Job Description
Job Profile: Senior MLOps Engineer
About the Project
LSEG is a leading global financial markets infrastructure and data provider. The?Content Amplify?project is at the forefront of transforming unstructured financial narratives into structured, accessible data using cutting-edge AI technologies.
Our mission is to?amplify human-in-the-loop efforts, enabling ML and LLM models to learn from subject matter expert feedback in a scalable, iterative process.
This includes leveraging?ML-Ops,?cloud-native architectures, and?innovative feedback loops?to continuously improve data quality, speed, and scope.
Key Responsibilities
- Develop scalable and maintainable Python-based backend systems.
- Build and optimize APIs and services using frameworks like Flask or Django.
- Collaborate with cross functional teams including Data Scientists, DevOps, Architecture, QA, Cyber Security etc. to integrate classic ML and LLM models into production workflows.
- Design and maintain efficient database schemas and queries.
- Implement security and data protection best practices.
- Debug, test, and improve existing systems.
- Support production systems and ensure high availability.
- Take full ownership of design initiatives — from concept to task breakdown.
- Ensure system reliability, fault tolerance, and performance optimization.
Required Experience & Skills
Must-Have:
- 5+ years of experience as a Python developer.
- Proficiency in at least one Python web framework (Flask, Django).
- Strong understanding of ORM tools and relational databases.
- Experience with cloud platforms (Azure preferred, AWS acceptable).
- Solid SQL skills and query optimization techniques.
- Bachelor's degree in Computer Science, Engineering, or equivalent.
- Excellent problem-solving and collaboration skills.
- Experience with Kubernetes (EKS), Docker, and CI/CD pipelines.
- Experience building scalable data pipelines and integrating with ML workflows.
Nice-to-Have:
- Experience with big data technologies (Snowflake preferred).
- Familiarity with ML libraries (scikit-learn, pandas, PySpark, PyArrow).
- Ability to design and optimize database performance.
- Prior collaboration with Data Science teams.
Soft Skills
- Energetic, open-minded, and creative.
- Strong self-learning ability.
- Team player with excellent communication skills.
- Flexible and adaptable to change.
- Independent and proactive.
