Lead AI Engr

Honeywell Honeywell · Industrial · Bengaluru, Karnataka, India

Lead AI Engineer at Honeywell focused on driving Generative AI strategy and roadmap for Value Engineering and Component Engineering COE. Responsibilities include market research, vendor partnerships, incubating new technologies, collaborating with IT and business teams, implementing and optimizing AI/ML models in production, developing APIs/microservices, and coaching data scientists. Requires strong experience in AI/ML, LLMs, fine-tuning, MLOps, cloud platforms (GCP), and data skills.

What you'd actually do

  1. Drive VE/CE COE Gen AI strategy. Establish current and future state landscape & roadmap
  2. Provide Subject Matter Expertise on Generative AI adoption and Impactful deployment for VE/CE
  3. Collaborate with IT, Technical teams, Business SMEs for defining architectural framework, common standards and solutions for VE/CE
  4. Work closely with data scientists to implement and optimize AI/ML models in production environments.
  5. Perform Market Research to identify new opportunities, ideas and technology trends for adoption.

Skills

Required

  • Python
  • R
  • SQL
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • LLM models like Gemini, Llama, GPT, DALL-E
  • LangChain
  • Vector databases like Faiss, Pinecone
  • fine-tuning LLM using LoRA/QLoRA techniques
  • Develop APIs and microservices
  • data integration
  • ETL processes
  • SQL/NoSQL databases
  • Big Data technologies (Hadoop, Spark)
  • data warehousing solutions
  • GCP
  • MLOps practices
  • analyse complex data sets
  • derive insights
  • solve sophisticated problems
  • communication and presentation skills
  • explain complex AI/ML concepts
  • Business Process
  • IT Industry Standards
  • Stay up-to-date with the latest developments in Gen AI/ML and cloud technologies.

Nice to have

  • master's degree or PhD in computer science, statistics, engineering, mathematics, or related fields.

What the JD emphasized

  • 5+ years of experience in leading and managing AI/ML teams and projects
  • demonstrated success in delivering impactful and actionable insights
  • track record of innovation and leadership in productizing AI research

Other signals

  • Drive Gen AI strategy & roadmap
  • Implement and optimize AI/ML models in production
  • Develop APIs and microservices to support Gen AI/ML applications
  • Scaling AI/ML projects using MLOps practices