GeekSoft Consulting
AI ML Senior Engineer
GeekSoft ConsultingNetherlands22 hours ago
Full-timeInformation Technology
  • Help design, build and continuously improve the clients online platform.
  • Research, suggest and implement new technology solutions following best practices/standards.
  • Take responsibility for the resiliency and availability of different products.
  • Be a productive member of the team.



Requirements

  • AI/ML Senior Engineer to join our growing ML Engineering team.
  • Collaborate closely with data scientists, engineers, and product managers to design, deploy, and operate production-grade machine learning systems that power critical services across our Digital and Retail platforms.
  • This position has a strong focus on MLOps and ML platform development, helping scale and maintain reliable, end-to-end ML workflows using modern cloud-native infrastructure and tools.
  • Design, build, and maintain ML pipelines for model training, validation, deployment, and monitoring.
  • Enable scalable ML solutions for use cases such as recommendation systems, forecasting, and intelligent automation.
  • Develop and deploy production-ready services using tools such as Airflow, Azure ML, and FastAPI.
  • Automate model build and deployment workflows using CI/CD pipelines (GitHub Actions, Azure DevOps).
  • Ensure reliability, observability, and performance of the ML platform.
  • Collaborate with data scientists to productionize research models and code into scalable services.
  • Implement monitoring, alerting, and model drift detection using tools like Azure Monitor, New Relic, Grafana, and custom logging frameworks.
  • Continuously improve and manage cloud infrastructure using Terraform, Docker, and Fargate.
  • Proven experience in ML Engineering, MLOps, DevOps, or Data Engineering with exposure to the full ML lifecycle.
  • Hands-on experience building and maintaining ML workflows and pipelines.
  • Strong proficiency in Python, with experience using MLflow, Scikit-learn, or PyTorch.
  • Experience with cloud platforms, particularly Azure and/or AWS.
  • Solid understanding of containerization (Docker) and orchestration technologies such as Kubernetes.
  • Hands-on exposure to CI/CD tools (GitHub Actions, Azure DevOps) and Infrastructure as Code (Terraform).
  • Strong collaboration and communication skills, with the ability to work in cross-functional teams.
  • Languages: Python (primary), SQL, Bash
  • Cloud Platforms: Azure, AWS
  • ML & Workflow Tools: MLflow, Azure ML, Airflow
  • APIs & Services: FastAPI, Azure Functions
  • Data Platforms: Snowflake, Delta Lake, Redis, Azure Data Lake
  • Infrastructure & DevOps: Docker, Fargate, Terraform, GitHub Actions, Azure DevOps
  • Monitoring & Observability: Grafana, Azure Monitor, New Relic
  • Experience working with enterprise data platforms such as Snowflake or Azure Data Lake.
  • Experience deploying ML models as APIs or microservices.
  • Strong understanding of model performance tracking, monitoring, and observability best practices.
  • Familiarity with orchestration tools such as Airflow or Azure Data Factory.


Benefits

  • A challenging, innovating environment.
  • Opportunities for learning where needed.

Key Skills

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