Facile Technolab Pvt Ltd
https://faciletechnolab.comAbout
We help startup, small & mid-sized healthcare, financial services, manufacturing & event companies design, build, and modernize mission-critical software platforms.
Since 2016, we have been helping clients across the US, Canada, Australia, New Zealand, and Europe with their software outsourcing and staff augmentation needs through our IT Services. We received many awards and recognition for our work in custom software development, SaaS/MVP development, and Azure/Microsoft technologies.
Founded in 2016 in Ahmedabad, India, Facile Technolab has grown into a senior‑heavy engineering team that combines strong product thinking with deep Microsoft expertise. Engagements typically span SaaS product development, legacy application modernization, AI‑enhanced workflows, and secure integrations with ERPs, EMRs, and other critical systems.
Facile Technolab is recognized as a Clutch Global Leader and Champion Company, with 30+ verified reviews and an average rating around 4.8–4.9/5, reflecting high client satisfaction with communication, reliability, and value for money. Clients partner with the company to get opinionated Microsoft guidance, predictable delivery, and long-term support—rather than a generic offshore vendor.
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Jobs at Facile Technolab Pvt Ltd
KubernetesJob Title:
DevOps / MLOps Engineer – GCP, Kubernetes, GPU Workloads, Python
Job Description
We are looking for an MLOps Engineer with 4–7 years of experience in cloud infrastructure, web application development, and ML pipeline deployment. The ideal candidate will manage GPU workloads on Kubernetes (GKE/EKS), optimize ML infrastructure, and handle scalable web applications in cloud environments.
Responsibilities:
- Develop and maintain web apps using Python, TypeScript, and Node.js.
- Manage DevOps pipelines and production infrastructure on GCP, including Terraform, Kubernetes, and cloud storage.
- Deploy, scale, and monitor ML models (vLLM, Triton, TensorRT-LLM) on multi-GPU instances.
- Optimize GPU resources, container GPU passthrough, autoscaling, and cost efficiency.
- Write and run tests for application and infrastructure code.
- Collaborate effectively using online communication tools (Slack, Teams, Zoom).
- Utilize AI coding copilots and productivity tools to accelerate development.
Requirements:
- 4–7 years experience in cloud infrastructure and DevOps/MLOps roles.
- Strong skills in Python, TypeScript, Node.js, and Kubernetes (GKE/EKS).
- Experience with GPU workloads, Terraform, SaaS environments, and Linux administration.
- Knowledge of ML model deployment, CUDA/NCCL debugging, and GPU optimization.
- Conversational English (written, verbal, listening).
Required - CI/CD, Node.js, TypeScript, CUDA, NCCL, GPU optimization, ML model deployment, Infrastructure as Code, Cloud infrastructure, and AI coding copilots.
Job Types: Full-time, Permanent
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