Machine Learning Engineer

DEVI TECHNOLOGIES LIMITED; Birmingham; On-site; GBP 50,000 - 70,000; Full time

Job summary

A tech solutions company in Birmingham seeks a Machine Learning Engineer to design, develop, and implement machine learning models for various applications. Responsibilities include cleaning and transforming datasets, deploying models, and collaborating closely with teams. Knowledge of tools like TensorFlow, Docker, and cloud platforms is essential. This position offers opportunities to stay updated with the latest AI techniques and ensure model accuracy and relevance.

Responsibilities

• Design, develop, and implement machine learning models for various applications.
• Clean, preprocess, and transform large datasets from diverse sources.
• Choose appropriate algorithms based on business goals and optimize models.
• Deploy models into production environments and integrate with existing systems.
• Monitor model performance post-deployment and update models as needed.
• Collaborate with data scientists, software engineers, and stakeholders.

Skills

Machine learning

Data preprocessing

Algorithm optimization

API integration

Model performance monitoring

Team collaboration

Documentation

Tools

TensorFlow

PyTorch

Scikit-learn

XGBoost

Docker

Kubernetes

AWS

GCP

Azure

Job description

Responsibilities

• Design, develop, and implement machine learning models for various applications such as classification, regression, clustering, and recommendation systems.
• Clean, preprocess, and transform large datasets; work with structured and unstructured data from diverse sources.
• Choose appropriate algorithms based on business goals, and optimize models for performance, scalability, and accuracy.
• Deploy models into production environments and integrate with existing systems via APIs or pipelines using tools like Docker, Kubernetes, or cloud platforms (AWS, GCP, Azure).
• Monitor model performance post-deployment and retrain/update models as needed to maintain accuracy and relevance.
• Work closely with data scientists, software engineers, product managers, and stakeholders to define project goals and deliverables.
• Stay up to date with the latest ML/AI research and incorporate cutting-edge techniques and frameworks when applicable.
• Utilize ML libraries and tools such as TensorFlow, PyTorch, Scikit-learn, XGBoost, and others for model building and experimentation.
• Ensure machine learning solutions are scalable and optimized for performance on large datasets or real-time systems.
• Maintain clear documentation of model development, data workflows, and experiments for reproducibility and future reference.
• Adhere to data privacy laws, model explainability standards, and ethical AI practices in all stages of ML development.