MLOps Engineer
You will build model serving infrastructure, latency tracking pipelines, and automated deployments for production AI services.
What you'll work with.
As an MLOps Engineer at TheWebVale, you will manage the operational lifecycle of AI models and inference engines. You will deploy open-weight language models, embedding services, and prediction pipelines on GPU and CPU cloud instances for business client applications. You will collaborate closely with AI engineers and backend developers in our regular two-to-three week release intervals. You will ensure models are served with low latency, high availability, auto-scaling, and predictable cloud expenditure.
Your day to day.
6 things, one at a time. Keep scrolling.
Deploy and scale machine learning and LLM inference engines using vLLM, Triton, or Ollama.
Build automated CI/CD deployment pipelines for model weights, embeddings, and prompt configs.
Configure GPU hardware monitoring, memory allocation, and utilization alerts.
Implement model versioning, rollback protocols, and blue-green deployment strategies.
Track inference latencies, token consumption rates, and error rates using Prometheus and Grafana.
Optimize container images to reduce cold-start latency and cloud server costs.
What we look for.
6 things, one at a time. Keep scrolling.
Hold 3–5 years of software engineering or DevOps experience with dedicated MLOps focus.
Demonstrate strong proficiency with Docker, Linux system administration, and GPU drivers.
Show hands-on experience serving models with vLLM, Hugging Face TGI, or FastAPI.
Understand model quantization formats, tensor parallelism, and batching mechanisms.
Possess experience building automated deployment workflows in GitHub Actions.
Communicate infrastructure reliability and capacity plans clearly to engineering leads.
What you get.
Three steps, no tricks.
- 1
Intro chat
A short call about what you want to work on and how you like to work.
- 2
Work review
Walk us through projects, code or designs you are proud of.
- 3
Paid task
A small paid task or pairing session, so both sides see the fit.
Apply for MLOps Engineer .
Tell us about your work. We reply to every application, usually within a few days.