AI Data Engineer

Aurum Search Limited; Greater London; On-site; GBP 50,000 - 120,000; Full time

Job summary

Join a leading multi-strategy systematic hedge fund in London as an AI Data Engineer. This exciting role involves designing and optimizing data infrastructure to support AI and machine learning initiatives that drive innovative trading strategies. You will work with a talented team of quantitative researchers and engineers, developing scalable data pipelines and automating processes to enhance efficiency. If you're passionate about leveraging advanced technology and data in finance, this is an opportunity to make a significant impact in a collaborative and dynamic environment.

Qualifications

• 3+ years of experience in data engineering focused on AI/ML.
• Proven experience in building data pipelines for production environments.
• Strong understanding of relational and NoSQL databases.

Responsibilities

• Design and maintain scalable data pipelines for AI applications.
• Implement automation processes for data ingestion and model deployment.
• Collaborate with AI/ML engineers to ensure data integration.

Skills

Python

SQL

Data Engineering

Machine Learning

Data Automation

Education

Bachelor's in Computer Science

Master's in Data Science

Ph.D. in Engineering

Tools

Apache Spark

Hadoop

AWS S3

Google Cloud Storage

TensorFlow

PyTorch

Docker

Kubernetes

Job description

Direct message the job poster from Aurum Search Limited

We are a leading multi-strategy systematic hedge fund based in London, leveraging advanced technology and data to drive our trading strategies. Our team includes top quantitative researchers, data scientists, and engineers, all collaborating to develop innovative solutions. We are seeking an AI Data Engineer to join our team, focusing on building and automating data systems that support AI-driven initiatives.

Role Overview:

As an AI Data Engineer, you will be responsible for designing, building, and optimizing data infrastructure to support AI and machine learning initiatives within our trading strategies. You will develop and maintain data pipelines, ensure seamless data integration for AI models, and automate processes to improve efficiency. Your role will be pivotal in enabling the successful deployment and operation of AI-driven trading models.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines that process large volumes of financial and alternative data for AI and machine learning applications. Ensure real-time data availability and integration with AI models.
• Build and optimize the data infrastructure that supports AI/ML models, including data storage, processing, and retrieval systems. Ensure data is accessible, clean, and ready for AI-driven analysis.
• Implement and refine automation processes for data ingestion, transformation, and model deployment. Focus on reducing manual intervention and improving the efficiency of AI workflows.
• Work closely with AI/ML engineers, data scientists, and quantitative researchers to understand data requirements and ensure seamless integration of data into AI-driven models and strategies.
• Continuously monitor and enhance the performance, scalability, and reliability of data systems. Apply best practices in data engineering to ensure high-quality data and robust AI model performance.
• Stay updated on the latest trends and technologies in AI data engineering and apply them to enhance our data infrastructure and AI capabilities.
• Collaborate with the engineering team to deploy AI data systems into production, ensuring they meet the low-latency and high-reliability demands of our trading operations.

Qualifications:

• Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, Data Science, or a related field.
• 3+ years of experience in data engineering, with a focus on AI and machine learning applications, preferably within the finance or hedge fund industry.
• Proven experience in building and maintaining data pipelines for AI/ML models in a production environment.
• Experience with data automation, ETL processes, and AI-driven data architecture design.

Technical Skills

• Proficiency in Python and SQL, with experience in data processing frameworks such as Apache Spark or Hadoop.
• Strong understanding of relational and NoSQL databases, as well as cloud-based data storage solutions (e.g., AWS S3, Google Cloud Storage).
• Experience with AI/ML tools and frameworks (e.g., TensorFlow, PyTorch) and integrating data pipelines with these tools.
• Familiarity with containerization technologies (e.g., Docker, Kubernetes) and cloud platforms (e.g., AWS, GCP, Azure).
• Strong programming and scripting skills, with the ability to write clean, maintainable code.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  Capital Markets, Investment Management, and Financial Services

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