Principal DevOps/Cloud Engineer

intelmatix
London
3 days ago
Create job alert

Role Overview

Join our team as the Principal Cloud/DevOps Engineer, a key player in our technological evolution. This role goes beyond traditional cloud infrastructure and DevOps, encompassing the automation and deployment of advanced computational processes, including machine learning models. You will be instrumental in ensuring our cloud infrastructure is robust, scalable, secure, and efficient, with a focus on supporting diverse technological solutions.

Key Responsibilities

  1. Lead the management and optimization of our cloud environment, focusing on performance, security, and scalability.
  2. Automate infrastructure provisioning and management, integrating complex computational and analytical model deployments.
  3. Develop and enforce comprehensive security policies for both cloud infrastructure and data-intensive applications.
  4. Work closely with development teams to optimize applications, machine learning model performance and help with setting up tools ensuring efficient deployment and monitoring.
  5. Design and implement CI/CD pipelines that support both software and data-driven workflows.
  6. Conduct regular security audits, adapting to the evolving demands of a data-centric infrastructure.
  7. Champion best practices in cloud management, DevOps processes, and compliance for data-intensive applications.

Required Qualifications

  1. Bachelor’s degree in Computer Science, Information Systems, or a related field, or equivalent professional experience.
  2. Minimum of 8 years in Platform/DevOps Engineering, with experience in cloud-based data processing and deployment strategies.
  3. Expertise in managing public cloud environments (AWS preferred), including proficiency with data services and ML model deployment tools.
  4. Skilled in Infrastructure-as-Code (IaC) using tools like Terraform, and in automating data processing tasks.
  5. Experience with CI/CD tools (GitHub Actions, Jenkins, AWS CodePipeline), and integrating data-centric workflows.
  6. Familiarity with monitoring and logging tools (e.g., Prometheus, Loki, Grafana) in application and data-intensive environments.
  7. Proficiency in Configuration Management tools (Chef, Puppet, Ansible) and data orchestration tools (e.g., Airflow, Prefect).
  8. Strong background in containerization using Docker and orchestration with Kubernetes.
  9. In-depth knowledge of Linux, SQL, cloud security, scripting for automation (Python, Bash), load balancing technologies, and CDN.
  10. Agile methodology experience, excellent communication, and leadership skills.
  11. Adaptable, self-motivated, and capable of thriving in a fast-paced, unstructured startup environment.

Nice to Have

  1. AWS Certifications (AWS Certified Solutions Architect, DevOps Engineer).
  2. Extensive experience with scalable deployment of data processing and machine learning models (batch as well as real-time).
  3. Practical experience in developing and maintaining ML systems with tools such as MLflow, BentoML, and Evidently AI.
  4. Exposure to learning methodologies leveraging advanced modeling frameworks such as PyTorch and TensorFlow will be beneficial.
  5. Familiarity with data governance and compliance standards.
  6. Certification as a Kubernetes Administrator or Developer (CKA/CKAD).
  7. Exposure to diverse cloud compute and data processing tool stacks (AWS, Azure, GCP, open source).

Employee Benefits

At Intelmatix, our benefits package is designed to meet the diverse needs of our employees, reflecting our dedication to their well-being and professional growth. Depending on your office location and specific needs, our benefits may include:

  1. Comprehensive Medical Insurance for you and your dependents.
  2. In-Office Snacks Pantry.
  3. Relocation Support.
  4. Childrens School Allowance.
  5. Role-Related Training Support.
  6. Wellness Programs.
  7. Salary Advance for Housing Costs.
  8. Travel Tickets.
  9. Pension Contributions.

We are committed to continuously enhancing our benefits package to adapt to the unique needs and circumstances of our valued team members, ensuring a supportive and enriching environment for everyone at Intelmatix.

J-18808-Ljbffr

Related Jobs

View all jobs

Principal Azure Data Engineer (Databricks)

Principal Software Engineer

Senior Principal AI/ML Engineer

Principal Software Engineer

Senior Manager - Data & AI Engineering

Technical Consultant, SI MNE India, Enterprise support

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Machine Learning Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Machine learning (ML) has become an indispensable force in the modern business world, influencing everything from targeted marketing campaigns to advanced medical diagnostics. As industries integrate predictive algorithms and data-driven decision-making into their core operations, the need for effective leadership in machine learning environments has never been greater. Whether you’re overseeing a small team of data scientists or spearheading an enterprise-scale ML project, your leadership style must accommodate rapid innovation, complex problem-solving, and diverse stakeholder expectations. This guide provides actionable insights into how you can motivate, mentor, and establish achievable goals for your machine learning teams—ensuring they thrive in data-driven environments.

Careers Jobs

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Careers

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.