MLOps Engineer

Cognism Limited is seeking an MLOps Engineer to join their growing Data team and to report to the Engineering Manager. The role focuses on optimizing and improving the quality of ML services and products, implementing machine learning platforms and best practices, particularly on AWS cloud.

• Strong understanding of AWS cloud architecture and services
• Experience deploying and monitoring classical Machine Learning models in production on AWS
• Good understanding of modern MLOps best practices
• Good understanding of core Machine Learning fundamentals including classical model training, evaluation, and feature engineering
• Experience serving models in production via model-serving runtimes such as ONNX Runtime, NVIDIA Triton, or TorchServe
• Experience with vector databases/approximate nearest neighbor search like Milvus, FAISS, or pgvector
• Good understanding of Data Engineering fundamentals
• Experience with Infrastructure as Code tools (Terraform, AWS CDK or similar)
• Experience with CI/CD pipelines (GitHub Actions, Circle CI or similar)
• Basic understanding of networking and security practices on cloud
• Experience with containerization (Docker, AWS ECS, Kubernetes or similar)
• Proficiency reading and writing Python code
• Experience with API deployment frameworks such as FastAPI
• Fluent in English with good communication skills
• Enthusiasm to learn and explore modern MLOps solutions

Ideal:

• 3+ years in an MLOps, Machine Learning Engineer, or DevOps role
• Ability to design and implement cloud solutions and build MLOps pipelines in AWS
• Good understanding of software development principles and DevOps methodologies
• Experience and understanding of MLOps concepts including experiment tracking, model registry/versioning, model and data drift monitoring
• Experience with GPU-based computational frameworks and cloud architectures
• Knowledge of MLOps and DevOps tools like Kubeflow, Metaflow, Airflow, Grafana, QuickSight, Coralogix, ELK stack
• Experience working with big data domains (10M+ scale)
• Experience with streaming and batch-processing frameworks

Bonus:

• Experience with MLOps platforms (Nvidia Triton, SageMaker, VertexAI, Databricks)
• Knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow
• Experience with SQL, NoSQL databases, and data lakehouse

• Build and manage automation pipelines to operationalize the ML platform, model training, and deployment on AWS
• Design and implement secure, reliable, scalable, and maintainable architectures and pipelines on AWS
• Operate, maintain, and evolve traditional ML systems in production including gradient-boosted trees, transformer classifiers, and NLP pipelines
• Contribute to MLOps best practices within the Science and Data team
• Act as a bridge between AI, Engineering, and DevSecOps for ML deployment, monitoring, and maintenance
• Collaborate with Data Scientists to provide tooling and integration of ML models into larger systems
• Monitor and maintain production-critical ML services and workloads at scale

The controller of your personal data is Cognism LTD, Prosta 20, 00-850 Warsaw, Masovian Voivodeship. Data processing is based on recruitment purposes compliant with GDPR. Providing mandatory data is required, other data is voluntary. Data retention is limited to recruitment duration and 24 months for future recruitment consent. You have rights to access, rectify, erase, restrict, port data, object, and lodge complaints. Consent withdrawal is possible any time without affecting prior processing.