Machine Learning Engineer/Data Scientist - ML, Data Science, Python, AI, Engineer, ML Ops
Posted 1 week 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 desired, along with cloud engineering experience. Additional preferred skills include exposure to GenAI/NLP, MLflow, Jenkins, and workflow automation.
Key Responsibilities:
- Develop and deploy machine learning models.
- Utilize Python and relevant data libraries for data analysis and model building.
- Implement CI/CD and DevOps practices in the ML life cycle.
- Collaborate on web server and API designs for ML model deployments.
- Engage in cloud engineering tasks, particularly with AWS and Databricks.
- Contribute to workflow automation and model explainability efforts.
Key Skills:
- Strong understanding of Data Science and Machine Learning.
- Proficiency in Python and relevant data libraries.
- Experience with ML Ops, CI/CD, and DevOps.
- Familiarity with cloud platforms, particularly AWS and Databricks.
- Exposure to GenAI/NLP, MLflow, Jenkins, and AutoML.
- Knowledge of unit testing and model explainability.
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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