Staff Full Stack Machine Learning Engineer

hace 1 mes

Córdoba, Córdoba, España Proofpoint A tiempo completo

We are seeking a highly skilled Staff Full-Stack Machine Learning Engineer to join our unified Scrum team.

This team is responsible for everything from ETL processes and Data Science to MLOps, in an end-to-end framework.

In this multifaceted role, you'll serve as both a technical linchpin and a mentor, steering best practices throughout the complete machine learning lifecycle.

Responsibilities will include building and maintaining data pipelines, ensuring a seamless data flow for our machine learning models, and translating project management requirements into actionable ML initiatives.

As a key member of our team, you'll work closely with members specializing in data science, MLOps, and ETL to ensure our models are well-crafted, scalable, and operationally sound.

Our ideal candidate is proficient in the entire ML pipeline but excels particularly in machine learning aspects.

Exposure to the challenges of adversarial machine learning would be a plus.

As a leader, you'll foster a culture of best practices within our comprehensive machine learning Scrum team.

You'll guide us in constructing systems resilient to adversarial attacks, enhancing the reliability and safety of our solutions.

Proactively identifying areas for improvement, you will propose actionable solutions and lead our focused team in executing them for operational excellence.

Day-to-day, you'll collaborate closely with other data scientists to ensure that machine learning models are not just theoretically sound but also practical for scalable, real-world applications.

You may also spend time reviewing code, running tests, and debugging issues that arise in different parts of the ML pipeline.

As someone responsible for mentoring and leading best practices, you'll frequently consult with team members to help them overcome technical challenges.

This might involve one-on-one mentoring or leading focused group discussions to resolve complex issues.

Given your expertise in cloud platforms like AWS, part of your day might also be spent deploying models to production environments, setting up monitoring systems, or automating workflows using MLOps best practices.

Your days will be a blend of hands-on coding, team collaboration, problem-solving, and leadership activities, all aimed at achieving operational excellence and pushing the boundaries of what our machine learning systems can do.

Desired Skills:

  • Strong proficiency in Python and/or PySpark, coupled with hands-on experience in machine learning frameworks like TensorFlow or PyTorch.
  • Experience with large language models like BERT, GPT, or similar, as well as off-the-shelf ML algorithms.
  • Expertise in cloud computing platforms, especially AWS services like EC2, S3, Lambda, Glue, and particularly SageMaker, for building, deploying, and scaling machine learning solutions.
  • In-depth understanding of ETL processes, including data collection, cleaning, and transformation to ensure effective data pipelines.
  • Demonstrated leadership in promoting best practices in MLOps, including CI/CD, model versioning, and monitoring for operational excellence.
  • Familiarity with adversarial machine learning, including an understanding of related security considerations, model robustness, and data integrity.

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