AI Engineer Manager
Remote
Information
Key Responsibilities:
Spearhead the design, development and deployment of Generative AI solutions tailored for Honeywell business requirements.
Provide technical leadership, mentorship and coaching to Data Scientists and AI/ML engineers. Develop top talents to build an effective and high performing team. Direct and support the team members to complete all the project deliverables.
Work closely with cross-functional teams to align AI initiatives, ensuring smooth integration of LLM solutions with existing enterprise systems.
Engage with senior leadership, providing regular updates on project milestones, risks, and achievements.
Identify business requirements and opportunities for Generative AI use cases and work with key stakeholders to create new project / business case.
Define best practices and consistent framework for deployment of Generative AI applications, implementing robust LLMOps process and reinforcing Responsible AI principles.
Drive operational excellence activities required to ensure a streamlined production process of data science deliveries.
Actively lead, analyze, and recommend highly complex business opportunities, through assessments/workshops, detailed data analysis/modeling and overall end-end solutioning to propose predictive, AI Driven solutions that drive the most business value with sustained impact.
Stay updated with advancements in AI, specifically Generative AI technologies, and identify potential applications in the enterprise space.
Continuously optimize the existing AI/ML operations and help build effective model performance monitoring, alert, and improvement framework to proactively identify problems/issues before business impact.
Partner and effectively communicate with Non-IT / Business users, functional counterparts, and stakeholders to understand the underlying business problem, and work with the extended team to define and communicate the right technical solution.
Company
Honeywell
Requirements
YOU MUST HAVE
Bachelors in Computer Science, Data Science or Engineering fields
6+ years of IT experience in solution architect / data scientist / software development for large corporate/organizations
4+ years of experience in building and deploying Machine Learning solutions using various supervised/unsupervised ML algorithms such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Random Forest, etc
4+ years of hands-on experience with Python and/or R programming and statistical packages, and ML libraries such as scikit-learn, Keras, TensorFlow, PyTorch, MXNet, etc, and/or natural language processing using NLTK, spaCy, Gensim, etc.
2+ years of experience in building IT use cases / solutions especially around AI/ML cognitive services, based on Cloud infrastructure and services such as Azure and/or AWS cloud platforms.
Excellent understanding of Machine Learning techniques and proficiency in feature analysis, algorithm selection and model hyperparameter tuning.
Demonstrated experience in people skills and project management.