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- Tasks: Design and manage data and machine learning infrastructure for seamless model deployment.
- Company: M-KOPA drives digital and financial inclusion across diverse markets.
- Benefits: Enjoy remote work flexibility, family-friendly policies, and personal development opportunities.
- Why this job: Join a mission-driven team focused on data-driven decisions and innovative machine learning solutions.
- Qualifications: Experience in managing ML infrastructure, Azure tools, and proficiency in programming languages required.
- Other info: Fully remote role with a diverse team across the UK, Europe, and Africa.
The predicted salary is between 48000 - 84000 £ per year.
We are looking for a Senior Analytics & MLOps Platform Engineer to join our Analytics team as we scale up and drive digital and financial inclusion across our markets. As a Senior Analytics & MLOps Platform Engineer, you will be designing, deploying and managing data and machine learning infrastructure to make it easy for data scientists to experiment, train, serve and monitor batch and online machine learning models in production.
Our mission is to improve the ability of Product, Operations and Data Science teams in M-KOPA to make data driven decisions and automate them using machine learning. You will be designing and implementing architectures to streamline exploration, training, deployment and monitoring of machine learning models. Building and maintaining CI/CD pipelines to deploy machine learning models into production, ensuring scalability, reliability, and continuous performance monitoring with automated retraining workflows.
You will also implement version control for models and feature sets to ensure reproducibility, traceability, and compliance with best practices. Using Azure and infrastructure-as-code tools (e.g., Azure Bicep, Terraform) you will automate and manage infrastructure for data pipelines, machine learning model training, and serving. Additionally, you will establish infrastructure and engineering patterns to feature engineering and reuse across a suite of models.
Developing workflows for model validation, testing, and deployment, fully integrated with CI/CD systems, while enhancing resource utilization, to enable distributed processing, and optimize workflows for scalability, including GPU/TPU acceleration. This is a fully remote role, working within the following time zone (UTC -1 / UTC+3) with a diverse group of other employees working remotely from locations such as the UK, Europe and Africa. You will be reporting to the Head of Analytics at M-KOPA.
Expertise
Our expectation is that you have experience managing machine learning infrastructure in production, working with infrastructure-as-code tools such as Azure Bicep, Terraform, ARM, CloudFormation or similar, and good practical experience in data engineering, for machine learning or general analytics use cases. Additionally, having experience with Kubernetes or other platforms for containerized applications as well as working with orchestration systems such as Apache Airflow would be essential to succeed in this role.
The ideal candidate for this role would need to have proficiency in programming languages (Python, C#, Java, etc.) as well as a certification in Azure Solutions Architect Expert or similar.
Why M-KOPA?
At M-KOPA, we empower our people to own their careers through diverse development programs, coaching partnerships, and on-the-job training. We support individual journeys with family-friendly policies, prioritise well-being, and embrace flexibility. Join us in shaping the future of M-KOPA as we grow together. Explore more at m-kopa.com.
Contact Detail:
M-KOPA Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Analytics & MLOps Platform Engineer
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Azure Bicep, Terraform, and Kubernetes. Having hands-on experience or projects showcasing these skills can set you apart during discussions.
✨Tip Number 2
Network with current employees or professionals in similar roles on platforms like LinkedIn. Engaging in conversations about their experiences at M-KOPA can provide valuable insights and potentially give you a referral.
✨Tip Number 3
Prepare to discuss your previous experience managing machine learning infrastructure in production. Be ready to share specific examples of how you've implemented CI/CD pipelines and automated workflows, as this will demonstrate your practical knowledge.
✨Tip Number 4
Showcase your problem-solving skills by preparing for technical interviews. You might be asked to solve real-world problems related to data engineering or machine learning, so practice coding challenges and system design questions relevant to the role.
We think you need these skills to ace Senior Analytics & MLOps Platform Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in managing machine learning infrastructure, using infrastructure-as-code tools like Azure Bicep and Terraform, and any work with CI/CD pipelines. Customise your CV to reflect the specific skills mentioned in the job description.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data-driven decision-making and your experience in designing and deploying machine learning models. Mention how your background aligns with M-KOPA's mission and values.
Showcase Technical Skills: In your application, emphasise your proficiency in programming languages such as Python, C#, or Java. Include any certifications you hold, particularly in Azure Solutions Architect, to demonstrate your qualifications for the role.
Highlight Remote Work Experience: Since this is a fully remote role, mention any previous remote work experience you have. Discuss how you effectively communicate and collaborate with diverse teams across different time zones.
How to prepare for a job interview at M-KOPA
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning infrastructure and tools like Azure Bicep and Terraform. Highlight specific projects where you've designed, deployed, or managed data pipelines and CI/CD workflows.
✨Demonstrate Problem-Solving Abilities
Expect to face scenario-based questions that assess your problem-solving skills. Think of examples where you overcame challenges in deploying machine learning models or optimising workflows, and be ready to explain your thought process.
✨Familiarise Yourself with M-KOPA's Mission
Understand M-KOPA's goals around digital and financial inclusion. Be ready to discuss how your role as a Senior Analytics & MLOps Platform Engineer can contribute to these objectives and improve data-driven decision-making.
✨Prepare Questions for the Interviewers
Have insightful questions ready about the team dynamics, current projects, and future challenges. This shows your genuine interest in the role and helps you gauge if the company culture aligns with your values.