Advanced Machine Learning Ops Engineer (Advanced Materials) (Finance)

Innovate high-purity, high-performance chemicals and materials

At Advanced Materials, we are committed to offering the highest value-add specialty solutions in the advanced materials sector. Our goal is to solve our customers' most complex challenges through a robust and innovative product portfolio and by doing so, deliver exceptional value to our stakeholders. We have identified actionable strategies to grow by expanding into new products and markets and through strategic acquisitions, while keeping our top operating margins.

Joining our team means becoming part of an organization which leverages its long-standing reputation to capture growth trends by investing in innovation and manufacturing enhancements and maintaining deep customer relationships. We foster a collaborative and inclusive work environment that values contributions and supports professional development. With a focus on innovation and sustainability, the team is dedicated to delivering value and making a meaningful impact in advancing our customers' success. Let's make that impact together.

This position is intended to convey to the new, independent company, to be named Solstice Advanced Materials when the separation occurs. This is expected to occur in late 2025 or early 2026.

THE POSITION

We are seeking an experienced Advanced Machine Learning Operations (MLOps) Engineer to join our Advanced Materials team. This role is pivotal in bridging the gap between data science and production, ensuring that our machine learning models are deployed, monitored, and maintained efficiently. The ideal candidate will have a robust understanding of machine learning principles and experience in managing MLOps pipelines in the context of advanced materials, research and development.

KEY RESPONSIBILITIES

• Design, implement, and manage scalable MLOps pipelines for deploying machine learning models related to advanced materials.
• Collaborate with data scientists to operationalize their models, ensuring robustness and efficiency in deployment.
• Set up monitoring tools to evaluate the performance of deployed models, ensuring they meet business and functional requirements.
• Perform model updates and retraining as needed based on incoming data and model performance metrics.
• Work closely with cross-functional teams, including data science, software development, and product management, to align on project goals and timelines.
• Document MLOps processes, methodologies, and best practices to facilitate knowledge sharing within the organization.
• Design and maintain the infrastructure required for model development, training, and deployment, ensuring high availability and security.
• Optimize cloud resources to manage compute costs effectively.
• Stay abreast of developments in machine learning and materials science to identify opportunities for innovative applications of machine learning.
• Engage in the continuous improvement of MLOps practices and tools within the team.

If required Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. Person, which is defined as, a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status or have the ability to obtain an export authorization.

The annual base salary range for this position is $132,000 to 198,000.

Please note that this salary information serves as a general guideline. Honeywell considers various factors when extending an offer, including but not limited to the scope and responsibilities of the position, the candidate's work experience, education and training, key skills, as well as market and business considerations.

BENEFITS OF WORKING FOR HONEYWELL
In addition to a performance-driven salary, cutting-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell employees are eligible for a comprehensive benefits package. This package includes 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), and 12 Paid Holidays. For more information visit: https://benefits.honeywell.com .

The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates.Come join the Advanced Materials Technology team at Honeywell! Honeywell has an exciting opportunity for a Advanced Machine Learning Ops Engineer.YOU MUST HAVE

• Bachelors degree in Computer Science, Data Science, Materials Science, Engineering, or a related field. A Master's or Ph.D. is a plus.
• Minimum of 3-5 years of experience in machine learning, or MLOps roles.
• Experience with deploying machines, learning models into production environments and managing their lifecycle.
• Deep understanding of machine learning frameworks (e.g., TensorFlow, PyTorch) and tools (e.g., Docker, Kubernetes).
• Experience with cloud services (e.g., AWS, Azure, GCP) and data storage technologies (e.g., SQL, NoSQL).

WE VALUE

• Deep knowledge of advanced materials, including polymer science, nanomaterials, ceramics, metals, or composites.
• Familiarity with experimental methods in materials characterization and testing.
• Excellent problem-solving abilities and critical thinking skills.
• Strong interpersonal and communication skills, capable of engaging with technical and non-technical audiences.
• Ability to work independently and manage multiple projects simultaneously in a fast-paced environment.
• Passion for innovation and continuous learning within the field of data science and materials science.

ABOUT HONEYWELL
Honeywell International Inc. (Nasdaq: HON) invents and commercializes technologies that address some of the world's most critical demands around energy, safety, security, air travel, productivity, and global urbanization. We are a leading software-industrial company dedicated 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. Learn more about Honeywell: https://www.honeywell.com/us/en.

THE BUSINESS UNIT
Honeywell Advanced Materials is an industry-leading solutions provider, playing a crucial role in advancing industries worldwide through diverse applications, revolutionary inventions, and pioneering technologies focused on high-growth mega-trends. Our science and technology experts create solutions that help solve our customers' needs today and in the future. Our solutions span across industries, including retail, healthcare and pharma, buildings, manufacturing, and hi-tech. In each of these verticals, we bring deep materials and engineering knowledge, which leads to our customers achieving a reduction in energy consumption, cutting down their carbon emissions, and improving their operational efficiencies.

Honeywell is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, care or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status. Learn more about inclusion and diversity: https://www.honeywell.com/us/en/company/inclusion-and-diversity.KEY RESPONSIBILITIES

• Design, implement, and manage scalable MLOps pipelines for deploying machine learning models related to advanced materials.
• Collaborate with data scientists to operationalize their models, ensuring robustness and efficiency in deployment.
• Set up monitoring tools to evaluate the performance of deployed models, ensuring they meet business and functional requirements.
• Perform model updates and retraining as needed based on incoming data and model performance metrics.
• Work closely with cross-functional teams, including data science, software development, and product management, to align on project goals and timelines.
• Document MLOps processes, methodologies, and best practices to facilitate knowledge sharing within the organization.
• Design and maintain the infrastructure required for model development, training, and deployment, ensuring high availability and security.
• Optimize cloud resources to manage compute costs effectively.
• Stay abreast of developments in machine learning and materials science to identify opportunities for innovative applications of machine learning.
• Engage in the continuous improvement of MLOps practices and tools within the team.

If required Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. Person, which is defined as, a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status or have the ability to obtain an export authorization.

The annual base salary range for this position is $132,000 to 198,000.

Please note that this salary information serves as a general guideline. Honeywell considers various factors when extending an offer, including but not limited to the scope and responsibilities of the position, the candidate's work experience, education and training, key skills, as well as market and business considerations.

BENEFITS OF WORKING FOR HONEYWELL
In addition to a performance-driven salary, cutting-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell employees are eligible for a comprehensive benefits package. This package includes 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), and 12 Paid Holidays. For more information visit: https://benefits.honeywell.com.

The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates.About Us

Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments - powered by our Honeywell Forge software - that help make the world smarter, safer and more sustainable.