Start Date: ASAP
Contract Length: 12 Month Contract
Location / Hybrid Working: Dublin- 1 week in office every month
Pay Rate: Up to €470 per day
Role Overview:
As a Principal Machine Learning Engineer, you will be involved in the complete end-to-end development process, from analysis and planning to design, development, quality assurance, and implementation of AI solutions. This role offers the opportunity to work closely with cross-functional teams, including engineers and data scientists, while producing insightful, impactful results for the division. We are looking for someone who thrives in a collaborative environment, has a keen eye for detail, and is driven by delivering high-quality solutions.
What You’ll Do:
- Lead the design, development, and deployment of AI/ML solutions that automate and improve business operations.
- Take ownership of the full lifecycle of machine learning solutions, from concept through to implementation.
- Collaborate with multiple teams to coordinate dependencies and deliver high-quality, scalable solutions.
- Develop and optimize APIs, microservices, and data pipelines in AWS.
- Implement best engineering practices, including code quality, unit testing, and code review.
- Work on deploying and optimizing systems using AWS services such as EC2, S3, Lambda, and more.
- Maximize tools like EC2 and EKS for API hosting and compute.
- Provide leadership and mentorship to junior engineers and support continuous learning within the team.
- Contribute to the machine learning lifecycle with model development, scoring (inference), and production deployment.
What We’re Looking For:
- 8+ years of hands-on experience working in large-scale systems development, focusing on software, API development, UI development, or similar areas.
- 3+ years of proven experience working with AWS services, particularly related to data and analytics (e.g. S3, EC2, Lambda, AWS Step Functions, SNS, SQS).
- Significant experience using CI/CD tools like Jenkins, uDeploy, or Concourse.
- Experience deploying data pipelines and OLTP systems in AWS, utilizing tools like RDS/Postgres and Snowflake.
- Expertise in API development using Java (Springboot) or Python microservices, with experience deploying using Docker and Kubernetes.
- Strong experience in UI development using AngularJS.
- Solid understanding of SQL and performing complex data analysis across platforms such as Snowflake, RDS/Postgres, and DynamoDB.
- Demonstrated exposure to AI/ML teams, with an understanding of the machine learning lifecycle, including model development and scoring (inference).
- Strong dedication to engineering best practices, including code quality, unit testing, and documentation.
- Excellent communication, presentation, and collaboration skills.
Nice to Have (or an Interest in Learning):
- Experience with Cloud service provider ML ecosystems such as AWS SageMaker, Azure ML, and MLOps platforms like MLFlow, ModelOp, Seldon, etc.
- Familiarity with AWS and Azure AI ecosystems such as Textract, Bedrock, Comprehend, Kendra, Cognitive Services, etc.
