Sr. Advanced AI Software Engineer - Honeywell
Overview
As a Sr. Advanced AI Software Engineer, you will own the development and deployment of AI/ML systems at scale for Honeywell's industrial software products, used in critical sectors. You will architect and ship production-grade solutions using LLMs, generative AI, and RAG pipelines, while driving MLOps and CI/CD workflows. Reporting to the Director of Engineering, you will work from Phoenix with a hybrid schedule, collaborating with product and platform teams to deliver measurable business outcomes. This role stands out for its focus on leading AI strategy and mentoring engineers, with a direct impact on high-growth industrial markets.
What You'll Do8
- 1Design and deploy advanced AI/ML systems, including LLMs and generative AI, end to end for production environments.
- 2Architect scalable, reliable, and cost-efficient AI solutions using Docker and Kubernetes to handle high-throughput workloads.
- 3Lead model optimization and evaluation, implementing monitoring to ensure performance and reliability.
- 4Drive MLOps practices for training, deployment, and lifecycle management with CI/CD pipelines.
- 5Collaborate with product, data, and platform teams to align AI outcomes with business goals.
- 6Provide technical leadership through design reviews and mentorship, influencing AI strategy.
- 7Implement RAG pipelines and semantic search using embeddings and vector databases to enhance model retrieval.
- 8Optimize model inference for latency and throughput, ensuring cost-effective deployment.
Requirements9
- 15+ years of hands-on AI/ML experience in production environments, building and deploying AI-powered systems at scale.
- 2Deep expertise in machine learning fundamentals, including supervised, unsupervised, and reinforcement learning.
- 3Proficiency with deep learning architectures such as CNNs, RNNs, and Transformers.
- 4Hands-on experience with LLMs, generative AI, prompt engineering, fine-tuning, and RAG pipelines.
- 5Strong programming skills in Python (primary), with experience in at least one additional language like Java or C++.
- 6Solid understanding of data structures, algorithms, and distributed systems, plus API design and microservices.
- 7Experience with cloud platforms including Azure or AWS, and containerization using Docker and Kubernetes.
- 8Familiarity with CI/CD tools for ML workflows and MLOps practices.
- 9Knowledge of SQL and NoSQL databases, plus vector databases.
Salary Insight
Salary not disclosed in listing
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