We are looking for a highly motivated, energetic, inquisitive young minds to be a part of HON Autonomous Buildings team, developing cutting edge technologies in AI ML and Gen AI based solutions for Smart Communities domain involving multi-functional data ranging from HVAC systems, Fire, security, irrigation etc. Your abilities should also include ability to design effective dashboards and show the live data analytics, alarms and analysis as needed. We want your hands-on experience and skills in development and completion of complex AL ML solutions in this domain.

• B Tech with 3 plus years experience in AI ML Projects, with specialization in AI/ML, Pattern Recognition etc.
• M Tech with 1-2 years experience in the above mentioned areas.

Your role will include

• Understanding the problem statement and allocated work
• Hands-on skills on Traditional AI / ML techniques, multi-parameter pattern recognition, Deep Learning AI Model Inferencing and Transformer based AI Model based solutions.
• LLM, SLM and other Transformer Architecture based solutions
• Multi-Agent Solutions, with understanding and implementation of Agent AI Framework
• Data Engineering and ETL Pipeline implementation

Technical Skills include but not limited to:

• Extensive experience with Py Torch and Tensor Flow to design and optimize complex neural architectures like CNNs, RNNs, and Transformers, Mastery of Python and SQL; proficiency in R, Scala, or C++ for high-performance applications.
• Frameworks: Deep expertise in Py Torch, Tensor Flow, Keras, and Hugging Face.
• Cloud & Infrastructure: Hands-on experience with AWS (Sage Maker, Athena), Azure, or GCP (Vertex AI).
• Big Data: Proficiency with Spark, Databricks, Airflow, and Kafka for large-scale data pipelines.
• Tooling: Experience with experiment tracking (WandB, MLflow) and containerization (Docker, Kubernetes).
• Data Engineering, ETL, setting up AI / ML pipeline
• Agentic AI Frameworks, Proficiency in Lang Graph, CrewAI, Microsoft Auto Gen, and Llama Index Workflows and Tools usage, orchestration of autonomous systems, Multi-Agent Systems.
• Multi-Modal AI Models, Language Models and Traditional and Deep Learning AI model training and fine tuning
• Safety, Ethics & "Agent Ops"