AI Engineer (Machine Learning & Computer Vision)

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.