Principal Machine Learning / Fullstack Engineer

Principal Fullstack ML Engineer
Start date: ASAP 
Contract: 12 Months 
Location: Galway, Ireland
Type: Hybrid: Onsite 1 week per month 
Rate: €450 - €500 per day 
Key Responsibilities:

• Develop and deploy scalable machine learning models and data pipelines in AWS.
• Design and implement CI/CD pipelines for seamless deployment of AI/ML solutions.
• Utilize AWS services such as S3, EC2, Lambda, Step Functions, SNS, and SQS for building efficient cloud solutions.
• Develop and maintain microservices and APIs using Java (Spring Boot) and Python.
• Work with containerization technologies such as Docker and Kubernetes (EKS) for model deployment and scaling.
• Optimize database performance using RDS/Postgres, Snowflake, and DynamoDB.
• Lead and collaborate with AI/ML teams to implement end-to-end machine learning workflows, including model development, inference, and monitoring.
• Ensure best practices for security, scalability, and performance in cloud environments.
• Work closely with stakeholders to translate business requirements into AI-driven solutions.

Required Skills & Experience:

• 8+ years of experience in large-scale systems development focused on software, APIs, and UI development.
• 3+ years of hands-on experience with AWS services, specifically for data and analytics.
• Experience in CI/CD automation using tools like Jenkins, uDeploy, or Concourse.
• Strong expertise in SQL and complex data analysis across multiple platforms.
• Proven experience in developing and deploying APIs using Java (Spring Boot) and Python.
• Experience working with containerized environments and orchestration tools like Kubernetes (EKS).
• Understanding of machine learning lifecycle, model development, and inference.
• Strong proficiency in UI development using AngularJS.
• Ability to collaborate across teams, coordinate dependencies, and deliver AI/ML solutions effectively.

Nice to Have:

• Experience with Cloud ML services like AWS SageMaker, Azure ML, or MLOps platforms (MLFlow, ModelOp, Seldon, etc.).
• Familiarity with AWS and Azure AI ecosystems such as Textract, Bedrock, Comprehend, and Cognitive Services.