Lead MLOps Engineer / Sagemaker

We're looking for a Senior Machine Learning Engineer to join one of the 100 Best Companies to Work For, with offices in the Chicagoland area and remote flexibility, on a full-time basis. This leading supplier of maintenance, repair, and operating products for businesses and a wide range of industries across the globe has a focus on sustainability, social responsibility, and community engagement, serving more than 4.5 million customers worldwide.

In this role, you'll collaborate with a talented group of Engineers, Architects, and Leaders to spearhead the design of a cutting-edge Computer Vision platform. To ensure the efficient and effective deployment and maintence of our machine learning models, you will collaborate closely with datascientists, software engineers, and key stakeholders.

If you are ready to make an impact and be part of a team that is revolutionizing how businesses thrive, apply now and join us on this exciting journey. Required Skills & Experience

• Bachelor's or Master's degree in a field such as Statistics, Applied Mathematics, Physics, Engineering, Computer Science, or Economics or equivalent experience.
• 4+ years of experience with SQL, Python
• Experience with AWS Sagemaker or similar too
• High level of proficiency in wrapping models in C/Python code and serving them as REST APIs
• 3+ years of relevant working experience in an analytical role involving data extraction, analysis, and communication of findings
• 4+ years of building models using traditional statistical methods and optimizing inference speeds of models when served as endpoints
• 3+ years of experience deploying models into the cloud with tooling like Docker & Kubernetes
• Experience automating data augmentation and refresh using Airflow and Bash Scripting
• Ability to effectively communicate technical solutions to engineering teams and business audiences

Desired Skills & Experience

• Utilize code (Python, SQL) for analyzing and building statistical models to solve specific business problems like anomaly detection, behavioral clustering, classification, and demand forecasting
• Build, test, and deploy customer-facing analytical and ML endpoints & APIs that are a mixture of business logic, model, and data
• Contribute to the design and development of Insight generation methods using Order History, Product Utilization, Customer Industry Classification, and Search History data
• Collaborate with researchers, software developers, and business leaders to define product requirements and provide analytical support
• Work backward from customer use cases, engender implementation of ML models that solves the use-cases at scale
• Articulate concepts and generate visual representations of the data product

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.

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