Machine Learning Engineer/Data Scientist - ML, Data Science, Python, AI, Engineer, ML Ops
Posted 1 day ago by Scope AT Limited
Negotiable
Undetermined
Undetermined
Bank, London, UK
Summary: A leading global payment domain firm is seeking a Machine Learning Engineer/Data Scientist to join their team in central London. The ideal candidate will possess a strong understanding of Data Science, Python, AI, ML Ops, CI/CD, DevOps, and the ML life cycle. Familiarity with web server and API designs for ML model deployments is also desirable. Additional preferred skills include cloud engineering experience and exposure to various ML tools and methodologies.
Key Responsibilities:
- Develop and deploy machine learning models and solutions.
- Utilize Python and relevant data libraries for data analysis and model building.
- Implement CI/CD and DevOps practices in the ML life cycle.
- Collaborate with cross-functional teams to integrate ML solutions into existing systems.
- Maintain and optimize ML models in production environments.
Key Skills:
- Strong understanding of Data Science and Machine Learning principles.
- Proficiency in Python and relevant data libraries.
- Experience with ML Ops and CI/CD practices.
- Familiarity with cloud platforms such as AWS and Databricks.
- Exposure to GenAI/NLP, MLflow, Jenkins, and workflow automation.
Salary (Rate): undetermined
City: London
Country: UK
Working Arrangements: undetermined
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Machine Learning Engineer/Data Scientist - ML, Data Science, Python, AI, Engineer, ML Ops
A leading global payment domain firm are looking for a new ML Engineer to join their central London based team. This individual will need to have a strong understanding of Data Science, Python, AI, ML Ops, CI/CD, DevOps and the ML life cycle.
In addition some good to haves are:
-Familiar with Web Server and API designs for ML model deployments
-Strong Python skills, including relevant data libraries
-Cloud engineering experience: AWS, Databricks
-Other preferred exposure: GenAI/NLP, MLflow, Jenkins, workflow automation, AutoML, unit testing, model explainability
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