Lead Machine Learning Engineer
Honeywell
Join a team recognized for leadership, innovation and diversity
ABOUT HONEYWELL
Honeywell International Inc. (Nasdaq: HON) invents and commercializes technologies that address some of the world's most critical challenges around energy, safety, security, air travel, productivity, and global urbanization. We are a leading software-industrial company committed to introducing state-of-the-art technology solutions to improve efficiency, productivity, sustainability, and safety in high-growth businesses in broad-based, attractive industrial end markets. Our products and solutions enable a safer, more comfortable, and more productive world, enhancing the quality of life of people around the globe.
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 impalement 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.
YOU MUST HAVE
• MS or Ph.D. in Computer Science, Software Engineering, Electrical Engineering, or related fields.
• 7+ years of industry experience in writing production level, scalable code (e.g. in Python)
• 5+ years of experience with one or more of the following machine learning topics: classification, clustering, optimization, recommendation system, deep learning.
• 5+ years of industry experience with distributed computing frameworks such as Spark, Kubernetes ecosystem, etc.
• 5+ years of industry experience with popular ml frameworks such as Spark MLlib, Keras, Tensorflow, PyTorch, HuggingFace Transformers and libraries (like scikit-learn, spacy, genism etc.).
• 5+ years of industry experience with major cloud computing services like Azure or GCP
• 1+ years of experience in building and scaling Generative AI Applications, specifically around frameworks like Langchain, PGVector, Pinecone, AzureML, VertexAI
• Experience in building Agentic AI applications.
• Prior experience in building data products and established a track record of innovation would be a big plus.
• An effective communicator - you shall be an ambassador of Honeywell's Machine Learning engineering at external forums and can explain technical concepts to a non-technical audience.
• 2+ years of technical leadership leading junior engineers in a product development setting
Preferred:
• Proficient Python/PySpark coding experience
• Proficient in containerization services
• Proficient in Azure ML or VertexAI to deploy the models
• Experience with working in CICD framework
• Motivation to make downstream modelers' work smoother
Honeywell is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status.
Additional Information
Global (ALL)
Honeywell is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status.
ABOUT HONEYWELL
Honeywell International Inc. (Nasdaq: HON) invents and commercializes technologies that address some of the world's most critical challenges around energy, safety, security, air travel, productivity, and global urbanization. We are a leading software-industrial company committed to introducing state-of-the-art technology solutions to improve efficiency, productivity, sustainability, and safety in high-growth businesses in broad-based, attractive industrial end markets. Our products and solutions enable a safer, more comfortable, and more productive world, enhancing the quality of life of people around the globe.
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 impalement 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.
YOU MUST HAVE
• MS or Ph.D. in Computer Science, Software Engineering, Electrical Engineering, or related fields.
• 7+ years of industry experience in writing production level, scalable code (e.g. in Python)
• 5+ years of experience with one or more of the following machine learning topics: classification, clustering, optimization, recommendation system, deep learning.
• 5+ years of industry experience with distributed computing frameworks such as Spark, Kubernetes ecosystem, etc.
• 5+ years of industry experience with popular ml frameworks such as Spark MLlib, Keras, Tensorflow, PyTorch, HuggingFace Transformers and libraries (like scikit-learn, spacy, genism etc.).
• 5+ years of industry experience with major cloud computing services like Azure or GCP
• 1+ years of experience in building and scaling Generative AI Applications, specifically around frameworks like Langchain, PGVector, Pinecone, AzureML, VertexAI
• Experience in building Agentic AI applications.
• Prior experience in building data products and established a track record of innovation would be a big plus.
• An effective communicator - you shall be an ambassador of Honeywell's Machine Learning engineering at external forums and can explain technical concepts to a non-technical audience.
• 2+ years of technical leadership leading junior engineers in a product development setting
Preferred:
• Proficient Python/PySpark coding experience
• Proficient in containerization services
• Proficient in Azure ML or VertexAI to deploy the models
• Experience with working in CICD framework
• Motivation to make downstream modelers' work smoother
Honeywell is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status.
Additional Information
- JOB ID: req489297
- Category: Engineering
- Location: 715 Peachtree Street, N.E.,Atlanta,Georgia,30308,United States
- Exempt
Global (ALL)
Honeywell is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status.
JOB SUMMARY
Lead Machine Learning Engineer
Honeywell
Atlanta
2 days ago
N/A
Full-time
Lead Machine Learning Engineer