AI/ML Lead

Job Summary

We are seeking a highly skilled Software Development Engineer (AI/ML Lead) with strong expertise in Artificial Intelligence and Machine Learning. The ideal candidate will have proven experience in building, implementing, and customizing advanced AI/ML models, along with strong software engineering fundamentals. This role requires collaboration in a fast-paced, innovative environment.

Key Responsibilities

• Design, develop, and implement AI/ML applications, with a focus on Large Language Models (LLMs) and their integration into enterprise systems.
• Develop scalable solutions using Python, R, or Java.
• Customize and optimize prebuilt models such as GPT, BERT, and DALL-E for business use cases.
• Architect and deploy high-performance LLM-based applications.
• Implement MLOps practices using tools like LangChain, LlamaIndex, and Ragas for model deployment and monitoring.
• Build applications leveraging Natural Language Processing (NLP) and Computer Vision.
• Collaborate with cross-functional teams to gather requirements and deliver solutions.
• Contribute to AI/ML research initiatives (papers, conferences, innovation programs).
• Stay up to date with the latest advancements in AI/ML technologies.

Mandatory Skills

• Strong hands-on experience in AI/ML development and implementation.
• Proficiency in Python, R, or Java.
• Expertise in deep learning frameworks: TensorFlow, PyTorch, or Keras.
• Experience with LLMs and prebuilt model customization (GPT, BERT, DALL-E).
• Knowledge of MLOps practices and tools.
• Experience with cloud platforms: AWS, Google Cloud Platform, or Azure.
• Hands-on experience with Docker and Kubernetes.
• Familiarity with cloud AI services such as Amazon Bedrock, AWS SageMaker, Google Vertex AI.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration abilities.

Preferred Skills

• Experience with AI/ML APIs and cloud AI services (Google AI, Azure AI, AWS SageMaker).
• Knowledge of Agile methodologies and modern software development practices.
• Contributions to AI/ML research (publications, conference presentations).