Description

You will lead the development of AI solutions integrating Large Language Models (LLMs) and traditional Deep Learning for industrial use cases.

Responsibilities

• Process and analyze high-volume industrial data (vibration, acoustics, IoT streams) using signal processing and feature engineering.
• Develop hybrid AI architectures combining LLMs with classical deep learning for multimodal industrial applications.
• Mentor junior team members and establish MLOps best practices for model scalability and deployment.
• Lead proof-of-concept projects to validate new AI approaches for real-time data processing.

Required Skills

• 15+ years of industry experience with a focus on data analysis and machine learning.
• 7+ years of expertise in Deep Learning (CNNs, RNNs, Transformers).
• 3–4 years focused on LLM development and fine-tuning.
• Proven history deploying industrial AI solutions involving large-scale data and signal processing.
• Hands-on experience with time-series analysis, FFT, and sensor/IoT data pipelines.
• Mastery of Python, TensorFlow, and PyTorch.
• Proficiency with NLP libraries including Hugging Face and LangChain.
• Experience with big data tools (Spark, Hadoop) and cloud platforms (AWS, GCP, Azure).

Key Skills

Education

Any Graduate