Description

Design, develop, and deploy production-grade AI, ML, and GenAI solutions for business-critical applications.

This role is on-site.

Responsibilities

• Design and build automated pipelines for model deployment, ensuring scalability and reliability.
• Fine-tune generative models for NLP tasks like summarization and text generation.
• Evaluate and iterate on model architectures (e.g., GPT-4.1) to enhance NLP performance.
• Implement real-time monitoring mechanisms to track model health and reliability.
• Communicate technical AI/ML results to both technical and non-technical stakeholders.

Required Skills

• 9+ years of applied AI/ML engineering experience in production environments.
• Proficiency in Python for model development and integration with OpenAI API.
• Experience with TensorFlow, PyTorch, Scikit-learn, and cloud platforms (AWS, Azure, GCP).
• Strong knowledge of containerization (Docker, Kubernetes) and microservices design.
• Solid understanding of statistics, deep learning, and generative architectures (GANs, VAEs).
• Ability to optimize models for NLP applications and address complex ML challenges.
• Bachelor's or Master's degree in Computer Science, Engineering, or related field.

Preferred Skills

• Familiarity with the financial services industry.
• Expertise in designing RAG pipelines.
• Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, and Graph-of-Thoughts prompting strategies.

Key Skills

Education

Bachelor's or Master's degrees