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AI Engineer

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Onsite

AI Engineer

Flexjet

AI Engineer

Skills

Google Cloud PlatformSQL QueriesBig DataDeep LearningDockerPythonData ScienceJavaMicroservicesNumPypandasPyTorchTensorFlowMachine LearningAIAWSKubernetesNLP / Natural Language ProcessingHadoopAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Cleveland, OH, USA

Work mode:

Onsite

Published on:

18 September 2026

What they need


Position Summary Flexjet is seeking a skilled and innovative AI Engineer to design, develop, and deploy machine learning and artificial intelligence solutions. You will work closely with data scientists, software engineers, and product teams to build scalable AI systems that drive business value and enhance user experiences.

Duties & Responsibilities

  • Design and develop machine learning and deep learning models for real-world applications
  • Build, test, and deploy AI/ML pipelines in production environments
  • Collaborate with cross-functional teams to translate business needs into AI solutions
  • Optimize model performance, scalability, and reliability
  • Work with large datasets: preprocessing, feature engineering, and data validation
  • Implement APIs and integrate AI models into existing systems
  • Monitor model performance and retrain as needed
  • Stay up to date with the latest advancements in AI and machine learning

Required Skills & Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field
  • Strong programming skills in Python (and/or Java, C++)
  • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
  • Solid understanding of algorithms, data structures, and software engineering principles
  • Experience with data processing tools (e.g., Pandas, NumPy, SQL)
  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud)
  • Knowledge of RESTful APIs and microservices architecture

Preferred Qualifications

  • Experience with NLP, computer vision, or generative AI
  • Familiarity with MLOps tools (e.g., Docker, Kubernetes, CI/CD pipelines)
  • Experience deploying models at scale in production environments
  • Knowledge of big data technologies (e.g., Spark, Hadoop)
  • Understanding of AI ethics and responsible AI practices
  • Problem-solving and analytical thinking
  • Strong communication and collaboration skills
  • Ability to work in a fast-paced, agile environment
  • Attention to detail and commitment to quality

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