10 Sep
|
Matilda Cloud
|
Hyderabad
10 Sep
Matilda Cloud
Hyderabad
Job Description
Title: Ai/ML Engineer
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Location: Hyderabad / Bangalore
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About the role
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You'll build the AI and machine learning systems that power Matilda Cloud's intelligent cloud cost optimization, policy management, and recommendation engine. This means shipping production agentic workflows, RAG pipelines, fine-tuned models, and ML services — all running across AWS, Azure, GCP, and OCI at enterprise scale.
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What you'll work on
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- Migrate cloud pricing and policy APIs to agentic AI architectures using LangGraph and MCP
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- Build RAG pipelines for AI-generated cost allocation and capacity reports
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- Design and execute the distillation pipeline: teacher data capture (Claude/Bedrock) → SFT/DPO training → Qwen student model
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- Build the cloud cost forecasting engine and anomaly detection service (Prometheus + time-series ML)
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- Instrument LLMOps observability: tracing, cost monitoring, groundedness evals (LangSmith)
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- Expose Matilda's cloud discovery data as MCP tool surfaces for agentic consumption
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Must have
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- 4+ years of software engineering with Python as primary language
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- Hands-on with LLM APIs — AWS Bedrock, OpenAI,
or Anthropic — including function calling and structured outputs
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- Built at least one production RAG pipeline (chunking, vector DB, hybrid retrieval)
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- LangChain or LangGraph experience — agent loops, tool use, state management
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- Solid cloud experience on at least two of: AWS, Azure, GCP, OCI — specifically AI/ML services (Bedrock, SageMaker, Azure ML, Vertex AI)
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- Kubernetes for deploying and scaling ML services
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- Experience with ML data pipelines — feature engineering, ETL for training data
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- Time-series analysis or anomaly detection in a production setting
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Nice to have
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- MCP (Model Context Protocol) — building or consuming MCP servers
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- LLM fine-tuning: SFT dataset construction, DPO, or LoRA/QLoRA
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- Model distillation — teacher/student patterns
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- LangSmith or equivalent LLMOps observability platform
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- FinOps / cloud cost domain knowledge (a big plus given our product)
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- Experience with LiteLLM, model routers, or multi-provider LLM setups
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