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- Tasks: Design, build, and maintain scalable machine learning platforms for fraud detection.
- Company: Join a multi-award-winning company recognized for its commitment to people and innovation.
- Benefits: Enjoy flexible working, personal growth opportunities, and a collaborative environment.
- Why this job: Work on cutting-edge AI technology that makes a real impact in preventing fraud.
- Qualifications: Experience with AWS, Python, and MLOps is essential.
- Other info: Opportunity to work on Greenfield projects and develop your skills in a supportive setting.
The predicted salary is between 48000 - 64000 £ per year.
MLOps Engineer (AWS IaC Python) London / WFH to £80k Do you have experience of putting Machine Learning models into production? You could be progressing your career working on bleeding edge, Machine Learning and AI powered, audio fraud detection software used by all UK banks, the emergency services and a range of other clients to prevent and detect fraudulent call activities. As an MLOps Engineer you’ll design, build and maintain scalable machine learning platforms, continually iterating and improving cloud based authentication and fraud detection systems using AWS SageMaker and other AWS services including EC2, S3, Lambda, CloudFormation and CloudWatch. You’ll develop robust data pipelines and workflows for efficient data processing and storage using tools such as Amazon Athena, Apache Iceberg and Spark. Your primary focus will be on MLOps and software engineering to develop datasets, data pipelines, platform features, writing Python code to train, deploy, monitor and run real-time inferences. There’s an open, collaborative environment where learning and personal development are key and there’s a strong pipeline of Greenfield projects as well as flexible working and a host of benefits; the company has been awarded Platinum standard by Investors in People and is multi-award winning with various DEI initiatives and excellent personal growth and career development opportunities. WFH Policy: You ca…
MLOps Engineer AWS employer: Client Server Ltd.
Contact Detail:
Client Server Ltd. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land MLOps Engineer AWS
✨Tip Number 1
Familiarize yourself with AWS services, especially SageMaker, EC2, S3, and Lambda. Having hands-on experience with these tools will not only boost your confidence but also demonstrate your capability to work on the projects mentioned in the job description.
✨Tip Number 2
Showcase your experience with MLOps practices and tools. Be prepared to discuss specific projects where you've implemented machine learning models into production, focusing on the challenges you faced and how you overcame them.
✨Tip Number 3
Highlight your proficiency in Python and any relevant frameworks or libraries you've used for data processing and machine learning. Being able to talk about your coding experience in detail will set you apart from other candidates.
✨Tip Number 4
Emphasize your collaborative skills and willingness to learn. The job description mentions an open and collaborative environment, so sharing examples of teamwork and continuous learning will resonate well with the hiring team.
We think you need these skills to ace MLOps Engineer AWS
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your experience with Machine Learning models and any specific projects where you've put them into production. Mention your familiarity with AWS services like SageMaker, EC2, and Lambda.
Showcase Technical Skills: Detail your proficiency in Python and any other relevant programming languages or tools. Include examples of how you've used these skills in previous roles, particularly in MLOps and software engineering.
Demonstrate Problem-Solving Abilities: Provide examples of challenges you've faced in developing data pipelines or workflows and how you overcame them. This will show your ability to think critically and adapt in a fast-paced environment.
Express Enthusiasm for Learning: Convey your eagerness to learn and grow within the role. Mention any relevant courses, certifications, or personal projects that demonstrate your commitment to continuous improvement in the field of MLOps and AI.
How to prepare for a job interview at Client Server Ltd.
✨Showcase Your MLOps Experience
Be prepared to discuss your previous experience with deploying machine learning models into production. Highlight specific projects where you utilized AWS services like SageMaker, EC2, and Lambda, and explain the impact of your work.
✨Demonstrate Your Python Skills
Since Python is a key part of the role, be ready to talk about your proficiency in writing Python code for data processing and model training. Consider sharing examples of scripts or applications you've developed that relate to MLOps.
✨Understand the Tools and Technologies
Familiarize yourself with the tools mentioned in the job description, such as Amazon Athena, Apache Iceberg, and Spark. Be prepared to discuss how you've used these technologies in past projects and how they can be applied to the company's needs.
✨Emphasize Collaboration and Learning
The company values an open and collaborative environment. Share examples of how you've worked effectively in teams, contributed to knowledge sharing, and pursued personal development in your career.
