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ML Engineer (MLOps)
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Job Overview
About DeepLabs
DeepLabs Innovation and Research Development researches, builds and deploys applied AI, machine learning and intelligent-automation products from Ahmedabad, India. Our teams build software platforms, AI agents, prototypes and proofs of concept, and work with businesses, academic institutions and industry partners to turn research into products.
About the Role
You will design the secure, internet-free environments our models run in, deploy deep-learning models inside them, and keep GPU spend under control. You will also research emerging AI solutions and build dashboards that show how our models perform.
What You Will Do
Infrastructure and Security
- Design secure, internet-free (air-gapped) cloud and on-premises architectures for ML workloads.
- Set up network isolation, private package and container registries, identity and access controls.
- Document each environment's architecture, security controls and recovery steps.
ML and Deep-Learning Stack
- Build, train and deploy convolutional neural networks (CNNs) for image classification inside disconnected VPCs.
- Run the MLOps pipeline offline: data versioning, training, evaluation, model registry, deployment and monitoring.
- Track model drift and retrain when accuracy drops below agreed thresholds.
FinOps and Cost Analysis
- Engineer the cost of distributed training and inference, so GPU and high-speed networking resources are used efficiently.
- Monitor utilisation, right-size clusters and schedule jobs to cut idle GPU time.
- Report monthly cost per model and per experiment, with savings recommendations.
Market Research
- Coordinate research on trial-phase AI solutions to map market competition.
- Benchmark competing architectures on accuracy, latency and cost.
- Write recommendations based on research and benchmarking.
Data Visualisation
- Build sentiment and performance dashboards that show model accuracy, latency and cost over time.
- Present results to the team and leadership in weekly reviews.
What You Bring
We are looking for a skilled professional with practical experience in machine learning, production deployments and MLOps.
Hiring Process
Apply by email or through the DeepLabs career portal.
Initial discussion with the hiring team.
ML system-design discussion and practical assignment.
Final discussion with the Head of Deep Lab.
Ready to Apply?
Send your CV and a short note on one ML system you have deployed.
hr@deeplabs-pi.comGet in touch with our team: hr@deeplabs-pi.com
