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:
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-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:
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-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 we're looking for
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-Bachelor's/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
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-Fully Remote Opportunity – Work from anywhere in the India
-Minimal Travel Required – Occasional travel opportunities (0-10%).
-Opportunity to Work on Cutting-Edge AI Solutions in a mission-driven healthcare technology environment.
