Senior MLOps Engineer

We are looking for a skilled and experienced MLOps Engineer with business orientation to join our dynamic and innovative team  an MLOps Engineer, you will play a crucial role in developing and maintaining the infrastructure and processes required for deploying and managing machine learning models in production.

• Master or higher degree in Computer Science, Engineering, or a related field.
• 5+ years of professional experience in MLOps, machine learning engineering, or a similar role.
• Strong experience in Computer Vision, NLP, Generative AI demonstrated through relevant projects or research.
• Strong communication and interpersonal skills to collaborate effectively with cross-functional teams.
• Strong programming skills in languages such as Python or Rust.
• Experience in designing and implementing scalable machine learning pipelines for model training, validation, and deployment.
• Experience with cloud AI services (AWS / Azure / GCP)
• Experience managing and deploying model registry and feature store technologies.
• Experience with one or more data-oriented workflow orchestration frameworks (Kube Flow, Airflow, Argo, etc.).
• Experience working with containerization technologies such as Docker and Kubernetes.
• Experience putting Deep Learning models into production with frameworks such as Pytorch or Tensorflow.
• Experience developing REST APIs using frameworks such as FastAPI or similar.
• Experience developing GenAI agents using libraries such as Lang Chain or similar.
• Experience in evaluating LLM agents, LLM observability, and agent memory management.
• Experience with infrastructure-as-code (IaC) tools such as Terraform.

• Experience of deploying LLM models on premise
• GCP Professional Machine Learning Engineer certification (not older than a year)
• Experience with data science projects
• Industry knowledge in retail, manufacturing, healthcare, energy, finance or telecom

• Execution and guidance of technical POCs and projects
• Consulting, discovery phases and suggestions for executing the MLOps projects by following best practices and latest advancements in the field
• Cooperating on presales and upsales with rest of the team