Join to apply for the ML Ops Engineer role at Element Materials Technology.
Seniority level
Mid‑Senior level
Employment type
Full‑time
Job function
Engineering and Information Technology
Industries
Industrial Machinery Manufacturing, Public Safety, and International Trade and Development
Overview
We are seeking a highly skilled ML Ops Engineer to join our growing data team. This role is critical in designing and implementing robust, scalable, and efficient data systems that power analytics, machine learning models, and business insights.
Responsibilities
Data Architecture & Development
* Leverage best practices in schema design, partitioning, and optimisation for efficient storage and retrieval.
* Build and maintain data models to support analytics and machine learning workflows.
* Design and implement scalable, secure, and high‑performance data lake and data warehouse solutions.
Pipeline Orchestration
* Develop, monitor, and optimise ETL/ELT workflows using Apache Airflow.
* Ensure data pipelines are robust, error‑tolerant, and scalable for real‑time and batch processing.
Data Scraping & Unstructured Data Processing
* Develop and maintain scalable web‑scraping solutions to collect data from diverse sources.
* Extract, clean, and transform unstructured data such as text, images, and log files into structured formats suitable for analysis.
* Use tools such as BeautifulSoup, Scrapy, or Selenium for web scraping, and NLP techniques for text processing.
Cloud Integration
* Design and implement cloud‑native data solutions with Microsoft Azure.
* Optimize costs and performance of cloud‑based data solutions.
Infrastructure as Code (IaC)
* Use Terraform to automate the provisioning and management of cloud infrastructure.
* Define reusable and modular Terraform configurations to support scalable deployment of resources.
MLOps
* Collaborate with data scientists and machine learning engineers to operationalise machine learning models.
* Deploy LLMs and debug failures in production environments to detect changes in data and model behaviour.
* Implement CI/CD pipelines for machine learning workflows, ensuring efficient model deployment and monitoring.
Containerisation and Orchestration
* Utilise Kubernetes and containerisation technologies (e.g., Docker) to deploy scalable, fault‑tolerant data processing systems.
* Manage infrastructure and resource allocation for containerised data applications.
Cross‑Functional Collaboration
* Work closely with stakeholders, including data scientists, software engineers, and business analysts.
* Mentor junior engineers and foster a culture of continuous learning within the team.
Skills / Qualifications
Education
* Bachelor’s/Master’s/PhD degree in Computer Science, Engineering, or a related field; or equivalent professional experience.
Experience
* 5+ years of experience in data engineering or a related field.
* Strong expertise in data pipeline orchestration tools such as Apache Airflow.
* Proven track record of designing and implementing data lakes and warehouses (experience with Azure is a plus).
* Demonstrated experience with Terraform for infrastructure provisioning and management.
* Solid understanding of MLOps practices, including model training, deployment, and monitoring.
* Hands‑on experience with Kubernetes and containerised environments.
* Knowledge and experience of working with Large Language Models.
* Interest in working alongside applied researchers and data scientists.
Technical Skills
* Proficiency in programming languages such as Python & SQL.
* Experience with distributed computing frameworks such as Spark.
* Familiarity with version control systems (e.g., Git) and CI/CD pipelines.
Soft Skills
* Strong problem‑solving skills and ability to work in a fast‑paced, collaborative environment.
* Excellent communication and documentation skills.
* Strong analytical mindset with attention to detail.
Company Overview
Element is one of the fastest growing testing, inspection and certification businesses in the world. Globally we have more than 9,000 brilliant minds operating from 270 sites across 30 countries. Together we share an ambitious purpose to ‘Make tomorrow safer than today’. When failure in use is not an option, we help customers make certain that their products, materials, processes and services are safe, compliant and fit for purpose. From early R&D, through complex regulatory approvals and into production, our global laboratory network of scientists, engineers, and technologists support customers to achieve assurance over product quality, sustainable outcomes, and market access.
Diversity Statement
At Element, we always take pride in putting our people first. We are an equal opportunity employer that recognises diversity and inclusion as fundamental to our vision of becoming ‘the world’s most trusted testing partner’. All suitably qualified candidates will receive consideration for employment on the basis of objective work‑related criteria and without regard for the following: age, disability, ethnic origin, gender, marital status, race, religion, responsibility of dependents, sexual orientation, or gender identity or any other characteristics in accordance with applicable governing laws.
For accommodations during the application process, please email Recruitment@element.com.
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