Key Responsibilities
Build, train, and optimize AI/ML models for a variety of use cases (e.g., predictive analytics, recommendation systems, computer vision, NLP).
Implement and fine-tune large language models (LLMs) such as GPT, Claude, Gemini, and open-source alternatives for chatbots, summarization, content generation, and automation.
Collect, clean, and preprocess structured and unstructured data for AI model training.
Deploy AI solutions into production environments and integrate with existing systems via APIs or cloud platforms.
Optimize AI models for accuracy, efficiency, and scalability.
Work with stakeholders to define AI solution requirements, KPIs, and expected outcomes.
Required Skills
Proficiency in Python (TensorFlow, PyTorch, Scikit-learn, Hugging Face, LangChain) and familiarity with R, Java, or C++.
Strong knowledge of machine learning algorithms, deep learning architectures (CNN, RNN, Transformers), NLP, and computer vision.
Experience with SQL, NoSQL, and big data frameworks (Spark, Hadoop).s.
Hands-on experience with AWS AI/ML, Azure AI, or Google Cloud AI services.
Experience with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes).