Job Description
About Inspiren
Inspiren offers the most complete and connected ecosystem in senior living. Founded by Michael Wang a former Green Beret turned cardiothoracic nurse Inspiren proves that compassionate care and technology can coexist - bringing peace of mind to residents families and staff.
Our integrated solutions seamlessly fit into existing workflows capturing everything happening within a community. Backed by nurse specialists and powerful analytics we provide the data operators need to make informed clinical and operational decisions - driving efficiency profitability and better care outcomes.
About the Role
Data and Machine Learning are at the heart of what we do at Inspiren. Our ecosystem of smart multi-sensor devices produces an enormous volume of raw timestream data across many modalities — and our ML systems are what turn that raw signal into valuable real-time insights about residents their health and safety and care staff (including time-critical notifications for events like falls). We are seeking a seasoned Senior Manager to lead our Data + ML Platform group and evolve the core platform that powers all of this. You will lead a team of Data Engineers Data Platform Engineers and ML Ops Engineers to build the foundation that lets our ML engineers move from idea to production quickly and reliably as well as the foundational data layer for internal company analytics and external data products. You will be a key technical leader collaborating with cross-functional partners (Data Science Product Engineering Hardware Analytics) to design scalable systems modernize legacy infrastructure and lay the groundwork for the next generation of multimodal and LLM/VLM-powered capabilities. You will also play a key role in scaling the team growing and upleveling engineers and contributing to a culture of technical excellence and innovation.
What You'll Own
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.
Build and scale the team
- 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.
Partner cross-functionally
- 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.
What You Bring
- 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.
Details
- The annual salary for this role is $200000 - 230000 + equity + benefits (including medical dental and vision)
- Flexible PTO
- Location: Remote US or Canada.
- Qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender perception or identity national origin age marital status protected veteran status or disability status.
Skills Required
- 8+ years professional experience in software or ML engineering with significant data/ML infrastructure/platform experience
- 3+ years managing ML Data Engineering or platform engineering teams
- Proven experience building or scaling MLOps capabilities (model registry feature stores deployment/serving drift monitoring experiment tracking)
- Experience building data platforms or data engineering systems at scale (streaming or large-scale batch pipelines)
- Proven experience shipping and operating data and ML systems in production at scale
- Ownership of 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 to convey complex ideas to cross-functional audiences
- Ability to operate under ambiguity prioritize effectively and maintain momentum in a fast-moving environment
What We Do
Inspiren offers the most complete and connected ecosystem in senior living. Founded by Michael Wang a former Green Beret turned cardiothoracic nurse Inspiren proves that compassionate care and technology can coexist - bringing peace of mind to residents families and staff.Our integrated solutions seamlessly fit into existing workflows capturing everything happening within a community. Backed by nurse specialists and powerful analytics we provide the data operators need to make informed clinical and operational decisions - driving efficiency profitability and better care outcomes.
Why Work With Us
Customers describe working with us as a partnership not a vendor relationship. We send people on-site to train. We listen to what customers need and put it on the roadmap. That's the culture internally too — high ownership high accountability and genuinely caring about outcomes for residents.
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Inspiren Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
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Date Posted
06/30/2026
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