Full-Time

Director – AI and ML

Confirmed live in the last 24 hours

Spring Health

Spring Health

1,001-5,000 employees

Personalized mental health solutions for employers

Healthcare

Compensation Overview

$200.8k - $245kAnnually

Senior, Expert

Remote in USA

Category
Applied Machine Learning
AI Research
AI & Machine Learning
Required Skills
Kubernetes
Microsoft Azure
Data Science
Tensorflow
Pytorch
AWS
Google Cloud Platform
Requirements
  • 7+ years of experience in building and leading machine learning, data science, or AI teams, with a track record of delivering successful AI-driven solutions.
  • Strong knowledge of machine learning frameworks, AI technologies, and modern data engineering tools. Experience with platforms like TensorFlow, PyTorch, Kubernetes, and cloud platforms such as AWS, GCP, or Azure.
  • Proven experience in architecting and deploying scalable ML platforms, building data pipelines, and managing infrastructure for AI/ML solutions.
  • Ability to bridge the gap between AI/ML capabilities and business goals, ensuring the technology meets the needs of the product teams and the broader business.
  • Strong leadership and management experience, with the ability to manage, coach, and develop high-performing teams.
  • Demonstrated ability to collaborate across technical and non-technical teams, fostering partnerships to deliver AI solutions that solve real-world problems.
  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
  • Excellent written and verbal communication skills, with the ability to explain complex AI concepts to stakeholders at all levels.
  • Experience in healthcare or mental health technology is not required but preferred.
Responsibilities
  • Design, architect, and build a robust, scalable machine learning platform that will be the foundation for AI-powered solutions across the company.
  • Ensure the platform is user-friendly, modular, and efficient, allowing various product teams to easily leverage AI and ML technologies.
  • Lead efforts to create data products that transform raw data into actionable insights for teams across the company.
  • Influence the data engineering team to ensure data pipelines are optimized for scalability and accuracy, supporting the rapid deployment of AI solutions.
  • Manage and mentor a team of machine learning engineers and data scientists, fostering a culture of collaboration, innovation, and continuous learning.
  • Set clear goals and expectations, ensuring teams are aligned with the company’s AI strategy and product roadmap.
  • Partner with leadership and product teams to understand business needs and prioritize AI and ML initiatives that drive value for the organization.
  • Work with your Data Products Product Management peer to define a clear AI/ML strategy, aligning technical capabilities with business objectives.
  • Ensure the AI platform is designed with scalability, security, and robustness in mind.
  • Partner with DevOps and IT teams to ensure the platform is integrated with broader company infrastructure and supports CI/CD pipelines for ML models.
  • Keep the organization at the forefront of AI innovation by adopting and implementing best practices, staying up-to-date with the latest advancements in AI and machine learning technologies.
  • Promote a culture of experimentation, testing new ideas and approaches to continuously improve AI-driven products.
  • Collaborate with product managers, software engineers, and business stakeholders to ensure the successful integration of AI/ML technologies into products and services.
  • Act as the subject-matter expert on AI and ML platforms, providing guidance and support to product teams on how to leverage these technologies effectively.
  • Track platform performance, data product success, and model accuracy, using metrics to drive continuous improvement.
  • Implement feedback loops to refine AI models and ensure they meet or exceed business expectations.
  • Build out a data quality framework to ensure model accuracy over time.

Spring Health offers personalized mental health solutions to employers and health plans, focusing on enhancing employee well-being. Their Precision Mental Healthcare system assesses individuals to provide tailored support, including digital resources, therapy, and medication. The platform is user-friendly, allowing users to receive personalized care plans and schedule appointments with providers easily. Spring Health aims to deliver effective mental health support that meets the unique needs of each individual.

Company Stage

Series E

Total Funding

$452.3M

Headquarters

New York City, null

Founded

2016

Growth & Insights
Headcount

6 month growth

14%

1 year growth

39%

2 year growth

103%
Simplify Jobs

Simplify's Take

What believers are saying

  • Spring Health raised $100M in Series E funding, valuing it at $3.3 billion.
  • Partnerships with major brands like Microsoft and Target enhance market reach.
  • The launch of Community Care addresses mental health equity and social determinants.

What critics are saying

  • Increased competition from startups may dilute Spring Health's market share.
  • Rapid AI advancements could outpace Spring Health's current technological capabilities.
  • Economic downturns might reduce budgets for employer-sponsored mental health programs.

What makes Spring Health unique

  • Spring Health offers Precision Mental Healthcare for personalized mental health solutions.
  • The company is the first to earn nationwide third-party accreditation for clinical care.
  • Spring Health's Atlas platform optimizes mental health programs for HR and benefits leaders.

Help us improve and share your feedback! Did you find this helpful?

Benefits

Retirement benefits

Paid time off

Healthcare benefits

Insurance benefits

Work-life benefits

Mental health benefits