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Apple Machine Learning Engineer India, Telangana, Hyderabad 861736955
06.05.2025
We are seeking a highly skilled and motivated Machine Learning Engineer with a solid focus on Large Language Models (LLMs) and text processing. In this role, you will work on building, fine-tuning, optimising, and deploying LLMs for real-world applications. You'll also be responsible for generating scripts using LLMs, customising models using platforms like Ollama, and integrating them into robust applications. Design and implement solutions leveraging LLMs for text generation, understanding, summarisation, classification, and extraction tasks. Customise and fine-tune LLMs using domain-specific data with tools like Ollama and LoRA/QLoRA. Optimize LLMs for inference speed, accuracy, and resource efficiency (quantisation, pruning, etc.). Integrate LLM functionalities into end-user applications with a strong emphasis on usability and performance. Collaborate with product, design, and engineering teams to translate business requirements into ML-based solutions. Develop APIs and micro-services for model serving and deployment. Monitor model performance and implement continuous improvement and retraining strategies. Stay updated with the latest research and trends in the LLM space and propose innovative ideas.
- 5+ years of experience in ML/NLP with a focus on large language models and text data with Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
- Experience with prompt engineering, retrieval-augmented generation (RAG), and vector databases (e.g., Pinecone, FAISS).
- Strong programming skills in Python, including popular ML/NLP libraries (e.g., HuggingFace Transformers, PyTorch, LangChain).
- Experience with LLM customisation and fine-tuning (e.g., on GPT, LLaMA, Mistral, Mixtral) and Hands-on experience with Ollama or similar tools for local/custom model deployment.
- Demonstrable ability to optimize model performance for production environments.
- Solid grasp of REST APIs, application development, and software engineering standard processes.
- Experience working with containerization (e.g., Docker) and orchestration tools (e.g., Kubernetes) is a plus.
- Exposure to frontend/backend development for building LLM-powered dashboards or assistants.
- Understanding of MLOps, model versioning, and continuous improvement practices.
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