Manager, Data/ML Platform

🔥 13 hours ago

🗽 New York – Remote

🗽 New York – Remote

💵 $200k - $230k / year

⏰ Full Time

🟠 Senior

🔴 Lead

🚰 Data Engineer

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Inspiren

WebsiteLinkedInAll Job Openings

1 - 10 employees

⚕️ Healthcare Insurance

☁️ SaaS

🧘 Wellness

💰 $2.7M Venture Round on 2022-10

Healthcare Insurance • SaaS • Wellness

Inspiren is a comprehensive solution for managing and optimizing operations in senior living communities. The platform enhances resident care by providing decision-grade data analysis for care planning, staffing optimization, and resident safety. Inspiren uses advanced technology, such as AUGi, to enable proactive care, improve workflow efficiency, and align care plans with resident needs. The technology's capabilities include real-time alerts for incidents and early risk flagging, tracking resident interactions, and monitoring staff effectiveness, thus ensuring high-quality resident care and operational efficiency.

📋 Description

• Lead Data + ML Platform strategy and execution • Own technical direction for the data and ML platform, spanning data engineering, data platform, and ML Ops. • Invest in ML Ops capabilities that accelerate ML enablement: offline experimentation, model registry, shadow deployments and testing, drift/product monitoring, online and offline feature stores, and training data management. • Build measurement and experimentation frameworks for LLM and agentic workflows. • Invest in data platform and data engineering capabilities to handle large-scale streaming and batch data across modalities. • Modularize and scale our system, increase reliability, and modernize legacy infrastructure. • Make it easy for ML engineers to have ideas, test them, shadow deploy, gather data, test online, and ship. • Set clear success criteria for platform capabilities and hold the team accountable to outcomes. • Anticipate skill gaps and build a deliberate hiring plan; consistently attract and retain strong data and ML platform engineers. • Coach with depth: set explicit expectations, give direct feedback, and accelerate individual growth. • Build an environment of ownership, trust, and continuous learning. • Develop future leaders and create succession within the team. • Work closely with Product, Hardware, Data Science, and Analytics to shape problem definition and roadmap. • Translate ambiguous business needs into concrete technical direction. • Influence hardware and device design decisions where they intersect with data and ML needs. • Contribute to company strategy at the intersection of data, ML, devices, and care outcomes.

🎯 Requirements

• 8+ years of professional experience in software or ML engineering, with significant time spent on data/ML infrastructure or platforms. • 3+ years managing ML, Data Engineering, or platform engineering teams. • Proven experience building or scaling MLOps capabilities (e.g., model registry, feature stores, deployment/serving, drift monitoring, experiment tracking). • Experience building data platforms / data engineering systems at scale (streaming or large-scale batch pipelines). • Proven experience shipping and operating data and ML systems in production at scale. • Demonstrated ownership of the model lifecycle infrastructure: data, training, evaluation, deployment, monitoring, and iteration. • Demonstrated ability to grow people, uplevel teams, and manage performance with clear expectations and direct feedback. • Experience driving alignment and execution across Product, Engineering, and Data, with accountability for outcomes. • Excellent verbal and written communication skills, with the ability to convey complex ideas clearly to cross-functional audiences and connect platform work to business outcomes. • Proven ability to operate under ambiguity, prioritize effectively, and maintain momentum in a fast-moving environment.

🏖️ Benefits

• medical • dental • vision • Flexible PTO