ML Engineer

100% remote B2B: 190-200 zł/h netto + VAT Role description: As an ML Engineer, you will be responsible for deploying, managing, and optimizing AI/ML models in production environments. You will work closely with data scientists, software engineers, and IT teams to ensure the seamless integration and operation of AI/ML solutions. Your role will be crucial in operationalizing AI models, ensuring they are scalable, reliable, and deliver value to the business. Responsibilities: • Design, implement, and maintain end-to-end MLOps pipelines for deploying machine learning models into production. • Collaborate with data scientists to understand model requirements and ensure smooth deployment and integration. • Develop and manage infrastructure for model training, validation, deployment, monitoring, and retraining. • Implement CI/CD pipelines to streamline the deployment and updates of AI/ML models. • Ensure the scalability, reliability, and performance of deployed models through continuous monitoring and optimization. • Utilize containerization and orchestration tools (e.g., Docker, Kubernetes) to manage model deployment environments. • Work with cloud platforms (AWS, GCP, Azure) to deploy and manage AI/ML services. • Implement security best practices for AI/ML models and data pipelines. • Troubleshoot and resolve issues related to model deployment and operation. • Stay updated with the latest MLOps tools, frameworks, and methodologies. • Document processes, configurations, and procedures to ensure knowledge sharing and continuity. Requirements: • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. • Proven experience (4+ years) in deploying machine learning models in production environments. • Strong understanding of machine learning, deep learning, NLP, and generative AI techniques. • Proficiency with MLOps tools and frameworks such as MLflow, Kubeflow, TensorFlow Extended (TFX), or similar. • Experience with CI/CD tools such as Jenkins, GitLab CI, or CircleCI. • Proficiency in programming languages such as Python and familiarity with ML/DL frameworks like TensorFlow, PyTorch, and scikit-learn. • Experience with cloud platforms (AWS, GCP, Azure) and their AI/ML services. •Knowledge of containerization and orchestration tools (Docker, Kubernetes). • Strong understanding of version control systems (e.g., Git) and collaborative development workflows. • Excellent problem-solving skills and the ability to design robust, scalable MLOps solutions. • Strong communication skills, with the ability to collaborate effectively with cross-functional teams. What we offer: • 100% remote • Multisport card • Private healthcare • Life insurance