Applied AI Manager

Inspiren

9d•$200,000 - $235,000•Remote

About The Position

Machine Learning and Computer Vision is how we at Inspiren turn raw data from our ecosystem of smart devices into valuable insights about residents and their health/safety as well as care staff. It is core to what we do as a company. We are seeking a seasoned Applied AI Manager (Computer Vision, LLMs) to play a critical role in scaling our Machine Learning organization and evolving our core ML platform. You will lead a team of talented engineers to design, develop, and deploy complex machine learning solutions that drive critical business outcomes. You will be a key technical leader, collaborating with cross-functional partners (Data Science, Product, Engineering, Analytics) to create scalable systems and deliver high-impact projects. You will also play a key role in continuing to build out the team, growing and upleveling engineers, and contributing to a culture of technical excellence and innovation.

Requirements

8+ years of professional experience in machine learning, software engineering, or a similar domain
5+ years with machine learning algorithms, model development, and model deployment
3+ years in managing machine learning and computer vision teams
Proven experience shipping ML systems into production and operating them at scale.
Demonstrated ownership of model lifecycle: data, training, evaluation, deployment, monitoring, and iteration.
Experience applying multimodal or GenAI techniques in real products.
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 machine learning projects to business outcomes.
Proven ability to operate under ambiguity, prioritize effectively, and maintain momentum in a fast-moving environment.

Nice To Haves

Experience with on-device or edge computer vision.
Experience with video/image processing on device.
Familiarity with Networking, Cloud Uploading, and WiFi constraints.
Experience in health-tech or regulated environments.
Experience in growth-stage startups.

Responsibilities

Lead ML engineering execution
Own technical direction for ML systems across computer vision and multimodal/GenAI use cases.
Design and develop advanced algorithms to address complex business challenges.
Research and implement cutting-edge machine learning models and techniques.
Prototype new models and evaluate their performance through simulation.
Optimize machine learning models to achieve faster speed and greater efficiency.
Implement feature selection and engineering techniques to boost model performance.
Evaluate machine learning models to ensure they deliver accurate and relevant results.
Set clear success criteria for models and systems, then 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 ML 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.
Contribute to company strategy at the intersection of ML, devices, and care outcomes.