MLOps Engineer

Job not on LinkedIn

đŸ”„ 0 minutes ago

🇼🇳 India – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

đŸ€– Machine Learning Engineer

đŸ‘» Ghost score 21%

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Logo of Saaf Finance

Saaf Finance

11 - 50 employees

Founded 2022

💳 Fintech

đŸ€– Artificial Intelligence

☁ SaaS

Fintech ‱ Artificial Intelligence ‱ SaaS

Saaf Finance is an AI-driven underwriting platform for mortgage lenders. Saaf’s AI Underwriter automates mortgage underwriting across products such as Non-QM, RTL, HELOC, DSCR, Jumbo, and Bank Statement loans, using OCR, large language models, and API integrations with data vendors and loan origination systems (e. g. , Encompass, MeridianLink). The platform produces structured “Source of Truth” loan data, reduces fraud risk through direct data connections, and claims substantial operational gains (faster processing, lower cost, and greater scalability). Saaf positions itself as a B2B partner to mortgage operations and secondary market participants, leveraging a training set of 200K+ loans and decades of industry experience to augment underwriters rather than replace them.

📋 Description

‱ Own the infrastructure supporting production AI systems ‱ Re-architect AI services from single-host deployments to horizontally scalable, orchestrated infrastructure ‱ Design infrastructure for LLM workloads with long-running requests, streaming responses, bursty concurrency, expensive downstream calls, and upstream rate limits ‱ Own capacity, autoscaling, and unit economics ‱ Build development-to-pre-production-to-production promotion paths with consistent, reproducible environments ‱ Version-control and make infrastructure, configuration, and application logic reviewable ‱ Build CI/CD with fast deployment, rollback, staged rollout, and auditable change history ‱ Build self-serve tooling for engineers and technically minded teammates to define, modify, and test AI workflow logic ‱ Design validation, versioning, review, staged promotion, and recovery guardrails ‱ Instrument the AI stack for latency, throughput, failure modes, cost, and output quality ‱ Build meaningful alerting and incident practices that improve the system ‱ Own secrets, access control, and environment isolation in a regulated industry

🎯 Requirements

‱ Production infrastructure ownership: deployed and operated containerized services in production under real traffic, including rollouts, autoscaling, failure isolation, resource limits, and rollback ‱ Infrastructure as code; declarative and reproducible environments ‱ CI/CD experience including automated testing, environment promotion, safe rollout, and fast recovery ‱ Strong Python; ability to read and change application code, profile it, and fix it ‱ Operational judgment across application, network, and infrastructure boundaries ‱ End-to-end ownership of design, implementation, deployment, monitoring, and follow-up ‱ Fast, incremental iteration and risk reduction ‱ Experience operating LLM or ML workloads in production ‱ Cloud deployment experience, AWS preferred ‱ Experience in fintech, lending, insurance, or another regulated industry ‱ Experience building internal developer platforms or self-serve tooling ‱ Full-stack comfort for lightweight UIs or internal tools ‱ Experience designing multi-environment promotion pipelines ‱ Familiarity with agent orchestration frameworks ‱ Observability for non-deterministic systems ‱ Inference optimization including model serving, batching, caching, and cost reduction ‱ Exposure to workflow automation tooling and low-code builders

đŸ–ïž Benefits

‱ Competitive compensation ‱ Unlimited PTO ‱ Remote-first with flexible hours ‱ $2,000/year professional development budget ‱ Home office setup stipend

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