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Founding Machine Learning Engineer

Heart Mind Talent
Glasgow
7 months ago
Applications closed

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Founding Machine Learning Engineer

Founding Machine Learning Engineer

Founding Machine Learning Engineer

Founding Machine Learning Engineer

Founding Machine Learning Engineer

Founding Machine Learning Engineer

As our Founding Engineer with a specialization in machine learning data engineering and model implementation, you'll have great experience building data pipelines and distributed processing systems. You’ll be responsible for designing and implementing robust, scalable systems, and efficient distributed processing frameworks that will power our core product.


We are a VC backed, remote-first business looking to complete our Founding Team.


Why Join Us:

  • Ambitious Challenges: We are using Generative AI (LLMs and Agents) to solve some of the most pressing challenges in cybersecurity today. You’ll be working at the cutting edge of this field, aiming to deliver significant breakthroughs for security teams.
  • Expert Team: We are a team of hands-on leaders with deep experience in Big Tech and Scale-ups. Our team has been part of the leadership teams behind multiple acquisitions and an IPO.
  • Impactful Work: Cybersecurity is becoming a challenge to most companies and helping them mitigate risk ultimately helps drive better outcomes for all of us.


What You Need to Be Successful:

  • Extensive Experience in backend development: Strong proficiency in backend languages and frameworks such as Python, Java, Go, or Node.js, and experience with building microservices.
  • Data Pipeline Mastery: Expertise in building and optimizing data pipelines using tools like Apache Kafka, Apache Spark, or AWS Glue.
  • Distributed Systems Knowledge: Experience designing and implementing distributed systems for parallel data processing, with a strong understanding of tools like Hadoop, Spark, or Flink.
  • Database Proficiency: Deep knowledge of both relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., Cassandra, MongoDB), with experience in designing scalable database architectures.
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