Python AI Developer

We are looking for a talented Python AI Engineer with 3–4 years of experience in designing, developing, and deploying AI/ML solutions. The ideal candidate should have expertise in machine learning, large language models (LLMs), data preprocessing, model training, deployment, and backend integration. You will work closely with cross-functional teams to build intelligent, scalable, and production-ready AI applications.

Key Responsibilities

• Design, develop, train, and optimize machine learning and deep learning models for real-world applications.
• Fine-tune and evaluate Large Language Models (LLMs) for domain-specific use cases.
• Build AI-powered applications by integrating LLMs through APIs and frameworks such as LangChain or LlamaIndex.
• Perform data collection, cleaning, preprocessing, feature engineering, and exploratory data analysis (EDA).
• Develop and maintain end-to-end ML pipelines for training, evaluation, and deployment.
• Deploy machine learning models using REST APIs, Docker, and cloud platforms.
• Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases.
• Optimize model performance, latency, scalability, and inference efficiency.
• Collaborate with software engineers and product teams to integrate AI solutions into production systems.
• Monitor model performance, retrain models as needed, and ensure reliability in production environments.
• Stay up to date with the latest advancements in AI, machine learning, and generative AI technologies.

Required Skills

• 3–4 years of professional experience in Python development and AI/ML engineering.
• Strong proficiency in Python and its AI/ML ecosystem.
• Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.
• Hands-on experience training, fine-tuning, and evaluating machine learning and deep learning models.
• Experience integrating and working with Large Language Models (OpenAI, Anthropic, Llama, Mistral, Gemini, or similar).
• Strong understanding of prompt engineering and LLM application development.
• Experience with LangChain, LlamaIndex, CrewAI, or similar AI orchestration frameworks.
• Strong knowledge of data preprocessing, cleaning, transformation, and exploratory data analysis.
• Experience with SQL and working with structured and unstructured datasets.
• Experience deploying ML models using FastAPI, Flask, or Django.
• Knowledge of vector databases such as Pinecone, Weaviate, ChromaDB, Milvus, or FAISS.
• Experience with Docker, Git, and Linux environments.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.

Preferred Qualifications

• Experience implementing Retrieval-Augmented Generation (RAG) architectures.
• Knowledge of MLOps tools such as MLflow, Kubeflow, SageMaker, or Vertex AI.
• Experience with model monitoring, versioning, and continuous deployment.
• Familiarity with distributed training and GPU optimization.
• Experience with CI/CD pipelines for AI applications.
• Knowledge of NLP, computer vision, or time-series forecasting is a plus.
• Experience working with Apache Airflow or similar workflow orchestration tools.

Nice to Have

• Experience with Hugging Face Transformers and PEFT/LoRA fine-tuning.
• Familiarity with ONNX, TensorRT, or model quantization techniques.
• Experience with Kubernetes and container orchestration.
• Knowledge of Apache Spark or distributed data processing frameworks.
• Contributions to open-source AI projects or published research are a plus.

Education

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering