Jobs Senior Machine Learning Engineer, LONDON #9887715

180 Media Group; London; On-site; GBP 70,000 - 100,000; Full time

Job summary

A leading company in the software development industry is seeking a Senior Machine Learning Engineer to enhance their MLOps strategy. This role involves developing and deploying machine learning models, managing cloud infrastructure, and collaborating with cross-functional teams to drive innovation and efficiency in model performance. Ideal candidates will have extensive experience in cloud platforms and a strong foundation in MLOps principles.

Qualifications

• 5+ years of experience as a Machine Learning Engineer.
• Proficient in cloud platforms, preferably Google Cloud Platform.
• Strong knowledge of MLOps principles and tools.

Responsibilities

• Lead the implementation of MLOps strategy and best practices.
• Create and train machine learning models for business problems.
• Design infrastructure for scalable model deployment.

Skills

MLOps

Machine Learning

Cloud Platforms

CI/CD

Terraform

Kafka

Docker

Kubernetes

LangChain

Real-time Data Streaming

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

Terraform

Docker

Kubernetes

Kubeflow

Apache Airflow

Job description

Jobs Senior Machine Learning Engineer, LONDON #9887715

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Jobs Senior Machine Learning Engineer, LONDON #9887715

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• Lead the implementation and continuous improvement of our MLOps strategy, establishing best practices for model development, deployment, and monitoring.
• Creating and training machine learning models to solve specific business problems, such as product recommendations, customer segmentation, and demand forecasting. Implementing such models into production systems to make predictions, drive real-time personalisation and support decision-making.
• Design and build the necessary infrastructure and tooling to support efficient and scalable model deployment, including CI/CD pipelines and automated testing.
• Implement and own Terraform to manage and provision our cloud infrastructure for machine learning operations.
• Oversee the transition to a real-time streaming architecture for our machine learning applications, ensuring efficient data ingestion, feature engineering, and model serving in a streaming context.
• Develop and implement a comprehensive monitoring framework to track model performance, identify potential issues, and ensure optimal model health in production. Monitoring model performance and updating them as needed to adapt to new data and changing conditions.
• Collaborate closely with data scientists and engineers to ensure seamless integration of models into our existing systems and workflows. Stay abreast of the latest MLOps trends and technologies to continuously improve our processes and tools.
  
  

Country : United Kingdom

Region : London

County : Greater London

Category : IT - Web

Contract type : Permanent

Availability : Full time

Job Description

In short Your Mission

• Lead the implementation and continuous improvement of our MLOps strategy, establishing best practices for model development, deployment, and monitoring.
• Creating and training machine learning models to solve specific business problems, such as product recommendations, customer segmentation, and demand forecasting. Implementing such models into production systems to make predictions, drive real-time personalisation and support decision-making.
• Design and build the necessary infrastructure and tooling to support efficient and scalable model deployment, including CI/CD pipelines and automated testing.
• Implement and own Terraform to manage and provision our cloud infrastructure for machine learning operations.
• Oversee the transition to a real-time streaming architecture for our machine learning applications, ensuring efficient data ingestion, feature engineering, and model serving in a streaming context.
• Develop and implement a comprehensive monitoring framework to track model performance, identify potential issues, and ensure optimal model health in production. Monitoring model performance and updating them as needed to adapt to new data and changing conditions.
• Collaborate closely with data scientists and engineers to ensure seamless integration of models into our existing systems and workflows. Stay abreast of the latest MLOps trends and technologies to continuously improve our processes and tools.
  
  

Your story

• You have 5+ years of experience as a Machine Learning Engineer with a strong focus on MLOps. You have a proven track record of successfully deploying and managing machine learning models in production environments.
• You possess deep knowledge of MLOps principles, tools, and best practices.
• You are proficient in cloud platforms (Google Cloud Platform is preferred), infrastructure-as-code tools like Terraform
• You have experience with CI/CD pipelines, containerization technologies (e.g., Docker), and orchestration tools (e.g., Kubernetes) and using orchestration tools such as Kubeflow (our preferred tool) or similar frameworks like Apache Airflow to manage and automate ML workflows.
• You have experience with real-time data streaming technologies such as Kafka and Confluent and feature stores in such settings.
• You are skilled in building and maintaining monitoring systems for machine learning models.
• You have excellent communication and collaboration skills, enabling you to effectively work with cross-functional teams.
• Knowledge of frameworks such as LangChain used to orchestrate LLMs
• Experience in LLM evaluations, debugging and monitoring using tools such as LangFuse or LangSmith

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

Job function

• Job function

  Information Technology

• Industries

  Software Development

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