Innovate to solve the world’s most important challenges
Senior Advanced AI Engineer
We have an opportunity for a
Senior Advanced AI Engineer
to join us at Honeywell, in Dublin, where you will be a driving force in designing, developing, and deploying end-to-end AI/ML solutions aimed at bringing autonomous capabilities to Honeywell products over the next decade. You will operate as a hands-on technical leader, working on everything from data pipelines to model optimization and drift detection, while mentoring junior team members to build a truly full-stack AI/ML practice.
This is a hybrid role, 3 days at the office + 2 days work from home model, with the opportunity to travel to India and US if required.
Honeywell
We have been innovating for more than 100 years and now we’re creating what’s next. Our programs serve a global community and our hometowns too. We provide resources and financial support to causes around the world and encourage employee volunteerism. We are committed to the highest standard in everything we do!

Key Responsibilities

• Design and implement high-impact AI/ML models and workflows, ensuring scalability and reliability on cloud platforms such as Databricks, VertexAI, etc.
• Collaborate with cross-functional teams (Data Engineering, ML Engineering, DevOps) to create holistic MLOps pipelines, leveraging frameworks such as MLflow and Kubeflow.
• Conduct thorough reviews of ML models for performance, bias, and drift, proposing corrective actions.
• Integrate AI (including TimeSeries, Computer Vision, NLP, GenAI/RAG/Agentic AI) solutions into existing Honeywell products, maintaining rigorous code quality standards.
• Mentor junior engineers, promoting best practices in model development and deployment.

Key Skills and Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI, or a related technical field, with knowledge of Agile or similar software development methodologies; strong Python skills complemented by exposure to additional programming languages like Scala or Java.
• Full-stack AI/ML experience encompassing all stages from data ingestion through model deployment and maintenance, supported by strong hands-on experience in developing and deploying ML models in production.
• Strong analytical mindset focused on skeptical, data-driven decision-making, with a proven track record in advanced machine learning frameworks such as TensorFlow and PyTorch.
• Familiarity with cloud platforms like AWS, Azure, or GCP for large-scale training and deployment of models, alongside demonstrated expertise in MLOps tools and best practices, including CI/CD, containerization, and orchestration.
• Ability to effectively communicate technical concepts to both technical experts and laypersons, facilitating collaboration across diverse teams.

Our Offer

• A culture that fosters inclusion, diversity, and innovation in an international work environment
• Market specific training and ongoing personal development.
• Experienced leaders to support your professional development

We are an equal opportunity employer and value diversity at our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Join us now and be part of a global team of thinkers, innovators, dreamers, and doers who make the things that make the future!

TheFutureIsWhatWeMakeIt

LI-Hybrid

Additional Information

• Design and implement high-impact AI/ML models and workflows, ensuring scalability and reliability on cloud platforms such as Databricks, VertexAI, etc.
• Collaborate with cross-functional teams (Data Engineering, ML Engineering, DevOps) to create holistic MLOps pipelines, leveraging frameworks such as MLflow and Kubeflow.
• Conduct thorough reviews of ML models for performance, bias, and drift, proposing corrective actions.
• Integrate AI (including TimeSeries, Computer Vision, NLP, GenAI/RAG/Agentic AI) solutions into existing Honeywell products, maintaining rigorous code quality standards.
• Mentor junior engineers, promoting best practices in model development and deployment