Manager, ML Engineering

Team Leadership & People Management

Lead, mentor and grow a team of 4 ML Engineers and 1 Delivery Engineer across India and the UK.

Run effective 1:1s, performance conversations, and career development planning.

Foster a high-trust, high-performance team culture grounded in continuous improvement.

Manage hiring, onboarding, and team capacity planning as Cortex expands.

Technical Delivery & Model Operations

Own end-to-end delivery of Cortex initiatives — from planning and scoping to production release and post-go-live operational support.

Drive delivery of new capabilities including Audio Analytics as a Service, In App Translation and Intelligent Agent Review.

Work closely with the Applied ML team to take in-house models from research handoff through to production-grade deployment — managing integration, validation, and operational readiness.

Own and evolve Cortex's gated model deployment pipeline: ensuring models progress through automated quality gates, shadow mode, canary, and full rollout stages with clear promotion and rollback criteria.

Establish model evaluation and monitoring frameworks — tracking quality, performance drift, and SLO compliance in production.

Maintain and improve Cortex's operational SLOs, reliability posture, and incident response process.

Ensure engineering practices, code quality, and architectural decisions meet Smarsh engineering standards.

AI-First Ways of Working

Actively use and champion AI productivity tooling: Windsurf, Claude Code, and similar tools.

Set the standard for how the team leverages AI-assisted development to increase velocity and code quality.

Identify and help to introduce new AI tooling where it adds measurable value to the team.

Technical Strategy, Stakeholder Management & Developer Experience

Contribute to the Cortex technical roadmap, working with engineering leadership, Product Management, and TPM to align delivery to business priorities.

Build strong working relationships with the Applied Machine Learning team — acting as a bridge between model development and production AI service deployment.

Partner closely with sister Cognition teams — Cognition Logic and Cognition Analytics — to align on shared platform patterns, APIs, and service contracts within the Enterprise Conduct organisation.

Engage proactively with the Fabric organisation on infrastructure, platform standards, and shared tooling dependencies.

Represent Cortex in cross-team forums, architecture reviews, and planning sessions — advocating for Cortex consumers' developer experience.

Help to drive the AI Service Catalogue vision: discoverable, well-documented, and operationally excellent services that product engineers across Smarsh can consume with confidence.