We're seeking a Machine Learning Engineer with strong data engineering expertise to build scalable real-time data pipelines and develop advanced ML models. This role involves collaborating with cross-functional teams to deliver innovative solutions.
Key Responsibilities:
- Data Engineering: Build and maintain real-time data pipelines and ETL workflows. Ensure data quality and integrity.
- Machine Learning: Design, train, and optimize ML models for fraud prevention and personalization.
- MLOps: Deploy, monitor, and maintain ML models in production using tools like Docker, Kubernetes, and cloud platforms (AWS/GCP).
- Data Analysis: Preprocess data, identify trends, and derive insights using clustering, classification, and anomaly detection techniques.
- Collaboration: Work with product managers, engineers, and data scientists to align technical solutions with business goals.
What We're Looking For:
- Experience: 2+ years in ML, data engineering, or related fields, with a focus on fraud detection or personalization.
Technical Skills:
- Proficiency in Python, SQL, and big data tools (e.g., Kafka, Spark).
- Strong knowledge of ML frameworks (TensorFlow, PyTorch).
- Experience with MLOps and cloud technologies (AWS/GCP).
- Analytical Skills: Strong understanding of statistical methods and data visualization tools (e.g., Pandas, Matplotlib).
- Mindset: Adaptable, innovative, and comfortable in a fast-paced environment.
Back to searchMachine Learning Engineer
Morson Talent
Posted 20 hours ago, valid for 21 days
London, Greater London E14, England
£60,000 - £90,000 per annum
Full Time
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Sonic Summary
- We are looking for a Machine Learning Engineer with strong data engineering skills to create scalable real-time data pipelines and advanced ML models.
- Candidates should have a minimum of 2 years of experience in machine learning, data engineering, or related fields, particularly in fraud detection or personalization.
- The role offers a competitive salary, which is commensurate with experience and expertise.
- Key responsibilities include building ETL workflows, deploying ML models, and collaborating with cross-functional teams to meet business objectives.
- Technical proficiency in Python, SQL, big data tools, and ML frameworks is essential for success in this position.
