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Shory

Machine Learning Engineer

Department
Engineering
Job Type / Location
Abu Dhabi
Experience Required
3+ years
Posted On

About Shory

Shory is revolutionizing the Insurtech market by empowering customers with technology to create ease of mind and trustworthiness around insurance needs.

About the Role

We are seeking a seasoned Machine Learning Engineer to join our AI team in Abu Dhabi, UAE. In this role, you will help design and build the technical backbone of intelligent products, developing scalable, cloud-native systems supporting machine learning workflows. The ideal candidate has a strong foundation in software engineering, with experience in one or more of the following: GenAI integration (e.g., OpenAI, AWS Bedrock) or MLOps. You will work alongside specialists in ML and data to deliver robust, production-grade AI capabilities. This role will be onsite in Abu Dhabi, UAE and requires relocation.

Responsibilities

  • Design and implement secure, cloud-native microservices and APIs using Python for data and AI services.
  • Architect LLM-integrated systems (e.g., RAG pipelines) leveraging LangChain, vector databases, and GenAI providers (e.g., AWS Bedrock, OpenAI).
  • Automate infrastructure and CI/CD workflows using Docker, Kubernetes, Helm, and Terraform across AWS and/or Azure.
  • Develop scalable data pipelines using technologies such as Spark, Kafka, and Airflow to power machine learning workflows.

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Software Engineering or a related field.
  • 3-5 years of experience in AI/software engineering, or MLOps roles building and deploying production-grade services.
  • Proven experience with Python (FastAPI, Django), SQL, and cloud-native architecture (AWS or Azure).
  • Hands-on with tools such as Kafka, Spark, Airflow, Redis, Elasticsearch, and container orchestration (K8s).
  • Experience with GenAI tools such as LangChain, RAG systems, Bedrock/OpenAI APIs.
  • Solid grasp of CI/CD, IAC (Terraform, Helm), and monitoring (Prometheus, Grafana).
  • Experience deploying in cloud environments with EC2, Lambda, S3, RDS, EKS/ECS, etc.

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