Design, develop, and deploy AI/ML models to solve business challenges (e.g., personalization, demand forecasting, predictive maintenance).
Clean, preprocess, and validate data to ensure quality and consistency for analysis.
Use statistical methods to understand data distributions and relationships.
Select appropriate algorithms based on project scope to maximize model performance (e.g., regression, classification, clustering, NLP, computer vision).
Fine-tune and customize LLMs (e.g., GPT, LLaMA, Mistral) for business-specific use cases.
Integrate LLMs into products and workflows via APIs, microservices, or edge deployments using tools such as LangChain, FastAPI, or vector databases (e.g., FAISS, Pinecone).
Deploy the AI/ML model into production setting.
Interpret analysis results and translate complex findings into clear, actionable recommendations for both technical and non-technical stakeholders.
Requirements:
2+ years of experience in data science, machine learning, or AI engineering roles
Proficiency in programming languages such as SQL, Python, and R.
Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
Experience in Prompt Engineering and Fine-tuning LLMs
Familiarity with LLM orchestration frameworks like LangChain and LlamaIndex
Experience with MLOps tools and practices for model monitoring, CI/CD for ML, and deploying models into production environments.
Excellent verbal and written communication to explain technical concepts to non-technical stakeholders and produce clear documentation.
Intellectual curiosity, teamwork, adaptability, and passion for continuous learning.
