Protections - Senior Machine Learning Engineer

Distributed, AMER | Distributed, EMEA

Full Time Senior-level / Expert
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Posted 3 weeks ago

The Elastic Security Data Science team is looking for a Senior ML Engineer to develop model pipelines to support our supervised and unsupervised machine learning technologies. These models detect and prevent malicious activity across Windows, macOS, and Linux endpoints and identify anomalous events in the Elastic Security product. We value autonomy, curiosity, fastidiousness, and questioning the status quo. You will collaborate with the broader Elastic Protections team, a diverse set of security researchers and data engineers who lend domain expertise to work with you to solve creative security problems.

Your responsibilities:

  • Working as part of the Protections team at Elastic, with other machine learning authorities, data engineers, and security researchers
  • Your primary focus will be leading the development of scalable, reproducible ML pipelines to support Elastic Security’s malware detection and anomaly detection features.
  • Introduce best practices and testing standards to increase robustness across all deployed models.
  • Work with data engineers to optimize processes for rapid prototyping of ML features: including data ingest, cleaning, featurization, and model training.
  • Deploy models under scalability, resource constraints, and efficacy requirements.
  • Gather implicit and explicit feedback from the platform we can collect to improve model performance over time.
  • Design and develop data-driven solutions that can run on millions of endpoints, cloud-based infrastructure, or the Elastic SIEM.

Skills you will bring

  • 5+ years machine learning experience; strong preference for a focus on delivering models to production environments.
  • Working knowledge of deep learning, clustering, and graph algorithms
  • Experience with machine learning pipeline technologies such as Airflow, Pachyderm, Prefect, etc. 
  • Experience using or developing data pipelines, including the collection, normalization, storage, and API access of complex event data
  • Proficient Python programming skills and experience using ML-related libraries
  • Ability to synthesize evaluation metrics, customer feedback, and internal analysis to tell a clear story of model performance
  • Enthusiasm for providing novel contributions to the information security research community on machine learning techniques
  • Ability to work in a fast-paced and highly autonomous environment

Engineering Philosophy

Engineering a highly complex distributed system that is easy to operate via elegantly designed APIs is a non-trivial effort. It requires solid software development skills, and more importantly, a sharp mind and the ability to think like a user. We also care deeply about giving you full ownership of what you’re working on. Our company fundamentally believes great minds achieve greatness when they are set free and are surrounded and challenged by their peers, which is clearly visible in our organization. At Elastic, we effectively don’t have a hierarchy to speak of. We feel that anyone needs to be in the position to comment on truly anything, regardless of his or her role within the company.

 

Job tags: Airflow API APIs Cloud-based Customer feedback Data-driven Elastic Linux Machine Learning MacOS ML Python Research Security Training Windows
Job region(s): Africa Europe Middle East North America South America
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