Company description
Honeywell International Inc. stands as a premier global technology and manufacturing pioneer, leading transformation across critical infrastructure and industrial landscapes worldwide.
The organization specializes in designing, engineering, and delivering highly advanced technological solutions that address some of the most intricate global operational challenges.
Operational domains encompass four major business segments: Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation.
Core solutions are heavily augmented by Honeywell Forge, an enterprise performance management software platform that integrates advanced artificial intelligence, predictive analytics, and Internet of Things (IoT) connectivity.
Honeywell enables diverse industries—including aviation, manufacturing, commercial real estate, energy distribution, and logistics—to operate with significantly heightened intelligence, safety, and energy efficiency.
The company operates across dozens of countries, providing a collaborative environment where cutting-edge software and physical engineering merge to shape next-generation industrial systems.
Honeywell maintains a resolute commitment to fostering workplace diversity, equity, continuous professional development, and sustainable technological progress on a global scale.
Employees at Honeywell engage in meaningful projects that influence critical global infrastructure, transforming traditional industrial practices into automated, digitized, and resilient ecosystem solutions.
Profile overview
The AI Engr I position represents a foundational engineering role designed for talented technical professionals looking to build advanced software and intelligence solutions within a world-class industrial enterprise.
In this capacity, the primary focus centers around assisting in the end-to-end design, architecting, training, evaluation, and optimization of production-grade artificial intelligence algorithms and statistical models.
You will work alongside highly experienced AI researchers, data scientists, and senior software engineers to solve complex enterprise problems through data-driven methodologies.
Key responsibilities involve gathering, cleaning, and preprocessing multi-modal industrial datasets to extract actionable insights and ensure high-quality input for deep learning frameworks.
The role demands active participation in integrating newly developed machine learning models into live deployment pipelines, enterprise software applications, and edge compute platforms.
Engineers in this position contribute actively to continuous integration and continuous deployment (CI/CD) practices customized specifically for machine learning operations (MLOps).
You will assist in running iterative tests, benchmarking model execution latency, analyzing accuracy metrics, and continuously tuning hyperparameters to maintain peak model reliability.
Beyond model creation, the post emphasizes cross-functional synergy, requiring regular communication with software developers, product managers, domain engineers, and business stakeholders.
The position requires maintaining strict alignment with industry best practices regarding code maintainability, system architecture, data privacy, and ethical artificial intelligence standards.
The environment encourages proactive learning, giving entry-level engineers access to cutting-edge research, internal technical mentorship, and practical application scenarios across diverse industrial verticals.
Candidates are expected to thrive in structured, fast-paced workflows where creative problem-solving and systematic analytical skills directly influence real-world industrial software performance.
This opportunity serves as a gateway for developing deep expertise in artificial intelligence, software design, and scalable enterprise computing within a dynamic global organization.
Qualifications
Completion of a Bachelor’s degree from an accredited university or higher education institution in a core technical discipline, such as Computer Science, Data Science, Artificial Intelligence, Mathematics, Software Engineering, or related technical fields.
Hands-on practical exposure to artificial intelligence technology initiatives, academic projects, research work, internships, or practical workplace applications.
Solid baseline knowledge and core practical expertise in building, evaluating, and troubleshooting fundamental machine learning techniques and deep learning neural network architectures.
High proficiency in foundational programming languages widely utilized in data science environments, with strong hands-on coding ability in Python.
Direct working knowledge or project-based experience with modern machine learning frameworks and numerical libraries such as TensorFlow, PyTorch, NumPy, Pandas, and Scikit-Learn.
Strong familiarity with foundational scientific concepts including advanced linear algebra, calculus, probability theory, statistical inference, and mathematical optimization techniques.
Demonstrated competency in data preprocessing, feature engineering, missing value imputation, exploratory data analysis, and dimensional reduction approaches.
Advanced degrees such as a Master’s degree or Ph.D. specializing in Computer Science, Machine Learning, Artificial Intelligence, or Quantitative Data Analytics are highly valued.
Prior experience working within an Agile, Scrum, or Kanban software development framework utilizing standard collaboration, version control, and task-tracking tools like Git, GitHub, GitLab, or Jira.
Exposure to cloud platform environments such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) for hosting machine learning workloads.
Familiarity with computer vision frameworks, natural language processing (NLP) pipelines, or time-series forecasting frameworks is considered a beneficial asset.
Excellent technical problem-solving capabilities, paired with systematic debugging skills and acute attention to operational and logical details.
Strong verbal and written communication skills necessary for articulating technical concepts, workflow diagrams, and model evaluation metrics clearly to team members.
Ability to prioritize tasks effectively, work autonomously when required, and adapt rapidly in a dynamic, high-growth technical ecosystem.
Additional info
The selected candidate will operate directly out of Honeywell’s state-of-the-art facility located at RMZ Ecoworld, Varturhobli, Bengaluru, Karnataka, India.
Position alignment requires physical on-site presence, offering rich opportunity for direct collaboration, in-person whiteboarding, and seamless team coordination.
This posting reflects full-time employment status, providing comprehensive job stability, comprehensive enterprise benefits, and continuous learning opportunities.
Honeywell fosters an inclusive workplace culture that actively recruits, supports, and develops a globally diverse workforce.
Equal opportunity employment policies ensure that all qualified applicants receive thorough consideration without regard to non-job-related attributes or backgrounds.
The role offers significant exposure to senior technological leaders, internal technical workshops, and global engineering networks across Honeywell Forge ecosystems.
Professional development paths are clearly mapped, helping entry-level engineers systematically transition toward senior technical specialist or technical leadership trajectories over time.
The requisition identification number for this specific talent acquisition posting is 154187, filed under the core Engineering job category.
Applicants are provided structured onboarding programs designed to accelerate technical integration, platform familiarization, and security compliance training.
Employees benefit from a collaborative corporate environment equipped with modern infrastructure, compute resources, hardware acceleration tools, and cloud environments necessary for modern AI development.
The position operates within a performance-oriented ecosystem where innovative thinking, project ownership, and technological curiosity are systematically recognized and nurtured.
Joining Honeywell in this role connects engineers to a global network of innovators who are actively redefining industrial automation, sustainable technology, and computational intelligence for the future.
Please click here to apply.
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