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AI Engineer (Machine Learning & Computer Vision)

In Technology Group
Leeds
4 months ago
Applications closed

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Lead Machine Learning and AI Engineer

Senior Data Scientist / AI Engineer

Job Title: AI Engineer (Machine Learning & Computer Vision)

Location: Leeds (3 Days a Week)

Salary: £60,000 - £80,000 + Benefits


About Us:

The Client, based in Leeds,have just received their Series A funding, is at the forefront of AI innovation, building cutting-edge solutions that harness the power of artificial intelligence, machine learning, and computer vision. Our team is dedicated to solving complex problems and delivering intelligent systems that drive real-world impact. We are seeking a skilled AI Engineer to help us push the boundaries of what's possible.


Responsibilities:


  • Design, develop, and deploy machine learning models, with a strong focus on computer vision applications.
  • Implement deep learning architectures using frameworks such as TensorFlow, PyTorch, or Keras.
  • Develop and optimize image processing and vision-based AI algorithms for object detection, segmentation, and classification.
  • Work with large-scale datasets, including data preprocessing, augmentation, and annotation.
  • Build and deploy AI models into production using cloud-based services (AWS, Azure, GCP) or edge computing platforms.
  • Improve model performance through hyperparameter tuning, transfer learning, and advanced optimization techniques.
  • Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to integrate AI models into applications.
  • Stay up to date with the latest AI research, trends, and emerging technologies in computer vision and deep learning.
  • Develop scalable APIs and integrate AI solutions with existing infrastructure.


Technical Skills:


  • Expertise in Python, C++, or Java for AI/ML development.
  • Proficiency in ML frameworks and libraries such as TensorFlow, PyTorch, OpenCV, Scikit-learn, and ONNX.
  • Experience with cloud platforms (AWS, Azure, GCP) for AI model deployment and scaling.
  • Strong understanding of neural networks, deep learning architectures, and computer vision techniques.
  • Knowledge of real-time AI inference and edge computing optimization.
  • Experience with AI pipeline automation, version control, and CI/CD integration.
  • Familiarity with data engineering tools such as Apache Spark, Hadoop, or SQL for large-scale data processing.
  • Proficiency in using Git, Docker, and Kubernetes for deployment and collaboration.


Required Qualifications:


  • Bachelor’s, Master’s, or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
  • Strong proficiency in Python and experience with ML libraries/frameworks (TensorFlow, PyTorch, OpenCV, Scikit-learn).
  • Experience with computer vision techniques such as image classification, object detection (YOLO, Faster R-CNN), image segmentation, and OCR.
  • Knowledge of deep learning architectures, including CNNs, RNNs, and transformers.
  • Experience working with large-scale datasets, data augmentation, and feature extraction techniques.
  • Proficiency in cloud computing services for AI/ML deployment (AWS SageMaker, Azure ML, GCP AI).
  • Familiarity with MLOps practices, including model versioning, deployment, and monitoring.
  • Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.


Preferred Qualifications:


  • Experience with edge AI deployment (NVIDIA Jetson, TensorRT, OpenVINO, or Coral Edge TPU).
  • Hands-on experience with reinforcement learning or generative AI models.
  • Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
  • Experience with automated ML pipelines and tools like Kubeflow or MLflow.
  • Contributions to open-source AI/ML projects or research publications in AI conferences.


What We Offer:


  • Competitive salary and equity options.
  • Opportunities to work on cutting-edge AI technologies and impactful projects.
  • A collaborative, innovation-driven work environment.
  • Flexible work arrangements and remote work options.
  • Continuous learning and professional development support.


Desirable Benefits:

  • Health, dental, and vision insurance
  • Flexy days off (upto 40)
  • Generous paid time off, including vacation and sick leave.
  • Stock options and performance-based bonuses.
  • Relocation assistance for eligible candidates.
  • Access to state-of-the-art AI research labs and computing resources.
  • Sponsored attendance at AI/ML conferences and workshops.

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