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Machine Learning Engineer (Visa Sponsorship Available)

Techwaka

City of Edinburgh

Hybrid

GBP 60,000

Full time

18 days ago

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Job summary

Techwaka is seeking a Machine Learning Engineer to join their MLOps team in Edinburgh. The role involves deploying and maintaining ML models, optimizing workflows, and collaborating with cross-functional teams to achieve business objectives. Ideal candidates will have a strong technical background, hands-on experience with cloud platforms, and excellent problem-solving skills.

Benefits

Flexible Working Options
Competitive Compensation Package + Bonus
25 Days Holiday Per Year (increasing to 28 after 2 years)
2 Paid Volunteering Days Per Year
Learning & Development Opportunities
Pension & Life Insurance
Health Cash Plan & Online GP services
Paid Parental Leave
Season Ticket Loan & Cycle-to-Work Scheme
Discounted Gym Membership
Central Office Location with complimentary snacks
Relocation Assistance & Work Visa Sponsorship
Employee Assistance Programme (EAP)
Company Events

Qualifications

  • 3+ years of experience in deploying and maintaining machine learning models
  • Strong coding skills in Python
  • Experience with cloud platforms and CI/CD processes

Responsibilities

  • Deploy machine learning models and ensure quality and scalability.
  • Build and maintain model pipelines and design CI/CD for ML.
  • Monitor models in production for performance and reliability.

Skills

Machine Learning
Python
CI/CD pipelines
Cloud platforms
Containerization
Data processing
Problem-solving
Communication

Education

Bachelor's degree in Computer Science, Data Science, or related field

Tools

TensorFlow
PyTorch
scikit-learn
Docker
Apache Beam/Dataflow

Job description

£60k per annum

As aMachine Learning Engineer, you will be part of an MLOps team, working alongside data scientists, software engineers, and other stakeholders to bring machine learning models to life. You will be responsible for deploying, maintaining, and monitoring models in production, improving model performance, and refining the machine learning infrastructure to support business objectives. Your role will also involve optimizing workflows, integrating CI/CD pipelines, and ensuring the scalability and reliability of AI-driven solutions.

Key Responsibilities:

  • Model Deployment: Collaborate with data scientists to deploy machine learning models, ensuring quality and scalability.
  • Pipeline Development: Build and maintain model pipelines to integrate with existing systems and workflows.
  • CI/CD for ML: Design and implement continuous integration and delivery pipelines for efficient model deployment.
  • Model Monitoring: Monitor machine learning models in production, ensuring ongoing performance and reliability.
  • Collaboration: Work with cross-functional teams to design solutions that align with business objectives and best practices in machine learning.
  • Optimization: Continuously improve machine learning infrastructure and production workflows.
  • Strong technical foundation in machine learning and software engineering
  • Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn)
  • Experience with cloud platforms (AWS, GCP, Azure)
  • Experience with CI/CD pipelines for machine learning (e.g., Vertex AI)
  • Familiarity with data processing tools like Apache Beam/Dataflow
  • Strong understanding of monitoring and maintaining models in production environments
  • Experience with containerization tools (e.g., Docker)
  • Problem-solving skills with the ability to troubleshoot model and pipeline issues
  • Strong communication skills for cross-team collaboration
Requirements
  • Bachelor's degree in Computer Science, Data Science, or a related field
  • 3+ years of experience in deploying and maintaining machine learning models
  • Experience with cloud platforms, model pipelines, and CI/CD processes
  • Strong coding skills in Python
Benefits
  • Flexible Working Options: Including hybrid and remote options
  • Competitive Compensation Package + Bonus
  • 25 Days Holiday Per Year(increasing to 28 after 2 years)
  • 2 Paid Volunteering Days Per Yearfor giving back to causes you care about
  • Learning & Development Opportunities: Access to industry training through learning platforms
  • Pension & Life Insurance
  • Health Cash Plan & Online GPservices
  • Paid Parental Leave
  • Season Ticket Loan & Cycle-to-Work Scheme
  • Discounted Gym Membership
  • Central Office Locationwith complimentary snacks and refreshments
  • Relocation Assistance & Work Visa Sponsorshipfor international talent
  • Employee Assistance Programme (EAP)
  • Company Events: Regular social events, team-building activities, and access to over 4,000 deals and discounts on travel, electronics, fashion, and more.
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