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Machine Learning Engineer

INSPYR Solutions · Sunnyvale, CA · Hybrid

Strong hiring record · median 14 days open

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Machine Learning Engineer at INSPYR Solutions. We’ll keep it in your applied jobs, so you can see it later and be warned before applying to the same employer twice.

Machine Learning Engineer

Location

Sunnyvale, CA or Austin, TX (hybrid, in office Tues-Thurs)

ABOUT THIS FEATURED OPPORTUNITY

The Machine Learning Engineer will join the Customer Systems team to design, develop, and optimize production-grade AI solutions, with a focus on Large Language Models (LLMs), agentic AI systems, and inference optimization. This role will be responsible for evaluating model performance, conducting experiments, and implementing optimization techniques to improve the efficiency, scalability, and reliability of open-source LLMs.

THE OPPORTUNITY FOR YOU

  • Design, develop, test, and deploy AI agents and agentic workflows using modern AI frameworks.
  • Evaluate and optimize inference performance of open-source LLMs to improve latency, throughput, and resource utilization.
  • Conduct performance testing, benchmarking, and experimentation to identify opportunities for model optimization.
  • Implement inference optimization techniques, including quantization, to improve model efficiency and scalability.
  • Develop and enhance Retrieval-Augmented Generation (RAG) solutions and integrate them into AI applications.
  • Research and evaluate emerging LLM architectures, inference techniques, and AI frameworks.
  • Collaborate with cross-functional engineering teams to deploy, monitor, and maintain production AI systems.

KEY SUCCESS FACTORS

  • 3 years of experience in AI/ML engineering, with strong hands-on development experience
  • Proven experience designing, developing, and deploying AI agents into production, with knowledge of agentic AI architectures and frameworks
  • Hands-on experience building and implementing RAG-based applications
  • Demonstrated experience deploying and optimizing LLMs in production environments, preferably open-source models.
  • Strong understanding of LLM inference optimization, including quantization, performance benchmarking, and model efficiency techniques
  • Experience conducting technical research, evaluating optimization approaches, and translating findings into production improvements
  • Proficiency in Python for machine learning development, testing, and deployment

NICE TO HAVES

  • Experience with LLM training, fine-tuning, or model adaptation
  • Experience programming in Rust

About INSPYR Solutions

Technology is our focus and quality is our commitment. As a national expert in delivering flexible technology and talent solutions, we strategically align industry and technical expertise with our clients' business objectives and cultural needs. Our solutions are tailored to each client and include a wide variety of professional services, project, and talent solutions. By always striving for excellence and focusing on the human aspect of our business, we work seamlessly with our talent and clients to match the right solutions to the right opportunities. Learn more about us at inspyrsolutions.com.

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