What are the responsibilities and job description for the Machine Learning Engineer II position at Honeywell?
Responsibilities:
- Collaborate with colleagues across multiple teams (Data Science and Data Engineering) on unique machine learning system challenges at scale.
- Leverage distributed training systems to build scalable machine learning pipelines for model training and deployments in IT/OT Products space.
- Design and implement solutions to optimize distributed training execution in terms of model hyperparameter optimization, model training/inference latency and system-level bottlenecks.
- Research and implement state of the art LLM models for different business use cases including finetuning and serving the LLMs.
- Ensure ML Model performance, uptime, and scale, maintaining high standards of code quality and thoughtful design quality and monitoring.
- Optimize integration between popular machine learning libraries and cloud ML and data processing frameworks.
- Build Deep Learning models and algorithms with optimal parallelism and performance on CPUs/ GPUs.
As an AI Engr II here at Honeywell, you will be responsible for developing and implementing AI algorithms, models, and systems to solve complex business problems. You will collaborate with cross-functional teams to integrate AI solutions into existing systems and processes, ensuring scalability, efficiency, and robustness.
In this role, you will impact the development and deployment of advanced AI solutions, contributing to Honeywell's commitment to innovation and cutting-edge technology. This position will play a key role in driving technical excellence within the organization and shaping the future of AI technology at Honeywell.
At Honeywell, our people leaders play a critical role in developing and supporting our employees to help them perform at their best and drive change across the company. Help to build a strong, diverse team by recruiting talent, identifying, and developing successors, driving retention and engagement, and fostering an inclusive culture.