Description

Key Skills: LLM, Python, Generative AI, AWS, Azure

Roles and Responsibilities:

• Utilize Large Language Models (LLMs), Generative AI frameworks, open-source technologies, and machine learning techniques to build transformative AI solutions.
• Architect and develop scalable, distributed systems and machine learning platforms for enterprise AI use cases.
• Optimize generative AI models for scalability, performance, reliability, and operational efficiency.
• Develop and maintain AI pipelines including data preprocessing, feature extraction, model training, evaluation, and deployment workflows.
• Build AI solutions aligned with responsible AI standards, governance practices, and ethical AI principles.
• Work with open-source models, cloud-based AI services, and enterprise AI platforms to deliver best-fit technical solutions.
• Collaborate with business stakeholders, data scientists, and machine learning engineers to translate requirements into scalable AI solutions.
• Contribute to AI engineering best practices, reusable frameworks, and development standards for generative AI initiatives.
• Document technical specifications, architectural decisions, and AI implementation approaches.
• Communicate complex AI and machine learning concepts effectively to both technical and non-technical stakeholders.
• Lead technical discussions, provide guidance to project teams, and contribute to strategic AI initiatives.

Skills Required:

• Strong programming expertise in Python for AI/ML and data-driven application development.
• Hands-on experience with Generative AI, Large Language Models (LLMs), and Transformer-based architectures.
• Expertise in NLP models and frameworks including BERT, RoBERTa, GPT, SpaCy, NLTK, and Hugging Face.
• Strong experience with machine learning and deep learning frameworks such as TensorFlow, PyTorch, and Keras.
• Knowledge of deep learning concepts including GANs, VAEs, self-supervised learning, transfer learning, and reinforcement learning.
• Experience building scalable AI pipelines for preprocessing, feature extraction, model training, validation, and evaluation.
• Strong understanding of distributed machine learning, distributed systems, and scalable AI architectures.
• Experience developing recommendation engines, sequential modeling systems, and intelligent automation solutions.
• Strong knowledge of data structures, algorithms, software engineering principles, and numerical programming.
• Ability to optimize generative AI models for performance, scalability, latency, and efficiency.
• Experience implementing responsible AI practices, governance, and ethical AI principles.
• Strong analytical, research, communication, and technical leadership skills.
• Ability to work effectively within cross-functional and matrixed enterprise environments.

Nice to Have

• Experience with AWS and Azure cloud platforms for AI/ML deployment and infrastructure management.

Education: Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field preferred

Key Skills

Education

Any Graduate