Summary Gainwell is seeking LLM Ops Engineers and ML Ops Engineers to join our growing AI/ML team. This role is responsible for developing, deploying, and maintaining scalable infrastructure and pipelines for Machine Learning (ML) models and Large Language Models (LLMs). You will play a critical role in ensuring smooth model lifecycle management, performance monitoring, version control, and compliance while collaborating closely with Data Scientists, DevOps. Your role in our mission Core LLM Ops Responsibilities: stylemargin:bottom:11.0px: : Develop and manage scalable deployment strategies specifically tailored for LLMs (GPT, Llama, Claude, etc.). : Optimize LLM inference performance, including model parallelization, quantization, pruning, and fine:tuning pipelines. : Integrate prompt management, version control, and retrieval:augmented generation (RAG) pipelines. : Manage vector databases, embedding stores, and document stores used in conjunction with LLMs. : Monitor hallucination rates, token usage, and overall cost optimization for LLM APIs or on:prem deployments. : Continuously monitor models for its performance and ensure alert system in place. : Ensure compliance with ethical AI practices, privacy regulations, and responsible AI guidelines in LLM workflows. Core ML Ops Responsibilities: stylemargin:bottom:11.0px: : Design, build, and maintain robust CI/CD pipelines for ML model training, validation, deployment, and monitoring. : Implement version control, model registry, and reproducibility strategies for ML models. : Automate data ingestion, feature engineering, and model retraining workflows. : Monitor model performance, drift, and ensure proper alerting systems are in place. : Implement security, compliance, and governance protocols for model deployment. : Collaborate with Data Scientists to streamline model development and experimentation. What were looking for stylemargin:bottom:11.0px: : Bachelors/Master's degree in computer science, Engineering, or related fields. : Strong experience with ML Ops tools (Kubeflow, MLflow, TFX, SageMaker, etc.). : Experience with LLM:specific tools and frameworks (LangChain,Lang Graph, LlamaIndex, Hugging Face, OpenAI APIs, Vector DBs like Pinecone, FAISS, Weavite, Chroma DB etc.). : Solid experience in deploying models in cloud (AWS, Azure, GCP) and on:prem environments. : Proficient in containerization (Docker, Kubernetes) and CI/CD practices. : Familiarity with monitoring tools like Prometheus, Grafana, and ML observability platforms. : Strong coding skills in Python, Bash, and familiarity with infrastructure:as:code tools (Terraform, Helm, etc.).Knowledge of healthcare AI applications and regulatory compliance (HIPAA, CMS) is a plus. : Strong skills in Giskard, Deepeval etc. What you should expect in this role stylemargin:bottom:11.0px: : Fully Remote Opportunity : Work from anywhere in theIndia : Minimal Travel Required : Occasional travel opportunities (0:10). : Opportunity to Work on Cutting:Edge AI Solutions in a mission:driven healthcare technology environment.