Full-Time

Director – AI and ML

Updated on 11/5/2024

Spring Health

Spring Health

1,001-5,000 employees

Personalized mental health solutions for employers

Consumer Software
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 provides personalized mental health solutions aimed at improving employee well-being for organizations and health plans. Their approach, known as Precision Mental Healthcare, involves assessing individuals to determine the most appropriate mental health support, which can include digital resources, therapy, and medication. The platform is user-friendly, allowing users to complete a brief assessment that generates a personalized care plan and connects them with suitable providers. Key features include appointment scheduling, on-demand wellness exercises, and access to a Care Navigator for ongoing support. Unlike competitors, Spring Health focuses on tailoring mental health services to the specific needs of each individual, ensuring a more effective and supportive experience. The company's goal is to enhance mental health accessibility and effectiveness for employees through comprehensive support systems.

Company Stage

Series D

Total Funding

$366.7M

Headquarters

New York City, null

Founded

2016

Growth & Insights
Headcount

6 month growth

16%

1 year growth

45%

2 year growth

116%
Simplify Jobs

Simplify's Take

What believers are saying

  • Collaborations with major health plans like Highmark Health expand access points and enhance service offerings, indicating strong growth potential.
  • The launch of innovative tools like Atlas and Sage demonstrates Spring Health's commitment to leveraging technology for better mental health outcomes.
  • High-profile partnerships with companies like General Mills and LinkedIn validate the platform's effectiveness and market acceptance.

What critics are saying

  • The highly competitive mental health sector requires continuous innovation to maintain a competitive edge.
  • Integration of new services and partnerships, such as with Eleanor Health, may pose operational challenges and strain resources.

What makes Spring Health unique

  • Spring Health's Precision Mental Healthcare system offers highly personalized mental health support, setting it apart from more generalized solutions.
  • The introduction of Atlas, a recommendation engine for workplace mental health, provides data-driven insights and action plans, enhancing the value proposition for HR and benefits leaders.
  • Their comprehensive approach, including partnerships like the one with Eleanor Health for substance use disorder services, ensures a full spectrum of mental health support.

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Benefits

Retirement benefits

Paid time off

Healthcare benefits

Insurance benefits

Work-life benefits

Mental health benefits