Strong communication skills

Experience with cloud platforms

Education

Bachelor's degree in Computer Science/Engineering/Mathematics/Statistics or equivalent

Tools

Docker

Kubernetes

MLflow

Job description

We are looking for an AI / Machine Learning Engineer with 2-5 years of experience to play a critical role in building and enhancing our production machine learning systems. You will be responsible for the day-to-day implementation of core models, developing efficient data pipelines, and ensuring the smooth operation of our AI services. This role is ideal for an engineer eager to solidify their production skills, learn MLOps best practices under senior guidance, and immediately contribute to impactful, user-facing features.

• This position is fully remote
• This role is an Individual Contributor position

A day in the life as an AI/ML Engineer

• Write, implement, and test machine learning algorithms and models under the guidance of senior team members, focusing on defined project scopes.
• Develop and maintain efficient data pipelines and scripts for cleaning, transforming, and augmenting large datasets necessary for model training and evaluation.
• Assist in the iterative process of developing, managing, and validating new features to improve existing model performance.
• Design and conduct rigorous A/B testing and validation experiments to measure model performance and impact before and after deployment.
• Work within our existing MLOps frameworks (e.g., Docker, Kubernetes, MLflow) to help deploy and manage models in cloud production environments.
• Quickly diagnose, debug, and resolve issues related to model performance, data pipelines, and production inference services.
• Help set up and maintain model monitoring tools to track key production metrics, latency, and data/model drift.
• Participate in agile ceremonies to contribute to effective sprint planning, transparent communication, and the successful delivery of sprint goals.
• Work closely with product owners and other cross-functional team members to deeply understand user stories and deliver valuable solutions in alignment with sprint goals.
• Contribute to the continuous improvement of development processes and tools through active participation in team retrospectives and feedback loops.
• Write clean, maintainable, and well-documented code and contribute to the development and maintenance of internal knowledge bases and documentation repositories to facilitate information sharing and team learning.
• Stay current with relevant technologies and industry trends.

What you’ll bring to the table

• Proficiency in Python and fundamental familiarity with essential ML libraries (e.g., scikit-learn, PyTorch, TensorFlow).
• Solid understanding of core machine learning concepts, statistical methods, and common algorithm families (e.g., regression, classification, clustering).
• Experience with SQL and working with relational or NoSQL databases for data extraction and preparation.
• Good grasp of software development principles, version control, and unit testing practices.
• Basic experience or strong foundational knowledge of deploying applications or using services on a major cloud platform (AWS, Azure, or GCP).
• Proven ability to analyze data, interpret model results, and clearly communicate findings.
• Strong communication and collaboration skills, with the ability to effectively interact with cross-functional team members.
• Ability to work independently on assigned tasks and contribute actively as a valued member of a self-organizing team.

We’d love to hear from you if you have…

• 2+ years of experience in machine learning engineering, data science or a related role.
• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field (or equivalent practical experience).