Senior ML Engineer

Key Skills

Apache, Azure, Cloud computing, Big Data Technology, Machine learning techniques, Data science techniques, Data Mining, Deep Learning, Natural Language Processing (NLP), Docker, Kubernetes-K8s, Continuous Integration & Continuous Delivery - CI/CD, Databricks, MLOps tools

Job Description

Join the industry leader to design the next generation of breakthroughs

Honeywell is charging into the Industrial IoT revolution with the establishment of Honeywell Connected Enterprise (HCE), building on our heritage of invention and deep, on-the-ground industry expertise. HCE is the leading industrial disruptor, building and connecting software solutions to streamline and centralize the assets, people and processes that help our customers make smarter, more accurate business decisions. Moving at the speed of software, we are creating, innovating and delivering solutions fast, challenging the way things have always been done, piloting new ways for all of us to work, and expecting our successes to set new standards for our customers and for Honeywell.

Key Responsibilities:

• Understand Honeywell’s business priorities and success measures to design implementation architectures and solutions.
• Apply technical knowledge to architect solutions that meet Honeywell’s business needs, create Data Science Solutions, roadmaps, and ensure long term technical viability of new deployments, infusing key analytics and AI technologies where appropriate (e.g., Azure ML, ML Ops, Cognitive Services, Big Data, Data Lake, Azure Databricks, etc.)
• Ensure that solution exhibits high levels of performance, security, scalability, maintainability, appropriate reusability, and reliability upon deployment.
• Closely work with technical teams and identify technical blockers (e.g., changing configurations, sample coding, POC development) for selected products to accelerate architecture implementations.
• Maintain technical skills and knowledge, keeping up to date with market trends and competitive insights on the area of Data Science, Big Data & Cloud technologies.

Key Technical Skills:

• Machine Learning, Deep Learning, Data Mining techniques, NLP, Transfer learning and other advanced Data Science concepts
• CICD pipeline development, Cloud deployments, Kubernetes, Docker, Cloud Security and private/public hybrid Cloud concepts
• Microservices development, Big Data and Analytics (i.e. Apache/Databricks Spark)
• MLOps, Software Engineering concepts, Solution Architecture Design, and Development.

You Must Have:

• 8+ years technical solutions experience combination of Machine Learning, Big Data/Analytics, and cloud concepts
• 5 years of experience in designing, building Data Science applications using big data and cloud services
• 3 years Automated deployment of Machine learning modes in cloud environment.
• Master’s from an accredited college or university

We Value:

• Experience working with Global teams
• AWS Cloud Certifications; Azure Certifications
• Experience with Streaming Analytics
• Experience working with remote and global teams
• Results driven with a positive can-do attitude
• Business functional process and data experience including SAP, SFDC data sets and processes