AI Systems Architect

2 days ago

Edinburgh, Edinburgh, United Kingdom Unreal Gigs Full time
Job Title: AI Engineer

At Unreal Gigs, we're seeking an experienced AI Engineer to design, develop, and deploy AI models and solutions that drive business impact. This is a unique opportunity to work with a talented team of data scientists, software developers, and product teams to integrate advanced machine learning models into products and services.

Key Responsibilities:

  • Develop and Deploy AI Models: Design, build, and deploy machine learning and AI models, including supervised and unsupervised learning techniques, using frameworks like TensorFlow, PyTorch, or Scikit-learn.
  • Data Processing and Feature Engineering: Collaborate with data engineers and scientists to collect, preprocess, and transform large datasets for model training, ensuring data pipelines are optimized for AI workflows and support the development of high-performance models.
  • Optimize Model Performance: Experiment with different model architectures, algorithms, and hyperparameters to improve accuracy, speed, and scalability, applying techniques like cross-validation, regularization, and gradient boosting to fine-tune models and ensure they perform well in production.
  • Deploy Models into Production: Work with DevOps and software engineering teams to deploy AI models into production environments, ensuring they are scalable, efficient, and integrated with other systems, building APIs and services that make your models accessible for real-time applications.
  • Monitor and Retrain AI Models: Continuously monitor the performance of deployed models, detecting model drift and updating models as necessary, retraining models with new data to keep them accurate and relevant in changing environments.
  • Collaborate with Cross-Functional Teams: Work closely with product managers, engineers, and other stakeholders to understand business needs and translate them into AI solutions, ensuring that AI models align with product goals and deliver measurable business outcomes.
  • Stay Up-to-Date with AI Research and Trends: Keep current with the latest advancements in machine learning, AI algorithms, and frameworks, experimenting with new technologies and bringing innovative approaches to solving AI challenges within the organization.

Requirements:

  • AI and Machine Learning Expertise: Deep understanding of machine learning algorithms, such as decision trees, neural networks, clustering, and reinforcement learning, with experience in developing models for NLP, computer vision, and predictive analytics.
  • Programming and AI Tools: Proficiency in programming languages like Python or R, and experience using machine learning frameworks such as TensorFlow, PyTorch, Keras, and Scikit-learn, with a strong coding and debugging background in AI solutions.
  • Data Engineering and Feature Engineering: Hands-on experience with data preprocessing, feature selection, and engineering for AI models, with the ability to clean and transform large datasets to support machine learning workflows.
  • Deployment and Integration: Experience deploying AI models into production environments using cloud platforms (AWS, GCP, Azure) and containerization tools like Docker and Kubernetes, with the ability to integrate models into existing systems and optimize for scalability.
  • Collaboration and Communication: Strong collaboration skills, with the ability to work with cross-functional teams, including data scientists, engineers, and product managers, with clear communication skills to convey technical concepts to non-technical stakeholders.

Education and Experience:

  • Educational Requirements: Bachelor's or Master's degree in Computer Science, Data Science, AI, Machine Learning, or a related field, with equivalent experience in AI development highly valued.
  • Experience Requirements: 3+ years of experience in AI engineering or machine learning, with hands-on experience developing and deploying AI models in real-world applications, a proven track record of working with large datasets, designing machine learning pipelines, and delivering AI-driven solutions that solve business problems.

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