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Machine Learning Engineer I - LLM

Machine Learning Engineer I - LLM

Skill Connect HR ConsultingBangalore
18 days ago
Job description

Description :

  • Collaborate with senior ML engineers to design and implement AI product features.
  • Train, evaluate, and fine-tune ML and LLM models under guidance.
  • Support the development and maintenance of scalable ML pipelines and APIs.
  • Assist in data preprocessing, feature engineering, and model evaluation.
  • Participate in code reviews, testing, and performance optimization.
  • Help deploy and monitor ML models in production environments.
  • Learn and apply best practices in LLMOps, DevOps, and cloud deployment.
  • Contribute to documentation and internal knowledge-sharing.
  • Deploy LLM solutions tailored to specific use cases.
  • Ensure DevOps and LLMOps best practices using Kubernetes, Docker, and orchestration frameworks.

Technical Requirements :

  • LLM & ML : Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama
  • LLMOps : MLFlow, Langchain, Langgraph, LangFlow, Langfuse, LlamaIndex, SageMaker, AWS Bedrock, Azure AI
  • Databases : MongoDB, PostgreSQL, Pinecone, ChromDB
  • Cloud : AWS, Azure
  • DevOps : Kubernetes, Docker
  • Languages : Python, SQL, JavaScript
  • Certifications (Bonus) : AWS Professional Solution Architect, AWS Machine Learning Specialty, Azure Solutions Architect Expert
  • What You'll Do :

  • Work on real-world Generative AI and NLP applications for the insurance domain.
  • Build and deploy LLM-based pipelines using modern frameworks.
  • Gain hands-on experience with cloud ML infrastructure.
  • Learn how to manage end-to-end ML workflowsfrom experimentation to deployment.
  • Collaborate with cross-functional teams (data, backend, product).
  • Contribute to improving model accuracy, reliability, and scalability.
  • What You Need to Succeed :

  • Bachelors or Masters degree in Computer Science, Machine Learning, or related field.
  • experience in ML, data science, or related software engineering roles (internships count).
  • Strong understanding of ML fundamentals, deep learning architectures, and data processing.
  • Experience building or fine-tuning models using Python ML frameworks.
  • (ref : hirist.tech)

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