Remote friendly

Line of Service



FS X-Sector



Management Level

Senior Associate

Job Description & Summary

A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.

Creating business intelligence from data requires an understanding of the business, the data, and the technology used to store and analyse that data. Using our Rapid Business Intelligence Solutions, data visualisation and integrated reporting dashboards, we can deliver agile, highly interactive reporting and analytics that help our clients to more effectively run their business and understand what business questions can be answered and how to unlock the answers.

**Job Title: Senior AWS MLOps Engineer**

**Job Description:**

We are seeking a highly skilled and experienced Senior AWS MLOps Engineer to join our dynamic team.
As a key member of our MLOps team, you will be responsible for designing, implementing, and
maintaining machine learning operations solutions on the AWS platform. The ideal candidate will have
5-6 years of hands-on technical experience in MLOps and a deep understanding of the machine learning
operations lifecycle, deployment strategies, CI/CD pipelines, model supervision techniques, automation
frameworks, and end-to-end workflow design.


- Design, implement, and maintain MLOps solutions on the AWS platform.
- Develop and manage CI/CD pipelines for machine learning models.
- Implement model deployment strategies using AWS services such as SageMaker, Lambda, and ECS.
- Design and implement model supervision mechanisms to monitor model performance and health.
- Develop automation frameworks for model training, deployment, and monitoring.
- Collaborate with data scientists, engineers, and other stakeholders to design end-to-end workflows for
machine learning projects.
- Implement drift detection and mitigation strategies using AWS services like SageMaker Model Monitor
and CloudWatch.
- Stay up-to-date with the latest advancements in MLOps practices and AWS services, and propose
innovative solutions to improve efficiency and scalability.


- Bachelor’s degree in Computer Science, Engineering, or related field. Master’s degree preferred.
- 5-6 years of hands-on experience in MLOps, with a strong understanding of the machine learning
operations lifecycle.
- Proficiency in AWS services such as SageMaker, Lambda, ECS, S3, CloudFormation, IAM, and

- Experience with containerization technologies such as Docker and Kubernetes.
- Strong programming skills in languages such as Python, Java, or Scala.
- Experience with CI/CD tools like Jenkins, GitLab CI/CD, or AWS CodePipeline.
- Good understanding on Machine learning/Deep learning Algorithms and its functionality.
- Basic understanding on Statistics and Domain knowledge of it.
- Excellent problem-solving skills and the ability to troubleshoot complex issues.
- Strong communication and collaboration skills, with the ability to work effectively in a team

**Preferred Qualifications:**

- AWS Certified Machine Learning – Specialty certification.
- Experience with serverless architectures and event-driven programming.
- Knowledge of data engineering concepts and tools such as Apache Spark, Hadoop, or Apache Airflow.
- Experience with version control systems like Git.
- Familiarity with DevOps principles and practices.
Good to have good understanding on LLM models and any hands on experience of deploying solutions
using LLMops. Bedrock

If you are passionate about leveraging AWS services to streamline machine learning operations and
drive innovation, we encourage you to apply for this exciting opportunity. Join us in shaping the future
of MLOps and revolutionizing the way machine learning models are developed, deployed, and managed.

Mandatory Skill Set-AWS ML Ops
Preferred Skill Set-AWS ML Ops
Year of experience required-4-6

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required:

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Amazon Web Services (AWS)

Optional Skills

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Available for Work Visa Sponsorship?

Government Clearance Required?

Job Posting End Date