Job Summary

We are looking for a Machine Learning Engineer with 2–5 years of experience to build and deploy scalable AI solutions. This role involves end-to-end ownership of ML models—from development to production, working on real-world use cases across NLP, recommendation systems, and Generative AI.

Required Qualifications

• Bachelor’s/Master’s in Computer Science, AI, Data Science, or related field
• 2–5 years of hands-on ML experience in real-world/production environments

Required Skills

• Strong Python skills with ML libraries (NumPy, Pandas, Scikit-learn, TensorFlow)
• Solid understanding of ML algorithms (classification, regression, clustering, NLP)
• Proficiency in SQL and data handling (structured & unstructured data)
• Experience with MLOps practices and model lifecycle management
• Hands-on experience with LLMs (e.g., GPT, LLaMA)
• Familiarity with LLM deployment (APIs, vector DBs, RAG pipelines)
• Strong problem-solving and communication skills

Preferred Skills

• Experience with vector/databases (Pinecone, Elasticsearch)
• Knowledge of visualization tools (Power BI, Tableau)
• Familiarity with Flask APIs for model deployment
• Experience with Docker/Kubernetes

• Design, build, and deploy ML models for business use cases
• Execute end-to-end ML workflows (data prep → training → deployment)
• Analyze large datasets to generate actionable insights
• Optimize model performance, scalability, and accuracy
• Integrate ML solutions into production systems with engineering teams
• Monitor, test, and improve models and data pipelines
• Stay updated with latest AI/ML tools and trends