Description :
Machine Learning Engineer LLM Applications
Overview :
We are looking for a Machine Learning Engineer with hands-on experience in productionizing Large Language Model (LLM) applications. The ideal candidate will be skilled at building scalable, reliable ML pipelines and deploying models to production environments.
Key Responsibilities :
- Design, develop and deploy LLM-based applications using scalable cloud infrastructure.
- Build and orchestrate data and model pipelines using Apache Airflow and GCP services (BigQuery, Vertex AI, Cloud Run, etc.).
- Implement retrieval-augmented generation (RAG) systems with vector databases (e.g., Pinecone, FAISS, Weaviate).
- Containerize, test and deploy ML workloads using Docker and Kubernetes.
- Maintain CI / CD workflows using Git, Jenkins, or similar tools.
- Monitor, optimize and troubleshoot production ML systems for reliability and performance.
Required Skills & Experience :
Proven experience in LLM application development and MLOps.Strong proficiency in Python, TensorFlow / PyTorch and cloud-native ML pipelines.Hands-on expertise in GCP, Airflow, BigQuery, Docker and vector databases.Good to Have :
Familiarity with Kubernetes, Git, Jenkins and modern CI / CD practices.Understanding of embeddings, prompt engineering and model serving in production.Interest in RAG performance optimisation and benchmarking.(ref : hirist.tech)