DevOps AI/ML Engineer

The Trust
Rishangles, United Kingdom
yesterday

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Remote
Rishangles, United Kingdom

Tech stack

Java
API
Artificial Intelligence
Airflow
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Data analysis
Azure
Cloud Computing
Continuous Integration
Directed Acyclic Graph (Directed Graphs)
Data Warehousing
DevOps
Amazon DynamoDB
Design of User Interfaces
Identity and Access Management
Python
PostgreSQL
Machine Learning
Online Transaction Processing
Performance Tuning
Systems Development Life Cycle
Cloud Services
Standard Sql
Azure
Software Deployment
Software Engineering
Feature Engineering
Snowflake
Spring-boot
Concourse
Kubernetes
Luigi
Data Analytics
Data Management
Machine Learning Operations
Functional Programming
Api Design
Amazon Web Services (AWS)
Data Pipelines
Docker
Jenkins
Microservices

Requirements

You're a highly motivated Principal Machine Learning Engineer. Your new role, in our Workplace Investing (WI) team, is part of our Artificial Intelligence and Machine Learning squad. Your squad consists of data engineers and data scientists who partner to deliver Artificial Intelligence solutions in support of our Participant Services business function. Your experience as an ML engineer and your appetite for a new challenge is what we are looking for. The role positions you as a member of our fast paced and integrated group and will be involved in the full end-to-end process through analysis, planning, design, development, quality and implementation of the solutions. It is a dynamic environment requiring strong social skills, superb communication skills, a strong team mentality, superb attention to detail and a sense of ownership. The Experience We're Looking For:

  • You will utilise your experience working in large-scale, sophisticated systems development initiatives.

  • Significant experience working on AI/ML teams giving you exposure and understanding of the entire machine learning lifecycle.

  • Experience using CI/CD tools like Jenkins, uDeploy or Concourse to establish CI/CD pipelines to deploy code and services to AWS preferably (or similar Cloud Provider), familiarity with IAM roles and policies and other security related artefacts, certificates etc...

  • Hands-on experience using AWS Services especially related to data and analytics - S3, EC2, Lambda, Glue, SNS, SQS for example

  • Demonstrated experience in deploying data pipeline and OLTP systems in AWS; using platforms like RDS/Postgres and/or data warehousing tools like Snowflake

  • Experience maximising tools like EC2 and EKS to run compute for API hosting on AWS ideally

  • Hands-on experience in assisting with (EDA) and feature engineering, Deployment, Tuning, Monitoring, Measurement and Retraining using ML infrastructure and MLOps in the Cloud (AWS preferred). The Skills You Bring:

  • A dedication to your craft and experience in software development, deployment, API development and UI development

  • Exceptional SQL skills and experience performing complex data analysis on multiple Data Platforms (Snowflake, RDS/Postgres, DynamoDB)

  • Working with Orchestration/DAGS tools (Airflow, Prefect, Luigi, Kubeflow or equivalent)

  • API development using Java (Springboot) and/or Python microservices infrastructure and deployment using containerisation (Docker) and container-orchestration systems such as Kubernetes

  • Your understanding of Model Development and Scoring (inference)

  • Your technical leadership skills and ability to communicate with a highly diverse peer group, both verbally and in written communications.

  • Your leadership skills, which enable you to lead several projects concurrently, collaborating with multiple teams and coordinating dependencies to deliver high quality AI/ML solutions. Nice to have or have an interest in learning:

  • Experience with Cloud service provider ML ecosystem such as AWS SageMaker, Azure ML and MLOps platform such as MLFlow, ModelOp, Seldon or equivalent

  • Experience with AWS and Azure AI ecosystems such as Textract, Comprehend, Kendra, Cognitive Services, etc

Benefits & conditions

DevOps AI/ML Engineer Start date: ASAPDuration: 12 monthsLocation: 1 week on site Dublin, 3 weeks working from homeRate: €450 - €500 per dayDescription

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