Cloudkeeper

Designation: Lead MLOps Engineer (GPU Optimization)

About CloudKeeper: 

CloudKeeper is a cloud cost optimization partner that combines the power of group buying & commitments management, expert cloud consulting & support, and an enhanced visibility & analytics platform to reduce cloud cost & help businesses maximize the value from AWS, Microsoft Azure, & Google Cloud. 

A certified AWS Premier Partner, Azure Technology Consulting Partner, Google Cloud Partner, and FinOps Foundation Premier Member, CloudKeeper has helped 350+ global companies save an average of 20% on their cloud bills, modernize their cloud set-up and maximize value — all while maintaining flexibility and avoiding any long-term commitments or cost. 

CloudKeeper hived off from TO THE NEW, a digital technology service company with 2500+ employees and an 8-time GPTW winner. 

To know more, please visit - https://www.cloudkeeper.com/ 

Responsibilities:

  - Drive R&D and engineering for AI Infrastructure optimization within CloudKeeper's FinOps for AI platform — building the Tuner AI / Commit AI capability on GPU and ML workloads

  - Design and build optimization engines for GPU right-sizing, idle shutdown, spot migration with checkpoint/resume automation, inference batching, quantization, and model placement

  - Extend the optimization stack to LLM-era workloads — caching, model routing, dynamic batching, prompt optimization, RAG-aware architectures

  - Partner with the Lens AI team to translate GPU and ML workload signals into actionable, dollar-quantified optimization recommendations for customers

  - Work cross-functionally with product, platform, and customer success teams to ship optimization features end-to-end (data ingestion → optimization engine → customer-facing recommendation)

  - Lead technical direction for AI workload optimization, set engineering standards, and mentor the ML / MLOps engineering bench as the AI Infrastructure pillar scales

  - (Lead level) Hire, ramp, and grow a team of ML infrastructure engineers as headcount expands

  Must Have:

  - B.E / B.Tech / M.Tech / MCA with 7+ years of hands-on engineering experience

  - Production experience with GPU workloads — has measurably optimized GPU utilization,  throughput, or cost in a real production environment, not just academic / lab work

  - Strong performance engineering background — must come ready with a concrete optimization story including before/after metrics (latency, throughput, or cost reduction)

  - Strong Python + Linux + systems fundamentals

  - Solid understanding of the ML model lifecycle — training, serving, inference — able to reason about what is running on the GPU and why

  - MLOps fluency — model deployment, monitoring, observability, GPU cluster operations

  - Hands-on with cloud GPU instances (AWS P5 / G6, Azure ND series, GCP A3, or equivalent) and Kubernetes-based GPU orchestration (EKS / AKS / GKE GPU node pools, Karpenter, Run:ai, NVIDIA GPU Operator, or similar)

  - Familiarity with at least one modern LLM inference framework — vLLM, TGI, Triton, SGLang, Ray Serve, or BentoML

  - Strong communication skills — able to translate deep technical optimization into customer / business outcomes

  - (Lead level) Experience managing or technically leading a team of 3+ engineers

  Good to Have:

  - Deep LLM-era optimization expertise — KV caching, semantic caching, model routing, dynamic batching, quantization (FP16 → INT8 → INT4), model distillation, structured outputs

  - Familiarity with LLM workload patterns — RAG, agents, embeddings, vector databases (Pinecone, Weaviate, Qdrant)

  - CUDA, NCCL, mixed-precision training and inference

  - Experience with managed ML training platforms — SageMaker, Azure ML, Vertex AI, Databricks Mosaic

  - Exposure to GPU-native clouds — CoreWeave, Lambda Labs, RunPod, Crusoe

  - Open source contributions to ML infrastructure projects — vLLM, llama.cpp, TGI, Ray, Triton, KubeRay

  - Adjacent experience in cloud cost optimization / FinOps — Spot.io, ScaleOps, Granulate, CAST AI

  - Comfort with Agile methodology and modern engineering practices (CI/CD, code review, observability)

About CloudKeeper:

CloudKeeper is a cloud cost optimization partner that combines the power of group buying & commitments management, expert cloud consulting & support, and an enhanced visibility & analytics platform to reduce cloud costs & help businesses maximize the value from AWS, Microsoft Azure, & Google Cloud. A certified AWS Premier Partner, Azure Technology Consulting Partner, Google Cloud Partner, and FinOps Foundation Premier Member, CloudKeeper has helped 350+ global companies save an average of 20% on their cloud bi ls, modernize their cloud set-up and maximize value — al while maintaining flexibility and avoiding any long-term commitments or cost. CloudKeeper has spun off from TO THE NEW, a digital technology service company with 2500+ employees and an 8-time GPTW winner.

