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Director or Manager of AI Engineering

  • Saint Petersburg, FL, United States

$175,000 to $215,000 USD / year

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Job details

Pay
$175,000 to $215,000 USD / year
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Experience
10+ years of experience in data science, machine learning, or AI engineering, including leadership responsibility for technical teams or programs.
Posting language
English
Posted

Original job description

Are you a technical leader and prior Programmer that is savvy in technical AI Engineering abilities and naturally showcase Leadership skills amongst a technical group? If so, and if you have been part of an AI Departmental Start up that required hands on coding and code review at a micro-level, as well as a tactical macro-level vision, THEN APPLY NOW. This role will require tight collaboration with the C Suite and VP Level Technical Executives and will require a residence in the Tampa Bay, FL Area for hybrid in-office/remote collaboration.

We are looking for an experienced AI/ML leader to guide the design, deployment, and evolution of enterprise-scale machine learning capabilities for a healthcare-focused organization in Saint Petersburg, Florida. This role blends strategic leadership with practical engineering oversight, making it ideal for someone who can shape long-term vision while staying close to technical execution when needed. The successful candidate will help build reliable data and machine learning solutions that improve operational performance, enable advanced analytics, and support innovation across the business.

Responsibilities:

  • Lead the AI/ML engineering function, setting technical direction for model development, deployment standards, and platform maturity across the organization.
  • Partner with data science, engineering, and business stakeholders to turn operational and analytical needs into scalable machine learning solutions.
  • Oversee the design and maintenance of end-to-end machine learning pipelines, including data ingestion, transformation, training, validation, and production monitoring.
  • Provide hands-on guidance for complex technical initiatives, stepping into architecture reviews, implementation planning, and troubleshooting when necessary.
  • Drive the use of modern big data and distributed processing technologies such as Spark, Hadoop, Kafka, and Databricks to support high-volume data workflows.
  • Establish engineering best practices for production-grade AI systems, with emphasis on reliability, performance, governance, and maintainability.
  • Direct the development and optimization of ETL processes that prepare structured and unstructured data for advanced modeling and analytics use cases.
  • Mentor and grow technical teams by fostering strong delivery habits, cross-functional collaboration, and continuous improvement in machine learning engineering.
  • Evaluate emerging tools, frameworks, and platform capabilities to strengthen the organization’s applied AI roadmap and execution model.
  • 10+ years of experience in data science, machine learning, or AI engineering, including leadership responsibility for technical teams or programs.
  • Strong proficiency in Python and experience building production-ready machine learning applications and services.
  • Deep knowledge of machine learning methods, model lifecycle management, and scalable ML pipeline design.
  • Hands-on experience with Apache Spark, Apache Hadoop, Apache Kafka, and Databricks in data-intensive environments.
  • Solid background in ETL architecture and data engineering practices that support reliable model training and deployment.
  • Demonstrated ability to balance strategic planning with tactical execution in a fast-moving technical setting.
  • Experience applying AI and machine learning within regulated or complex operational environments, preferably in healthcare or a related industry.
More about this job

Skills

  • Leadership
  • ML
  • Troubleshooting
  • Apache Spark
  • Apache Hadoop
  • Apache Kafka
  • Databricks
  • Data engineering
  • Unstructured data
  • Process improvement
  • Machine learning
  • Python
  • Strategic planning

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