Machine Learning Ops Engineer

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