Tech Stack
AWSAzureCloudDockerERPGoogle Cloud PlatformIoTKerasPythonPyTorchTensorflow
About the role
- Develop and implement AI models and GenAI applications to address business challenges in semiconductors, enterprise technology, consumer technology, medical technology and related industries
- Collaborate with cross-functional teams to gather requirements, design solutions, and deploy models into production environments
- Create industry-leading points-of-view in the client domains you are working on that ensures our positioning as a value-partner
- Utilize your expertise in IoT-IIoT/ERP/CRM systems to integrate data sources and ensure seamless operation of AI solutions
- Design and develop machine learning models using Python, with proficiency in Computer Vision techniques like OpenCV
- Architect functional solutions and provide technical guidance to enhance the performance and scalability of AI systems
- Design and implement GenAI based solutions through contextual prompt engineering and prompt tuning and supporting solution architects on the design of GenAI-powered solutions/assets
- Experience optimizing model hyperparameter tuning for speed and cost
- Containerize and deploy models using Docker and cloud platforms (Azure/AWS/GCP)
Requirements
- 7-15 years of hands-on experience in AI/ML and GenAI
- Prior experience in leading teams that develop data science/GenAI/AI solutions
- Proven track record of developing AI models in channel analytics, marketing & customer experience, analytics, predictive maintenance, production optimization, and connected products
- Exposure to IOT/IIoT/ERP/CRM systems and understanding of their integration with AI solutions
- Proficiency in Python
- Proficiency in Computer Vision techniques (e.g., OpenCV)
- Familiarity with deep learning and machine learning frameworks (Keras, TensorFlow, PyTorch)
- Experience using HuggingFace Transformers and related libraries
- Experience optimizing model hyperparameter tuning for speed and cost
- Experience designing and implementing GenAI-based solutions through contextual prompt engineering and prompt tuning
- Experience with Docker
- Experience with cloud platforms (preferably Azure/AWS; familiarity with GCP)
- Excellent communication, customer service, and problem-solving skills