Algoleap
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1 to 50 Employees · Hyderābād, India
Hiring: Engineering
What employees say
+ Good support for Employees working.
− If you are a contract employee hired for some other client, you are here till client needs you.
More reviews on the company profile.
Interview experience · Sr Database Administrator
They were clear on requirement needed and feedback was given as soon as client them. Overall, interview experience was very smooth and ontime updates were given to the candidate by hr operations team.
Difficult difficulty · India · 3 reports
More interview insightsJob description
Overview
Responsible for hosting, deploying, and operating open-weight LLMs within a sovereign cloud environment. The role focuses on GPU infrastructure, model serving, performance optimization, and reliable model lifecycle management.
Responsibilities
- Responsible for hosting, deploying, and operating open-weight LLMs within a sovereign cloud environment. The role focuses on GPU infrastructure, model serving, performance optimization, and reliable model lifecycle management.
- Deploy and operate models such as GPT, LLaMA, Gemma, Mistral, and other product/open-weight models within sovereign cloud.
- Manage GPU provisioning, capacity planning, utilization, and performance optimization.
- Implement LLM inference serving using platforms such as vLLM, Triton, or similar frameworks.
- Build model deployment, versioning, rollback, and lifecycle management processes.
- Develop MLOps pipelines for model packaging, testing, deployment, and monitoring.
- Monitor latency, throughput, GPU utilization, availability, and inference costs.
- Implement scalable and highly available model-serving infrastructure using Kubernetes and containers.
- Work closely with platform, security, and gateway teams to ensure secure model access and governance.
- Troubleshoot production issues across GPU, inference, Kubernetes, networking, and model-serving layers.
- MLOps, LLM infrastructure, model serving, GPU-based inference, Kubernetes, vLLM, NVIDIA Triton, TensorRT-LLM, LLaMA, Gemma, Mistral, GPT, Docker, CI/CD, model registries, observability, quantization, batching, caching, GPU memory management, inference optimization, private/sovereign-cloud environments.
- NVIDIA GPUs, CUDA, Helm, Prometheus/Grafana, MLflow, automated model deployment pipelines.
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Job application FAQ
Last updated 4 October 2026
- How do I apply for Algoleap Technologies - MLOps/LLM Infrastructure Engineer at Algoleap?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Algoleap may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this Algoleap Technologies - MLOps/LLM Infrastructure Engineer role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is Algoleap Technologies - MLOps/LLM Infrastructure Engineer remote or on-site in India (+1 other)?
- This listing is marked on_site with location India (+1 other). Confirm details on the job description before applying.
- What skills matter for this Algoleap Technologies - MLOps/LLM Infrastructure Engineer role at Algoleap?
- This is a mid-level Algoleap Technologies - MLOps/LLM Infrastructure Engineer role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.