We're Hiring | LLM Ops Engineer (Infrastructure & Performance)

We are looking for a Junior AI MLOps Engineer to join our Data Science & AI/ML team in Bangalore. If you're passionate about AI infrastructure, LLM deployment, cloud optimization, and building reliable, scalable ML systems, we'd love to hear from you!

? Location: Bangalore – In office? Experience: 1–2 Years? Department: Data Science & AI/ML☁️ Primary Cloud: AWS

Key Responsibilities

- Evaluate AWS hosting options such as Lambda, EC2, SageMaker, and Bedrock to optimize cost and performance for LLMs and ML models.
- Track and analyze cost-per-inference, latency, throughput, and resource utilization.
- Build and maintain CI/CD pipelines for model testing, containerization, and deployment.
- Deploy and manage ML workloads using Docker, Kubernetes, and AWS services such as EKS and ECS.
- Monitor model performance, API health, infrastructure reliability, and model drift.
- Optimize CPU/GPU utilization, availability, scalability, and cloud infrastructure costs.




- Collaborate with Data Science teams to deploy models as scalable, version-controlled microservices.

Required Skills
- 1–2 years of hands-on experience in MLOps, DevOps, or Backend Engineering, preferably working with ML infrastructure.
- Strong proficiency in Python.
- Experience with Docker and Kubernetes.
- Practical knowledge of AWS services, including Lambda, EC2, S3, and SageMaker.
- Understanding of CI/CD pipelines, model deployment, monitoring, and versioning.
- Familiarity with FastAPI or Flask and REST API integration.
- Basic understanding of the ML lifecycle, model monitoring, and feature stores.
- Analytical skills to evaluate infrastructure performance and cost efficiency.

Good to have: Exposure to AWS Bedrock, LLM deployment, and AI infrastructure cost optimization.

Education

Bachelor's degree in Computer Science, Information Technology, or a related technical field.

📌 LLM Ops Engineer (Bengaluru)
🏢 Dinoxo
📍 Bengaluru