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Machine Learning Ops Engineer
  • Gdynia
Machine Learning Ops Engineer
Gdynia, Gdynia, Pomeranian Voivodeship, Polska
Adtran Networks sp. z o.o.
15. 3. 2025
Informacje o stanowisku

Adtran seeks an outstanding Machine Learning Ops Engineer II to work on the execution of ML/AI-driven Network Intelligence Solutions. You will collaborate with a highly skilled team of engineers, data scientists and subject matter experts to develop proof-of-concepts, explore AI-driven insights, and define next generation of data intelligence products. 

Responsibilities 

  • Deploy, monitor, and manage machine learning models in production using MLOps best practices. 
  • Automate model retraining, versioning, and deployment pipelines using CI/CD workflows. 
  • Ensure scalability, reliability, and reproducibility of ML models in cloud or on-prem environments. 
  • Design and implement end-to-end ML pipelines, including data ingestion, preprocessing, training, and inference. 
  • Optimize and maintain data pipelines for feature engineering and model retraining. 
  • Use tools like Airflow, Kubeflow, MLflow, or SageMaker Pipelines to orchestrate workflows. 
  • Deploy ML workloads on AWS, leveraging services like SageMaker, Databricks, Kubernetes, and Vertex AI. 
  • Optimize cloud resource utilization, cost management, and performance. 
  • Implement containerization and orchestration using Docker, Kubernetes, and AWS Fargate. 
  • Set up real-time model monitoring, logging, and alerting for performance tracking. 
  • Implement model drift detection and automate retraining strategies. 
  • Ensure models meet latency, throughput, and accuracy requirements. 
  • Enforce data governance, security, and access control policies for ML models and data pipelines. 
  • Ensure compliance with GDPR, HIPAA, and other industry regulations. 
  • Implement authentication and encryption mechanisms for data and model security. 
  • Work closely with data scientists, ML engineers, software engineers, and cloud architects. 
  • Collaborate with DevOps teams to integrate ML workloads into broader CI/CD pipelines. 
  • Participate in Agile workflows (sprint planning, stand-ups, retrospectives). 

Basic Qualifications 

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field. 
  • 4+ years of experience in MLOps, DevOps for ML, or Cloud-based ML Engineering. 
  • Strong programming skills in Python and Bash (knowledge of Go or Rust is a plus). 
  • Hands-on experience with CI/CD tools (Jenkins, GitLab CI, ArgoCD). 
  • Experience with containerization (Docker) and orchestration (Kubernetes, Kubeflow, MLflow). 
  • Strong knowledge of cloud platforms (AWS, Azure, GCP) and ML services (SageMaker, Vertex AI). 
  • Familiarity with monitoring and logging tools (Prometheus, Grafana, ELK Stack). 
  • Understanding of machine learning workflows, model lifecycle management, and data pipelines. 
  • B2+ English proficiency, with strong documentation and communication skills. 

Preferred Qualifications 

  • Experience with Apache Airflow, Databricks, Kafka, or Spark for ML pipeline orchestration. 
  • Hands-on experience with Feature Stores (Feast, AWS Feature Store). 
  • Experience with distributed training and model serving frameworks (TensorFlow Serving, Triton Inference Server). 
  • Knowledge of MLOps best practices, including model lineage tracking and automated retraining. 
  • Security and compliance experience (IAM policies, RBAC, SOC2 compliance). 
  • Experience working in Agile teams and across multi-cloud or hybrid environments. 

Compensation and Benefits

  • Stable employment conditions based on an employment contract (turnover rate below 4%) 
  • 1 additional vacation day for all, and 1 extra after 10 years being with us 
  • Flexible working hours and possible hybrid work (presence in the office in Gdynia 3 days a week)
  • English lessons during working hours 
  • Internal training program to support your training needs 
  • Paid employee referral program 
  • Multisport Card 
  • 3% employer contribution to PPK 
  • Private Health Care at Medicover (extended package for employees and possibility to enroll family members) 
  • Strong team-oriented and friendly work culture
  • Access to various sports activities and events 
  • Modern office (well-equipped gym and playroom) close to the SKM/PKM stations 

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