Senior Machine Learning Engineer
Core
Design, develop, and maintain scalable data pipelines, ML services, and cloud infrastructure to power ML-based products and ensure seamless integration with the data ecosystem.
Role type
Senior Machine Learning Engineer (MLOps & Infrastructure)
Builds
High-performing data pipelines, machine learning services, APIs, and production-ready ML solutions
Domain
Financial services / Tax & Accounting / Machine Learning Infrastructure
Deliverable
production ML models
Required skills
Python, end-to-end ML pipelines, MLOps frameworks (MLFlow, KubeFlow), AWS SageMaker, SQL/NoSQL, Docker, Kubernetes, CI/CD for ML, model lifecycle management
Preferred skills
Computer Vision, NLP, deep learning frameworks (TensorFlow, PyTorch), Scikit-Learn, Pandas, Infrastructure as Code (Terraform, CloudFormation), asynchronous messaging, observability tools
Technologies
Python, MLFlow, KubeFlow, AWS SageMaker, Docker, Kubernetes, Terraform, CloudFormation, TensorFlow, PyTorch, Scikit-Learn, Pandas
Responsibilities
Plan, design, and maintain scalable data pipelines and ML infrastructure; Lead development and deployment of ML services and APIs; Implement code quality standards and testing frameworks; Collaborate with Data Scientists to translate models into production solutions; Drive MLOps best practices including CI/CD; Troubleshoot production issues; Evaluate new technologies and drive technical decisions
Seniority
Senior, hands-on IC with leadership responsibilities