Machine Learning Engineer I - LLM

<p><b>Description : </b><br/><br/>- Collaborate with senior ML engineers to design and implement AI product features.<br/><br/>- Train, evaluate, and fine-tune ML and LLM models under guidance.<br/><br/>- Support the development and maintenance of scalable ML pipelines and APIs.<br/><br/>- Assist in data preprocessing, feature engineering, and model evaluation.<br/><br/>- Participate in code reviews, testing, and performance optimization.<br/><br/>- Help deploy and monitor ML models in production environments.<br/><br/>- Learn and apply best practices in LLMOps, DevOps, and cloud deployment.<br/><br/>- Contribute to documentation and internal knowledge-sharing.<br/><br/>- Deploy LLM solutions tailored to specific use cases.<br/><br/>- Ensure DevOps and LLMOps best practices using Kubernetes, Docker, and orchestration frameworks.<br/><br/><b>Technical Requirements : </b><br/><br/>- LLM & ML : Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama<br/><br/>- LLMOps : MLFlow, Langchain, Langgraph, LangFlow, Langfuse, LlamaIndex, SageMaker, AWS Bedrock, Azure AI<br/><br/>- Databases : MongoDB, PostgreSQL, Pinecone, ChromDB <br/><br/>- Cloud : AWS, Azure <br/><br/>- DevOps : Kubernetes, Docker<br/><br/>- Languages : Python, SQL, JavaScript<br/><br/>- Certifications (Bonus) : AWS Professional Solution Architect, AWS Machine Learning Specialty, Azure Solutions Architect Expert <br/><br/><b>What You'll Do : </b><br/><br/>- Work on real-world Generative AI and NLP applications for the insurance domain.<br/><br/>- Build and deploy LLM-based pipelines using modern frameworks.<br/><br/>- Gain hands-on experience with cloud ML infrastructure.<br/><br/>- Learn how to manage end-to-end ML workflowsfrom experimentation to deployment.<br/><br/>- Collaborate with cross-functional teams (data, backend, product).<br/><br/>- Contribute to improving model accuracy, reliability, and scalability.<br/><br/><b>What You Need to Succeed : </b><br/><br/>- Bachelors or Masters degree in Computer Science, Machine Learning, or related field.<br/><br/>- experience in ML, data science, or related software engineering roles (internships count).<br/><br/>- Strong understanding of ML fundamentals, deep learning architectures, and data processing.<br/><br/>- Experience building or fine-tuning models using Python ML frameworks.</p> (ref:hirist.tech)