Machine Learning Software Engineer II

Job not on LinkedIn

🕒 May 6

🇺🇸 United States – Remote

⏰ Full Time

🟢 Junior

🟡 Mid-level

🤖 Machine Learning Engineer

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Cambium Learning Group

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2009

📚 Education

🤖 Artificial Intelligence

Education • Artificial Intelligence

Cambium Learning Group is a company focused on providing essential educational solutions through a family of companies. They create experiences designed to help educators and students succeed by leveraging technology, including artificial intelligence and machine learning. Cambium Learning Group's brands are among the most respected in the edtech sector, supporting meaningful work and innovation in education. Their commitment is reflected in their dedication to making every learning moment valuable and impactful.

📋 Description

• Lead the transition of machine learning models from theoretical prototypes into scalable, high-performance production systems. • Architect and deploy ML solutions utilizing AWS ECS (Elastic Container Service) for containerized workloads and AWS Lambda for serverless, event-driven inference pipelines. • Optimize PyTorch models for production deployment by converting them to ONNX formats. • Apply advanced inference optimization techniques (quantization, pruning, ONNX Runtime) and memory-efficient attention mechanisms like Flash Attention to minimize latency and maximize throughput. • Champion infrastructure best practices for machine learning systems, establishing reliable CI/CD pipelines, and ensuring robust, secure, and reproducible deployments across the AWS ecosystem. • Design, develop, and evaluate algorithms that generate descriptive, diagnostic, predictive, and prescriptive insights from both structured and unstructured data. • Write clean, efficient, and well-tested code. Complete rigorous testing, debugging, and documentation to ensure seamless installation and long-term maintenance. • Actively participate in research discussions, requirements gathering, and system design alongside domain experts to build tailored scoring and ML solutions.

🎯 Requirements

• 2–5 years of industry experience in Machine Learning Engineering, Software Engineering, or Data Science, with a proven track record of architecting and deploying models to production. • Deep, hands-on experience with the AWS ecosystem, specifically AWS ECS and Lambda. • Solid understanding of containerization (Docker) and event-driven architectures. • Strong proficiency in modern programming languages used in ML (e.g., Python, C++, Java) and familiarity with industry-standard coding practices. • Hands-on experience with PyTorch and other machine learning libraries (e.g., Scikit-Learn, TensorFlow). • Deep understanding of model optimization pipelines, including PyTorch to ONNX conversions, ONNX Runtime, and scaling attention mechanisms (e.g., Flash Attention). • Experience working with large-scale computing frameworks, data analysis systems, and relational/non-relational databases.

🏖️ Benefits

• Equal Opportunity Employer • Fostering a culture that celebrates unique backgrounds, ideas, and experiences.