AI/ML Developer

3 days ago

Chennai Porur, India LateShipment Full time ₹ 8,00,000 - ₹ 24,00,000 per year
  • We are seeking a highly skilled AI/ML Developer to join our team in Chennai. The ideal candidate will have expertise in Python, machine learning libraries, and deep learning frameworks, along with hands-on experience in offline/self-hosted LLMs. You will work on building customized models, integrating pre-trained/self-hosted models, and deploying them at scale. The role involves diverse projects in computer vision, NLP, recommendation systems, MLOps, and data pipelines.Key Responsibilities
  • Design, train, and deploy custom ML/DL models using Python.
  • Work with offline/self-hosted LLMs (LLaMA, Mistral, Falcon, GPT-J, etc.) using
  • Hugging Face, vLLM, Ollama, LangChain, RAG pipelines.
  • Develop and optimize models with classical ML libraries:
  • o Scikit-learn, XGBoost, LightGBM, CatBoost
  • Build deep learning solutions using:
  • o PyTorch, TensorFlow, Keras
  • Work on computer vision tasks with OpenCV, PyTorch/TensorFlow (classification, detection, OCR, segmentation).
  • Develop NLP applications (text classification, embeddings, summarization, chatbots) using NLTK, SpaCy, Hugging Face Transformers.
  • Construct and maintain data pipelines using Airflow, Spark, Kafka, or Prefect.
  • Apply MLOps practices: model versioning, CI/CD, monitoring, retraining workflows.
  • Deploy models across cloud and on-prem environments (AWS, GCP, Azure, bare-metal).
  • Collaborate with cross-functional teams to deliver AI-driven solutions.Required Skills & Experience
  • Bachelors/Masters in Computer Science, Data Science, AI/ML, or related field.
  • 2 - 3 years of hands-on experience in Python-based AI/ML development.
  • Strong expertise with ML/DL libraries: Scikit-learn, XGBoost, LightGBM, CatBoost, PyTorch, TensorFlow, Keras.
  • Proficiency in data analysis and processing with Pandas, NumPy, Dask.
  • Knowledge of offline/self-hosted LLMs and private deployment stacks.
  • Familiarity with vector databases (FAISS, Pinecone, Weaviate, Milvus) for RAG.
  • Experience with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes, SageMaker).
  • Strong debugging and optimization skills for ML pipelines and models.Nice to Have
  • Experience with Generative AI (LLMs, diffusion models, fine-tuning).
  • Exposure to reinforcement learning and advanced recommender systems.
  • Open-source contributions in Python/AI/ML.

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