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Grid Dynamics

Machine Learning Engineer

Grid Dynamics
Romania · Full-time · Mid-Senior

At Grid Dynamics, we are looking for a Machine Learning Engineer to join a cutting-edge GenAI initiative in the energy sector. This project goes beyond traditional AI co-pilots—it's a bold step toward fully digitalizing expert knowledge into a proactive, intelligent recommendation system that’s reshaping industrial innovation.



Details on tech stack:

  • Proficiency in Python
  • Competent knowledge of best practices for software development
  • Strong understanding of Data Science concepts such as supervised and unsupervised learning, feature engineering and ETL processes, classical DS models types and neural networks types, hyperparameters tuning, model evaluation and selection
  • Proficiency in usage of appropriate AWS(preferred)/Azure services for building end-to-end ML pipelines, e.g. Amazon SageMaker, Lake Formation, Kinesis
  • Competent knowledge of MLOps paradigm and practices. Experience with MLOps tools (or appropriate cloud services), including model and data versioning and experiment tracking (e.g., DVC, MLflow, Weights & Biases), pipeline orchestration (e.g., Apache Airflow, Kubeflow). Understanding of deployment strategies for different types of models and inference (batch/online)
  • Knowledge and experience with big data processing frameworks (e.g., AWS Kinesis, Apache Flink, Lake Formation, Glue)
  • Competent SQL skills and experience with databases like SQLServer, PostgreSQL, Redis. TimescaleDB is a plus
  • Experience in developing and integrating RESTful APIs for ML model serving (e.g., Flask and FastAPI)
  • Experience with containerization technologies like Docker and orchestration tools (e.g., Kubernetes, AWS EKS, AWS ECR)


Nice to have requirements to the candidate:

  • Knowledge of monitoring and logging tools (e.g., AWS CloudWatch, Grafana, ELK Stack or appropriate cloud services)
  • Understanding of CI/CD principles and tools (e.g., Jenkins, GitLab CI, with Azure Repos and Azure Pipelines preferred) for automating the testing and deployment of machine learning models and applications
  • Experience with Cloud Identity and Access Management
  • Experience with Cloud Load Balancing
  • Knowledge of Infrastructure as Code (IaC) tools such as AWS CloudFormation (preferred), or similar like Terraform, Ansible


We offer:

  • Opportunity to work on bleeding-edge projects
  • Work with a highly motivated and dedicated team
  • Competitive salary
  • Flexible working hours, with a hybrid working mode
  • Benefits package - medical insurance, sports
  • Corporate social events
  • Professional development opportunities, international certification
  • Well-equipped office located downtown

Key Skills

Ranked by relevance

aws cloud machine learning apache mlops infrastructure as code containerization neural networks cloudformation restful apis kubernetes postgresql gitlab ci terraform big data kubeflow jenkins grafana docker gitlab mlflow redis flask cicd sql etl elk eks ai
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Posted
Jun 04, 2025
Type
Full-time
Level
Mid-Senior
Location
Bucharest
Company
Grid Dynamics

Industries

IT Services IT Consulting

Categories

Science

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