20 hours ago
Responsibilities
- Provide technical guidance and support to a team of AI engineers.
- Design, develop, and implement scalable AI and machine learning solutions.
- Collaborate with Data Science and Data Engineering teams on machine learning system challenges at scale.
- Build distributed training systems and scalable machine learning pipelines for training and deployment in IT/OT products.
- Optimize hyperparameter tuning, training and inference latency, distributed execution, and system-level bottlenecks.
- Research, implement, fine-tune, and serve state-of-the-art large language models for business use cases.
- Build agentic AI applications and deep learning models optimized for CPUs and GPUs.
- Maintain model performance, uptime, scalability, code quality, design quality, and monitoring.
- Optimize integrations between machine learning libraries and cloud machine learning and data processing frameworks.
- Lead junior engineers in a product development setting.
Requirements
- Bachelor’s degree from an accredited institution in a technical discipline such as science, technology, engineering, or mathematics.
- At least 6 years of industry experience writing production-level, scalable code, such as Python.
- At least 5 years of experience with machine learning topics including classification, clustering, optimization, recommendation systems, or deep learning.
- At least 5 years of industry experience with distributed computing frameworks such as Spark or the Kubernetes ecosystem.
- At least 5 years of industry experience with machine learning frameworks and libraries including Spark MLlib, Keras, TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn, spaCy, or Gensim.
- At least 5 years of industry experience with major cloud computing services such as Azure or GCP.
- At least 1 year of experience building and scaling generative AI applications using frameworks or services such as LangChain, PGVector, Pinecone, Azure ML, or Vertex AI.
- Experience building agentic AI applications.
- At least 2 years of technical leadership experience leading junior engineers in a product development setting.
- Preferred qualifications include an MS or PhD in Computer Science, Software Engineering, Electrical Engineering, or a related field; proficient Python/PySpark, containerization, Azure ML or Vertex AI deployment, CI/CD, external technical communication, downstream modeler enablement, and data product development.
Benefits
- Employer-subsidized medical, dental, vision, and life insurance.
- Short-term and long-term disability coverage.
- 401(k) match, flexible spending accounts, health savings accounts, and an employee assistance program.
- Educational assistance, parental leave, paid time off, and 12 paid holidays.
- Hybrid work schedule in Atlanta, Georgia; new hires must work 100% onsite Monday through Friday for the first 90 days.
- The application period is estimated at 40 days from the job posting date and may change based on business needs and candidate availability.
Tech Stack
Apache SparkAzureGoogle Cloud PlatformHugging Face TransformersKerasKubernetesPythonPyTorchscikit-learnspaCyTensorFlow
Categories
About Honeywell
Honeywell is a public industrial technology company that sells aerospace systems, industrial automation, warehouse and building management technologies, and safety and security products to commercial, industrial, and government customers. Its portfolio spans avionics and propulsion, process controls and SCADA, warehouse automation, and IoT software such as Honeywell Forge. The company is headquartered in Charlotte, North Carolina and serves global markets across aviation, energy, logistics, and critical infrastructure.