Key Responsibilities:
Design, develop, and deploy robust and scalable AI/ML models and GenAI solutions
Implement ML workflows, including data preprocessing, feature engineering, model training, validation, and deployment
Develop and optimize data pipelines for both training and inference
Integrate LLMs using prompt engineering techniques to address domain-specific challenges
Collaborate with cross-functional teams to prototype solutions using low-code/no-code platforms or rapid development tools
Ensure effective model monitoring, versioning, and lifecycle management through MLOps best practices
Utilize cloud services (AWS, Azure, or GCP) to build and scale AI/ML solutions
Research and experiment with Agentic AI and other emerging technologies as needed
Required Skills & Qualifications:
4–6 years of experience in AI/ML development and deployment
Strong proficiency in Python and ML/DL frameworks such as TensorFlow or PyTorch
Proven experience working with Generative AI, LLMs, and prompt engineering
Experience in building and managing data pipelines and implementing MLOps practices
Hands-on experience with cloud platforms (AWS, Azure, or GCP)
Exposure to low-code/no-code platforms or rapid prototyping tools
Strong problem-solving abilities and adaptability in a fast-paced environment
Excellent communication and collaboration skills
Preferred Qualifications:
Experience or research in Agentic AI systems
Familiarity with API integrations, vector databases, and model fine-tuning techniques
Contributions to open-source AI/ML projects or published research are a plus
