Company
Job location: Leeds, UK
Posted: 2d ago
Job details
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:
1. Design, develop, and deploy machine learning models, with a strong focus on computer vision applications.
2. Implement deep learning architectures using frameworks such as TensorFlow, PyTorch, or Keras.
3. Develop and optimize image processing and vision-based AI algorithms for object detection, segmentation, and classification.
4. Work with large-scale datasets, including data preprocessing, augmentation, and annotation.
5. Build and deploy AI models into production using cloud-based services (AWS, Azure, GCP) or edge computing platforms.
6. Improve model performance through hyperparameter tuning, transfer learning, and advanced optimization techniques.
7. Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to integrate AI models into applications.
8. Stay up to date with the latest AI research, trends, and emerging technologies in computer vision and deep learning.
9. Develop scalable APIs and integrate AI solutions with existing infrastructure.
Technical Skills:
1. Expertise in Python, C++, or Java for AI/ML development.
2. Proficiency in ML frameworks and libraries such as TensorFlow, PyTorch, OpenCV, Scikit-learn, and ONNX.
3. Experience with cloud platforms (AWS, Azure, GCP) for AI model deployment and scaling.
4. Strong understanding of neural networks, deep learning architectures, and computer vision techniques.
5. Knowledge of real-time AI inference and edge computing optimization.
6. Experience with AI pipeline automation, version control, and CI/CD integration.
7. Familiarity with data engineering tools such as Apache Spark, Hadoop, or SQL for large-scale data processing.
8. Proficiency in using Git, Docker, and Kubernetes for deployment and collaboration.
Required Qualifications:
1. Bachelor’s, Master’s, or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
2. Strong proficiency in Python and experience with ML libraries/frameworks (TensorFlow, PyTorch, OpenCV, Scikit-learn).
3. Experience with computer vision techniques such as image classification, object detection (YOLO, Faster R-CNN), image segmentation, and OCR.
4. Knowledge of deep learning architectures, including CNNs, RNNs, and transformers.
5. Experience working with large-scale datasets, data augmentation, and feature extraction techniques.
6. Proficiency in cloud computing services for AI/ML deployment (AWS SageMaker, Azure ML, GCP AI).
7. Familiarity with MLOps practices, including model versioning, deployment, and monitoring.
8. Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.
Preferred Qualifications:
1. Experience with edge AI deployment (NVIDIA Jetson, TensorRT, OpenVINO, or Coral Edge TPU).
2. Hands-on experience with reinforcement learning or generative AI models.
3. Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
4. Experience with automated ML pipelines and tools like Kubeflow or MLflow.
5. Contributions to open-source AI/ML projects or research publications in AI conferences.
What We Offer:
1. Competitive salary and equity options.
2. Opportunities to work on cutting-edge AI technologies and impactful projects.
3. A collaborative, innovation-driven work environment.
4. Flexible work arrangements and remote work options.
5. Continuous learning and professional development support.
Desirable Benefits:
1. Health, dental, and vision insurance.
2. Flexy days off (up to 40).
3. Generous paid time off, including vacation and sick leave.
4. Stock options and performance-based bonuses.
5. Relocation assistance for eligible candidates.
6. Access to state-of-the-art AI research labs and computing resources.
7. Sponsored attendance at AI/ML conferences and workshops.
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