Machine Learning Engineer – MLOps

About the role

Langan is looking for a Machine Learning Engineer with a focus on MLOps to join its Information Technology team. The role involves building, deploying, and maintaining scalable machine‑learning systems that support the firm’s engineering and consulting projects.

Key responsibilities

• Design and implement ML infrastructure frameworks and tools to accelerate model development.
• Champion model observability, monitoring, and feedback loops for continuous performance.
• Create and maintain automated pipelines for training, evaluation, versioning, and deployment.
• Collaborate with data scientists and engineers to define requirements and deliver high‑impact solutions.
• Enforce model governance, validation standards, and reproducibility.
• Identify and resolve bottlenecks in ML workflows to improve reliability and latency.
• Leverage AI‑assisted and LLM‑based tools to automate development processes.

Required profile

• Bachelor’s degree in Computer Science, Software Engineering, Machine Learning, Statistics, or a related field.
• 8+ years of software engineering experience with large‑scale system design and ML systems.
• Strong experience with Microsoft Azure, distributed systems, and SQL/NoSQL databases.

Required skills

• Python programming.
• Azure Machine Learning, MLflow, Kubeflow.
• TensorFlow, PyTorch, scikit‑learn.
• CI/CD for ML: Azure DevOps, GitHub Actions, ArgoCD.
• Data orchestration: Azure Data Factory, Airflow, Prefect.
• SQL and NoSQL database technologies.