About Company
Join a dynamic team where your contributions directly shape the future of intelligent systems. Career.zycto is at the forefront of leveraging artificial intelligence to solve complex industry challenges, driving innovation across various sectors. We foster a collaborative environment where curiosity is celebrated, and continuous learning is paramount. For an AI Engineer focused on model training and automation, we offer unparalleled opportunities to work with cutting-edge technologies, scale impactful solutions, and significantly advance your career in a supportive, growth-oriented culture. Be part of a company that values expertise and empowers its engineers to push boundaries.
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Job Description
Career.zycto is seeking a highly skilled and passionate AI Engineer with a strong focus on model training and automation to join our innovative team in Thorner, Leeds. In this pivotal role, you will be instrumental in designing, developing, and deploying robust machine learning pipelines, ensuring our AI models are efficient, scalable, and perform optimally in production environments. You will dive deep into data, architecting solutions that automate the entire lifecycle of AI models, from initial data ingestion and feature engineering to training, evaluation, deployment, and ongoing monitoring. This role requires a blend of deep technical expertise in machine learning and software engineering, with a keen eye for operational excellence and automation. You will work closely with data scientists, researchers, and product teams to translate cutting-edge AI research into practical, high-impact solutions that drive business value. We are looking for someone who is not just proficient in current ML technologies but also eager to explore new paradigms, optimize existing workflows, and contribute to a culture of continuous improvement in our AI development practices. If you are passionate about building intelligent systems, thrive on automating complex processes, and want to make a tangible impact, we encourage you to apply.
Key Responsibilities
- Design, develop, and implement scalable and efficient machine learning pipelines for model training, validation, and inference.
- Automate the full lifecycle of AI models, including data preparation, feature engineering, model training, evaluation, deployment, and monitoring.
- Optimize existing AI models for performance, accuracy, and resource efficiency using advanced techniques and distributed computing.
- Collaborate with data scientists to transition experimental models into production-ready solutions, applying MLOps best practices.
- Develop and maintain robust monitoring and alerting systems for deployed AI models to ensure stability and performance.
- Research, evaluate, and integrate new AI/ML technologies, frameworks, and tools to enhance our capabilities.
- Ensure data quality, integrity, and security across all stages of the ML pipeline.
- Contribute to code reviews, technical documentation, and knowledge sharing within the engineering team.
Required Skills
- Proficiency in Python and strong software engineering fundamentals.
- Extensive experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Solid understanding of machine learning algorithms, statistical modeling, and data structures.
- Practical experience with MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes).
- Experience with cloud platforms (AWS, Azure, GCP) and their AI/ML services.
- Familiarity with version control systems (Git) and CI/CD pipelines.
- Excellent problem-solving, analytical, and communication skills.
- Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, or a related quantitative field.
Preferred Qualifications
- Master's or PhD in Computer Science, AI, Machine Learning, or a related discipline.
- Experience with large-scale data processing technologies (e.g., Spark, Hadoop).
- Knowledge of deep learning architectures (CNNs, RNNs, Transformers) and their applications.
- Familiarity with model explainability (XAI) and fairness techniques.
- Contributions to open-source machine learning projects or relevant publications.
- Experience with distributed training and hyperparameter optimization frameworks.
Perks & Benefits
- Competitive salary and performance-based bonuses.
- Comprehensive health, dental, and vision insurance plan.
- Generous paid time off, including holidays and sick leave.
- Flexible working arrangements and support for work-life balance.
- Dedicated budget for continuous professional development, training, and certifications.
- Modern, collaborative office environment with ergonomic workspaces.
- Company pension scheme with employer contributions.
- Regular team social events, wellness programs, and employee recognition initiatives.
- Opportunities for career advancement and mentorship within a growing company.
How to Apply
To apply for this exciting opportunity, please click the application link below. Ensure your resume highlights your experience with AI model training, automation, and relevant MLOps practices. We look forward to reviewing your application and exploring how your skills can contribute to our innovative team.
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