Senior Applied Machine Learning Engineer

Hewlett Packard Enterprise•Fort Collins, CO

1d•$137,000 - $315,000•Hybrid

About The Position

We are seeking an experienced Senior Applied Machine Learning Engineer with a proven track record of deploying, integrating, and leveraging machine learning and AI solutions in real-world, customer-facing environments. The ideal candidate has worked either directly with clients as part of an AI/ML solutions team or as an end-user of AI/ML products to solve practical business challenges. In this role, you will apply your hands-on experience with machine learning and AI technologies to build, optimize, and integrate solutions that address customer needs and improve product performance. You will translate complex data and AI/ML models into accessible, scalable solutions, working closely with cross-functional teams to ensure successful deployment and adoption.

Requirements

PhD with at least 2 years of relevant industry experience, or the equivalent (e.g., Master’s degree with 4+ years, Bachelor's with 6+ years).
Extensive hands-on experience applying machine learning and AI solutions in customer-facing or end-user environments.
Proven ability to deploy models in production, ensuring reliability and performance.
Experience with open-source ML/AI tools and frameworks.
Experience with backend programming languages (Python, Go).
Proficiency in developing, using, and maintaining AI agents; proven experience coding agents for automation or decision-making tasks.
Excellent written and verbal communication skills, especially in asynchronous collaboration.

Nice To Haves

Experience with AI agents and automation.
Knowledge of inference deployment and optimization techniques.
Familiarity with large-scale data pipelines.
Experience with retrieval-augmented systems (e.g., RAG).

Responsibilities

Design, develop, and deploy machine learning models and AI solutions that address real-world customer problems, focusing on usability, scalability, and performance.
Rapidly develop demos, POCs, MVPs, and workflows to showcase new AI/ML capabilities that could be integrated into the product or used to improve existing features based on customer feedback or market research. Work in a fast-paced environment to experiment with emerging techniques and tools, ensuring the creation of tangible, functional prototypes that demonstrate practical AI/ML solutions for real-world problems.
Develop and improve integrations of open-source ML/AI tools (e.g., MLFlow, Spark, LangChain, Kubeflow) within production environments, ensuring seamless operation on platforms like Kubernetes.
Fine-tune models and algorithms for accuracy, efficiency, and scalability in production settings, including deep learning technologies.
Translate customer requirements and industry trends into actionable AI/ML solutions that improve product features, data management, and system performance.
Work closely with product managers, data scientists, and engineering teams to brainstorm, design, and deploy AI/ML solutions, documenting procedures and best practices.
Lead efforts in integrating emerging AI tools, mentor junior team members, and communicate progress and challenges to leadership.