To know more about CloudKeeper,

please visit - https://www.cloudkeeper.com/ To know more about TO THE NEW, please visit - https://www.tothenew.com/

Responsibilities:

● Generate qualified leads for various services of CloudKeeper with a target geography outside India.

● Develop relationships with new customers and nurture existing ones. ● Use Outbound Lead Generation tools such as calls and email Marketing to hunt for new business.

● Demonstrate an understanding of customers’ critical business issues and propose CloudKeeper’s solutions that help clients meet their business objectives.

Must Have:

● Must be willing to work in rotational shifts.

● Good verbal and written communication skills

● A hunter by nature who loves to look for new opportunities

● Enthusiastic, positive, and energetic

In addition to the compensation, the following benefits are provided by the company as per the prevailing policy:

● Gratuity

● Medical insurance

● Accidental insurance. Work Model: Work from Office (all 5 days). Location: Noida Sector 144 

About the Role

As the Product Manager at CloudKeeper, you will lead the strategy, roadmap, and execution of our real-time Cloud usage optimization and recommendation platforms. 

As we expand our portfolio and deepen capabilities across cost optimization, observability, automation, and cloud management, we are seeking a Product Manager who can drive the vision, roadmap, and execution for one or more products within the CloudKeeper Platform Suite such as Lens, Tuner, Commit, Gen AI and Check

You will work cross-functionally across engineering, data science, FinOps SME, go-to-market and customer success to drive product growth, adoption, and customer value.

Key Responsibilities

• Define the vision and product strategy for CloudKeeper Platform Suite, aligned with overall cloud cost & usage optimization goals and the broader CloudKeeper solutions.
• Own the product roadmap: prioritize features, enhancements, integrations, and user experience improvements
• Own end-to-end product lifecycle: concept → PRDs → UX/design → development → launch → iteration
• Work with UX/design to craft intuitive workflows for engineering/DevOps users, ensuring that insights embed into their flow of work 
• Engage with customers (particularly engineering and FinOps teams) to gather feedback, identify pain points, and validate product direction.
• Drive annual planning, release cycles, and sprint delivery (Agile methodology) while ensuring high quality and timely launch of features.
• Ensure appropriate documentation, training materials, and enablement for internal teams and external customers.

Desired Qualifications 

• Bachelor’s degree in Computer Science, Engineering, Business or related field (Master’s preferred).
• 5+ years of product management experience in SaaS, preferably in cloud infrastructure, FinOps, cloud cost optimisation, or dev tools.
• Experience in B2B / Enterprise SaaS product development is a must (B2C product experience will not be considered)
• Strong understanding of AWS or other public-cloud: you should know at least the major compute / storage / services / networking footprint and usage patterns. 
• Proven ability to translate customer needs into product features, write product requirements (PRDs), and work with engineering teams on execution.
• Proficiency with product management, collaboration, and analytics tools (e.g., Jira, Confluence, Figma, Productboard, BI dashboards, PostHog)

Preferred 

• Prior experience in cloud cost optimization, cost-management tools, or FinOps practices is a strong plus
• Exposure to FinOps platforms or cloud cost optimization tools (e.g., AWS Cost Explorer/CUR, CloudHealth or equivalents)

What You’ll Work On

• Lead development and launch of next-gen recommendation engine enhancements (e.g., smarter detection of idle/over-provisioned resources).
• Evolve CloudKeeper’s industry-leading Guaranteed Savings model and its underlying pricing, automation, and governance engines
• Design conversational, AI-powered experiences that guide engineers through optimization opportunities, troubleshooting, and architectural decisions
• Define and refine metrics around savings impact, recommendation adoption, user engagement, churn, and product-market fit.
• Explore spaces like multi-cloud optimization, FinOps governance frameworks, cloud budgeting & forecasting, or cloud-native developer tools.
• Identify gaps in the cloud management ecosystem and work with leadership to incubate entirely new product lines, from concept to MVP to full-scale launch

What We Offer

• The opportunity to own a high-impact product in the rapidly growing FinOps/cloud cost optimisation space.
• A collaborative, innovative environment with talented teams in engineering, data science, UX, and product.
• The chance to make a measurable difference: help customers reduce cloud cost while maintaining performance and accelerate their cloud usage optimisation journey.