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Director, Fleet AI Engineering

LinkedIn Hertz Atlanta, GA
Not Applicable Posted March 14, 2026 Job link
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Requirements
  • 12+ years of progressive experience in software or AI/ML engineering, with at least 5+ years in a leadership role managing and scaling engineering teams (preferably 10+ engineers).
  • Proven track record of successfully leading the design, development, and deployment of complex, production-grade AI/ML solutions.
  • Technical Skills:
  • Machine Learning Expertise: Deep understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning), deep learning architectures, and natural language processing (NLP).
  • Programming Proficiency: Expert-level proficiency in Python and relevant ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
  • MLOps & DevOps: Extensive experience with MLOps practices, including CI/CD pipelines for ML models, model versioning, monitoring, automated retraining, and experiment tracking.
  • Cloud Platforms: Hands-on experience with major cloud AI platforms (e.g., AWS SageMaker, Azure ML, Google Cloud AI Platform) and their associated services.
  • Data Engineering: Strong understanding of data processing technologies, large-scale data pipelines, relational and NoSQL databases, and data warehousing concepts.
  • System Architecture: Demonstrated ability to design scalable, fault-tolerant, and high-performance distributed systems for AI workloads.
  • Generative AI: Experience with Generative AI models, large language models (LLMs), prompt engineering, and fine-tuning techniques is highly desirable.
  • Strategic Thinking: Ability to translate complex business problems into actionable AI strategies and technical roadmaps.
  • Exceptional Communication: Superior verbal and written communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders, including executive leadership.
  • Leadership & Mentorship: Demonstrated ability to inspire, motivate, and develop high-performing engineering teams.
  • Strong coaching and feedback skills.
  • Problem-Solving: Excellent analytical and problem-solving abilities, with a pragmatic approach to delivering solutions in a fast-paced, evolving environment.
  • Collaboration: Proven ability to foster strong cross-functional relationships and drive alignment across diverse teams.
  • Adaptability & Agility: Comfortable navigating ambiguity and adapting to rapidly changing priorities and technologies within the AI landscape.
Preferred Skills
  • Programming Proficiency: Expert-level proficiency in Python and relevant ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
  • MLOps & DevOps: Extensive experience with MLOps practices, including CI/CD pipelines for ML models, model versioning, monitoring, automated retraining, and experiment tracking.
  • Cloud Platforms: Hands-on experience with major cloud AI platforms (e.g., AWS SageMaker, Azure ML, Google Cloud AI Platform) and their associated services.
  • Generative AI: Experience with Generative AI models, large language models (LLMs), prompt engineering, and fine-tuning techniques is highly desirable.
Education
  • (Not required) – Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. (Ph.D. preferred).