About Company
Are you ready to redefine the future of machine learning operations? At Career.zycto, we are a dynamic team dedicated to building robust, scalable, and intelligent systems that drive real-world impact. We champion innovation and empower our engineers to tackle complex challenges with cutting-edge technology. For an MLOps Engineer, this means a unique opportunity to build the very infrastructure that brings our groundbreaking AI models to life, ensuring seamless deployment and continuous improvement in a collaborative and forward-thinking environment. Join us and shape the next generation of AI solutions.
Job Description
Career.zycto is seeking a talented and passionate MLOps Engineer to join our innovative team in Henbury, Bristol. In this critical role, you will be instrumental in bridging the gap between machine learning model development and their deployment into production environments. You will design, implement, and maintain scalable and reliable MLOps pipelines, ensuring the seamless integration, continuous delivery, and robust monitoring of our cutting-edge AI solutions. This position requires a strong blend of software engineering, DevOps, and machine learning expertise, with a keen eye for automation and operational excellence. You will collaborate closely with data scientists, machine learning engineers, and software developers to establish best practices, improve infrastructure, and accelerate the development lifecycle of our intelligent systems. If you thrive in a fast-paced environment, are passionate about bringing AI innovations to life, and possess a solid understanding of the entire machine learning lifecycle, we encourage you to apply and contribute to our mission of pushing technological boundaries.
Key Responsibilities
- Design, develop, and maintain robust MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of machine learning models.
- Implement automated testing, validation, and deployment strategies for ML models across various environments.
- Monitor the performance, health, and data drift of machine learning models in production, setting up alerts and dashboards.
- Collaborate with data scientists and ML engineers to containerize models and ensure they are production-ready.
- Develop and manage infrastructure for model serving, inference, and batch predictions using cloud platforms and containerization technologies.
- Optimize ML workflows for efficiency, scalability, and cost-effectiveness.
- Establish and enforce best practices for code quality, version control, and reproducibility in ML projects.
- Troubleshoot and resolve issues related to ML model deployment, performance, and infrastructure.
- Stay current with emerging MLOps tools, techniques, and industry trends.
Required Skills
- Strong proficiency in Python programming.
- Extensive experience with MLOps platforms and tools (e.g., MLflow, Kubeflow, Sagemaker, Azure ML).
- Solid understanding of containerization technologies (Docker, Kubernetes).
- Proficiency with cloud platforms (AWS, Azure, or GCP).
- Experience with CI/CD pipelines (e.g., Jenkins, GitLab CI, GitHub Actions).
- Knowledge of machine learning concepts, models, and data science workflows.
- Experience with version control systems (Git).
- Excellent problem-solving and communication skills.
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Experience with infrastructure as code tools (e.g., Terraform, CloudFormation).
- Familiarity with data pipeline tools (e.g., Apache Airflow, DataFactory).
- Experience with monitoring tools like Prometheus, Grafana, or equivalent.
- Understanding of microservices architecture.
Perks & Benefits
- Competitive salary and performance-based bonuses.
- Generous paid time off and public holidays.
- Comprehensive health, dental, and vision insurance.
- Pension scheme with company contributions.
- Opportunities for professional development and continuous learning.
- Flexible working arrangements (where applicable).
- Modern office environment with state-of-the-art facilities.
- Regular team-building events and social gatherings.
How to Apply
To apply for this exciting MLOps Engineer role, please click on the application link below. We encourage you to submit your resume and a cover letter detailing your experience and why you believe you’re a great fit for Career.zycto. We look forward to reviewing your application!
