Machine Learning Data Engineer

Project - the aim you'll have

Our client is pioneering personalized wellness through innovative technology. Their team is committed to enhancing healthcare experiences using cutting-edge AI. They value creativity, collaboration, and the drive to revolutionize personal wellness. Their culture thrives on innovation, continuous improvement, and pushing boundaries. Join their dynamic and rapidly growing team and be part of a journey that's reshaping the future of healthcare.

As an ML Data Engineer, you will be instrumental in building and optimizing data systems and infrastructure to support client's Machine Learning projects. You'll work closely with ML engineers to ensure that they have the clean, well-structured, and high-quality data necessary for developing cutting-edge AI models.

Position - how you'll contribute

• Processing (NLP), tailored to personalized healthcare applications.
• Design and implement robust data pipelines to collect, clean, and consolidate data from diverse sources.
• Enhance data quality and reliability to drive ML initiatives.
• Implement systems to monitor data quality, ensuring that our models have the best data available.
• Work with state-of-the-art data processing technologies to prepare and optimize data for machine learning.
• Collaborate with machine learning engineers and business units to understand and fulfill their data requirements.
• Being up to date with new ML practices such as GenAI, MLops, ML Inference, and GPU based training.

Requirements

Expectations - the experience you need

• BS/MS in Computer Science, Engineering, or a related field.
• 3+ years of experience in a data engineering role, specifically supporting machine learning data needs.
• Strong programming skills in Python and SQL, as well as experience with Scala or Java, are a plus.
• Experience with big data technologies such as Apache Spark, Hadoop, or similar frameworks.
• Knowledgeable in machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn).
• Proficient in managing and optimizing big data storage and data warehouse solutions.
• Excellent problem-solving skills and the ability to work in a dynamic and agile environment.