Inito
Principal Machine Learning Engineer
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Bengaluru, Karnataka, India
Work mode:
Onsite
Published on:
8 September 2026
What they need
Role Overview
We are seeking a Principal Machine Learning Engineer to lead ML system architecture, enforce technical standards, and ensure controlled, audit-ready AI development. This role operates across ML design, regulatory alignment, and risk-aware SDLC , ensuring models are scalable, explainable, and defensible.
Key Responsibilities
ML Architecture & Technical Leadership
- Define reference ML architectures for training, inference, and monitoring
- Lead Next-Generation (NG) Models lifecycle (Quantification + Cycle Tracking + App)
- Drive optimal algorithm design and system scalability
- Enforce separation of deterministic logic vs ML components
- Standardize patterns for features, datasets, and evaluations
- Maintain the ML technical roadmap
- Review system and model designs across teams
QMS & Regulatory Alignment
- Translate product claims into ML requirements
- Maintain end-to-end traceability (Requirement Model Dataset Validation Release)
- Identify algorithmic risks and mitigations
- Contribute to SRS, RMF, and V&V artifacts
- Act as technical SME during audits
AI & Software Lifecycle (Controlled SDLC)
- Drive requirements-driven ML development
- Enforce versioning of code, models, and datasets
- Define verification vs validation triggers
- Establish release gates and rollback strategies
- Integrate post-market monitoring & model drift learnings
Requirements
- Strong experience in ML system design & architecture
- 8-12 years of experience required.
- Proven expertise in production-grade ML lifecycle
- Deep understanding of scalable and explainable ML systems
- Experience with controlled SDLC / risk-aware development
- Exposure to regulated / quality-driven environments preferred
What We re Looking For
We re looking for a system-level ML leader who can:
- Provide technical direction and architectural clarity
- Balance accuracy, latency, cost, and reliability
- Reduce algorithmic and regulatory risk
- Build traceable, defensible ML systems
- Clearly justify model behavior, decisions, and safety
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
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