Job
Description
Job Title : AI/ML Engineer (with LLM, Azure, Python & PySpark expertise) Job Description : We are looking for a skilled and experienced AI/ML Engineer to join our data science and AI team. The ideal candidate will have a strong foundation in machine learning, artificial intelligence, and large language models (LLMs), along with deep proficiency in Python, PySpark, and Microsoft Azure services. You will be responsible for developing and deploying scalable AI solutions, working with big data frameworks, and leveraging cloud platforms to operationalize machine learning models. Key Responsibilities : Artificial Intelligence (AI) & Machine Learning (ML): Design, develop, and optimize machine learning and AI models to solve business problems. Perform exploratory data analysis and feature engineering for model development. Use supervised, unsupervised, and reinforcement learning techniques where appropriate. Build AI pipelines and integrate models into production systems. Large Language Models (LLM): Fine-tune and deploy LLMs (e.g., OpenAI, Hugging Face, or custom-trained models). Develop prompt engineering strategies for LLM applications. Implement RAG (Retrieval-Augmented Generation) systems or LLMOps workflows. Evaluate LLM outputs for accuracy, bias, and performance. Python Programming: Write efficient, reusable, and testable Python code for data processing, modeling, and API services. Build automation scripts for data pipelines and model training workflows. Use popular libraries such as Scikit-learn, TensorFlow, PyTorch, Pandas, and NumPy. PySpark and Big Data: Work with large datasets using PySpark for data wrangling, transformation, and feature extraction. Optimize Spark jobs for performance and scalability. Collaborate with data engineering teams to implement end-to-end data pipelines. Microsoft Azure: Deploy models and applications using Azure ML, Azure Databricks, Azure Functions, and Azure Synapse. Manage compute resources, storage, and data security on Azure. Use Azure DevOps for CI/CD of ML pipelines and automation. Cross-Functional Collaboration & Documentation: Collaborate with data engineers, product managers, and business stakeholders to align technical solutions with business needs. Maintain clear documentation of models, code, and workflows. Present technical findings and model outcomes to both technical and non-technical audiences. Required Skills & Qualifications : Bachelor's or Masters degree in Computer Science, Data Science, Engineering, or a related field. 3+ years of experience in AI/ML and data engineering roles. Proficient in Python and PySpark. Experience with cloud platforms, especially Microsoft Azure. Hands-on experience with LLMs (e.g., GPT, BERT, Claude, etc.). Familiarity with ML frameworks like Scikit-learn, TensorFlow, or PyTorch. Solid understanding of ML lifecycle, MLOps, and deployment strategies. Nice to Have : Experience with LLMOps and vector databases (e.g., FAISS, Pinecone). Knowledge of data governance and responsible AI practices. Azure certifications (e.g., Azure AI Engineer Associate, Azure Data Scientist Associate). Experience with REST APIs and containerization (Docker, Kubernetes).
