AI & Machine Learning Development:
- Develop, train, and fine-tune machine learning (ML) and deep learning (DL) models.
- Implement LLMs, NLP, reinforcement learning (RL), and computer vision (CV) models.
- Optimize retrieval-augmented generation (RAG) systems with vector databases (FAISS, Pinecone, Chroma).
- Work on multimodal AI systems integrating text, image, and audio processing.
Agentic AI Systems Development:
- Build autonomous AI agents that can make decisions, learn from feedback, and interact with environments.
- Implement multi-agent frameworks using LangChain, CrewAI, AutoGen, BabyAGI, MetaGPT.
- Integrate AI agents with APIs, databases, and enterprise applications for real-world deployment.
Software Engineering & MLOps:
- Design and deploy AI models using Docker, Kubernetes, and CI/CD pipelines.
- Implement MLOps workflows for continuous training, monitoring, and model retraining.
- Optimize AI solutions for cloud platforms (AWS, Azure, GCP) and edge computing.
AI Governance & Security:
- Implement AI safety measures, including adversarial defense and bias mitigation.
- Ensure compliance with AI regulations (GDPR, HIPAA, SOC 2) and ethical AI principles.
- Secure AI agents against prompt injection, model poisoning, and adversarial attacks.
Technical Skills:
- Strong programming skills in Python, Java, or R.
- Expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-Learn).
- Experience with LLMs & NLP (Hugging Face, OpenAI API, BERT, GPT, Claude).
- Proficiency in multi-agent frameworks (LangChain, CrewAI, AutoGen).
- Knowledge of reinforcement learning (PPO, A3C, DDPG, SAC).
- Experience with vector databases (FAISS, Pinecone, Chroma) and knowledge graphs.
- Strong foundation in MLOps, cloud AI services (AWS, Azure AI, Google Vertex AI).
Soft Skills:
- Strong analytical and problem-solving skills.
- Ability to work in a fast-paced, cross-functional team.
- Excellent communication and documentation skills.
Preferred Qualifications:
- Master s. in Computer Science, AI, or Data Science.
- Certifications in AI/ML (AWS ML Specialist, Google ML Engineer, Microsoft AI Engineer).
- Experience with autonomous systems, robotics, or digital twins.
