Senior Machine Learning Engineer

4 weeks ago

London, Greater London, United Kingdom Accolite Full time
Job Title: Lead/Senior Machine Learning Engineer

We are seeking a highly skilled and experienced Lead/Senior Machine Learning Engineer to join our team at Accolite. As a key member of our data science team, you will play a critical role in operationalizing machine learning models, ensuring their quality, and driving business outcomes.

Key Responsibilities:
  • Conduct reviews of machine learning models to ensure compliance with platform governance principles, including versioning, data/model lineage, and code best practices.
  • Develop pipelines for continuous operation, feedback, and monitoring of machine learning models, leveraging best practices from the CI/CD vertical within the MLOps domain.
  • Optimize AI development environments for usability, reliability, and performance.
  • Collaborate with infrastructure and application development teams to integrate machine learning models into enterprise applications.
  • Work with data engineers to ensure data storage and pipelines are working as intended.
  • Evaluate open-source and AI/ML platforms and tools for feasibility of usage and integration from an infrastructure perspective.
Requirements:
  • At least 10 years of experience as a machine learning engineer, working with Python, ML libraries, and large-scale data processing frameworks.
  • Advance proficiency in Python used for machine learning and automation tasks.
  • Experience working with machine learning libraries such as Pandas, NumPy, H2O, or TensorFlow.
  • Experience working with large-scale data processing frameworks, such as Hadoop, Spark, or Dask.
  • Knowledge of OpenShift/Kubernetes is a must-have.
  • Good knowledge of Bash and Unix/Linux command-line toolkit is a must-have.
  • Hands-on experience building CI/CD pipelines orchestration using Jenkins, GitLab CI, GitHub Actions, or similar tools.
  • Knowledge in the operationalization of data science projects (MLOps) using at least one popular framework or platform.
  • Knowledge of workflow orchestrator, such as Airflow or Ctrl-M.
  • Knowledge of logging and monitoring tools, such as Splunk and Geneos.
  • Experience in defining processes, standards, frameworks, prototypes, and toolsets in support of AI and ML development, monitoring, testing, and operationalization.
  • Experience in ML operationalization and orchestration (MLOps) tools, techniques, and platforms.
Soft Skills:
  • Good knowledge of DevOps process and principles.
  • Strong software engineering fundamentals.
  • Excellent communication skills.
  • Attention to detail.
  • Analytical mind and problem-solving aptitude.
  • Strong organizational skills.
  • Visual thinking.

We are looking for a highly motivated and experienced professional who can drive business outcomes through the effective operationalization of machine learning models. If you have a passion for machine learning and a strong background in software engineering, we encourage you to apply for this exciting opportunity.

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