Machine Learning Engineer

Exoeris
London
2 months ago
Applications closed

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Machine Learning Engineer

Machine Learning Engineer / MLOps Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

We are seeking exceptional individuals who are passionate about software development, large-scale data analytics, and driving AI-led innovation within organizations.

Ideal candidates will demonstrate:

  • 4+ years of experience in a technology consulting environment
  • Strong ability to apply software development best practices and standards to build robust, maintainable solutions
  • Hands-on involvement throughout the entire software development lifecycle
  • Proven experience in guiding non-technical teams and consultants on best practices for scalable and reliable software development
  • Expertise in optimizing algorithms and software design for computational efficiency
  • Motivation to thrive in a fast-paced, client-focused environment, engaging directly with clients to shape new features for future product releases
  • A collaborative mindset, eager to share ideas and co-create solutions within teams
  • A natural problem-solver with intellectual curiosity across diverse industries and topics
  • Master’s degree or PhD in a relevant field (please provide all academic certificates, including A-level, Bachelor, Master, and PhD, with final grades)

Additional Responsibilities:

  • Design and build data & AI platforms for clients, enabling data and generative AI capabilities across multiple use cases and organizational functions
  • Contribute to large-scale AI transformation programs, often as part of strategic journeys led by BCG
  • Work across key engineering disciplines:
  • Cloud Engineering
  • Data Engineering (framework design, not just pipelines)
  • DevOps
  • MLOps / LLMOps

Technologies you’ll often work with:

  • Cloud Platforms: Azure, AWS, GCP
  • Data Tools: Airflow, dbt, Databricks, Snowflake
  • Developer Tooling & CI/CD: GitHub, Azure DevOps, Terraform (or other Infrastructure-as-Code tools)
  • MLOps / LLMOps Frameworks: MLflow, AzureML, LangSmith, La

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