Job
Description
We are seeking an AI/ML Engineer - I to design, develop, and deploy machine learning models and AI solutions. This role involves working with modern ML frameworks, large language models (LLMs), and building scalable AI applications. **Key Responsibilities:** - Develop and deploy machine learning models using TensorFlow, PyTorch, and Scikit-Learn - Build end-to-end ML pipelines from data preprocessing to model serving - Work with LLMs, implement RAG systems, and develop AI-driven applications - Create REST APIs using FastAPI or Flask and deploy using Docker and Kubernetes - Process and analyze large datasets using SQL, Pandas, and Spark - Implement MLOps practices such as model monitoring, logging, and versioning **Required Skills:** - **Programming & Development:** Python - Strong proficiency, including OOP principles - **Software Architecture:** Familiarity with frontend/backend components, microservices, and API design - **Version Control:** Proficient with Git and platforms like GitHub or GitLab - **ML/AI Technologies:** ML Frameworks - TensorFlow, PyTorch, Scikit-Learn, XGBoost - **LLM Expertise:** Understanding of transformer architectures, fine-tuning, and prompt engineering - **Vector Databases:** Experience with Pinecone, Weaviate, or Chroma for embeddings and similarity search - **Data & Infrastructure:** Data Handling - Pandas, NumPy, SQL, Apache Spark - **Cloud Platforms:** Experience with AWS, GCP, or Azure - **Deployment:** Docker, Kubernetes, FastAPI, Flask, REST APIs - **Mathematical Foundation:** Solid understanding of linear algebra, statistics, and calculus as applied to ML algorithms - **Soft Skills:** Strong problem-solving abilities, clear technical communication, and collaboration across teams **Preferred Qualifications:** - Bachelor's or Masters degree in Computer Science, Data Science, or a related field - Approximately 1 year of experience in ML/AI development - Familiarity with MLOps tools like MLflow or Weights & Biases - Knowledge of computer vision and/or NLP applications **Additional Technical Areas:** - Understanding of data privacy and security best practices - Experience with streaming data processing tools such as Kafka or Apache Beam **Educational Qualifications:** - Bachelors degree in B.Tech/B.E **Rounds Description:** - Preliminary Assessment Round - Virtual AI Interview - Ensure screen sharing and laptop usage - Keep updated resume ready - Keep phone on silent mode - Basic communication assessment - Communication Assessment Round 1 - Assignment Round - Technical Interview - HR Discussion Wishing you the very best!,
