Machine Learning Engineer II

Honeywell International • Atlanta, GA

156d

About The Position

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.

Requirements

• MS or Ph.D. in Computer Science, Software Engineering, Electrical Engineering, or related fields.
• 3+ years of industry experience with Python in a programming intensive role.
• 2+ years of experience with one or more of the following machine learning topics: classification, clustering, optimization, recommendation system, graph mining, deep learning.
• 3+ years of industry experience with distributed computing frameworks such as Spark, Kubernetes ecosystem, etc.
• 3+ years of industry experience with popular ml frameworks such as Spark MLlib, Keras, Tensorflow, PyTorch, HuggingFace Transformers and libraries (like scikit-learn, spacy, gensim, CoreNLP etc.).
• 3+ years of industry experience with major cloud computing services.
• Background or experience in building and scaling Generative AI Applications, specifically around frameworks like Langchain, PGVector, Pinecone, AzureML.
• Experience with Prompt Engineering in Agent orchestration framework.
• An effective communicator - you shall be an ambassador of Honeywell's Machine Learning engineering at external forums and have the ability to explain technical concepts to a non-technical audience.

Nice To Haves

• Proficient Python/PySpark coding experience.
• Proficient in containerization services.
• Proficient in Azure ML to deploy the models.
• Experience with working in CICD framework.
• Motivation to make downstream modelers' work smoother.

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.
• Help to build a strong, diverse team by recruiting talent, identifying, and developing successors, driving retention and engagement, and fostering an inclusive culture.

Benefits

• Employer subsidized Medical, Dental, Vision, and Life Insurance.
• Short-Term and Long-Term Disability.
• 401(k) match.
• Flexible Spending Accounts.
• Health Savings Accounts.
• EAP and Educational Assistance.
• Parental Leave.
• Paid Time Off (for vacation, personal business, sick time, and parental leave).
• 12 Paid Holidays.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Machinery Manufacturing
• Education Level: Master's degree