About Company
Imagine a career where your AI expertise truly reshapes industries. At Career.zycto, we are an innovative technology consultancy, dedicated to delivering transformative AI solutions that drive real-world impact for our diverse client base. We cultivate a vibrant, agile culture where curiosity is celebrated, and bold ideas are encouraged. For an AI Engineer focused on model training and automation, Career.zycto offers a unique canvas to innovate, tackling complex challenges with state-of-the-art tools and collaborative teams. Grow with us as you contribute to pioneering projects, advance your skills, and make a tangible difference in the future of artificial intelligence.
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Job Description
We are seeking a highly skilled and passionate AI Engineer with a strong focus on Model Training & Automation to join our dynamic team in Camden, London. In this pivotal role, you will be instrumental in designing, developing, and deploying robust machine learning models and automated pipelines that power our innovative solutions. You will work across the entire ML lifecycle, from data preprocessing and feature engineering to model training, evaluation, optimization, and production deployment, ensuring scalability, reliability, and performance.
This position demands a deep understanding of various machine learning algorithms, model architecture design, and best practices for training large-scale models. A significant part of your responsibility will involve establishing and improving MLOps practices, including continuous integration/continuous deployment (CI/CD) for ML, automated testing, and model versioning. You will collaborate closely with data scientists, software engineers, and product managers to translate complex business requirements into tangible AI solutions, driving efficiency and intelligence across our client projects. If you thrive in a collaborative environment, are eager to push the boundaries of AI, and are committed to building maintainable, high-performance systems, we encourage you to apply. Join us in shaping the future with intelligent automation.
Key Responsibilities
- Design, develop, and implement machine learning models, focusing on efficient training strategies and performance optimization.
- Build and maintain robust MLOps pipelines for automated model training, evaluation, deployment, and monitoring.
- Collaborate with data scientists to transition research prototypes into production-ready, scalable AI systems.
- Perform data preprocessing, feature engineering, and data pipeline development to support model training.
- Ensure model quality, reliability, and ethical fairness through rigorous testing, validation, and explainability techniques.
- Implement and manage cloud-based ML infrastructure and services (e.g., AWS Sagemaker, Google AI Platform, Azure ML).
- Stay abreast of the latest advancements in AI/ML research and apply cutting-edge techniques to enhance our solutions.
- Contribute to code reviews, documentation, and the overall development best practices within the team.
- Troubleshoot and resolve issues related to model performance, data pipelines, and deployment.
- Work in a hybrid model, balancing on-site collaboration with remote work for optimal productivity and team cohesion.
Required Skills
- Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Strong experience with MLOps principles and tools (e.g., MLflow, Kubeflow, Airflow, Docker, Kubernetes).
- Demonstrable experience in building and deploying machine learning models in production environments.
- Solid understanding of data structures, algorithms, and software engineering best practices.
- Experience with cloud platforms (AWS, Azure, or GCP) for ML model development and deployment.
- Familiarity with CI/CD pipelines and version control systems (e.g., Git).
- Excellent problem-solving skills and ability to work independently as well as in a team.
- Strong communication skills to articulate complex technical concepts to diverse audiences.
Preferred Qualifications
- Master’s or Ph.D. in Computer Science, AI, Machine Learning, or a related quantitative field.
- Experience with distributed computing frameworks (e.g., Spark) for large-scale data processing.
- Knowledge of model interpretability (XAI) and fairness techniques.
- Familiarity with experiment tracking and model registry solutions.
- Experience with reinforcement learning or deep learning architectures beyond standard CNNs/RNNs.
- Certifications in cloud-based AI/ML services.
Perks & Benefits
- Competitive salary and performance-based bonuses.
- Generous paid time off (PTO) and bank holidays.
- Comprehensive health and dental insurance.
- Pension scheme with employer contributions.
- Flexible hybrid work model.
- Opportunities for continuous learning and professional development (e.g., conferences, courses, certifications).
- Collaborative and innovative work environment.
- Regular team social events and wellness initiatives.
- Cycle-to-work scheme.
How to Apply
If you are ready to take on this exciting challenge and contribute to groundbreaking AI projects, please click on the application link below to submit your CV and cover letter. We look forward to reviewing your application!
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