MLOps Engineer designing and maintaining cloud infrastructure for large - scale computer vision model training. Collaborating with Data Scientists and AI Engineers to streamline model development lifecycle.
About the role
- MLOps Engineer ensuring production reliability and value of machine learning models. Focused on integration, monitoring, and assisting data scientists with model deployment.
Responsibilities
- Help ensure our machine learning models run reliably and add value in production.
- Focus on monitoring, maintaining, and integrating models into products.
- Assist data scientists in moving models from research into production.
Requirements
- Technical experience in data engineering or data science roles.
- An understanding of the machine learning development lifecycle, including model development, deployment, monitoring, and maintenance.
- Experience with Quantexa would be advantageous.
- Strong programming skills in Python and experience with common ML libraries.
- Experience with big data tools, such as Spark
- Experience with containerization and orchestration technologies like Docker, Helm, and Kubernetes.
- Familiarity with DevOps tools such as Jenkins, or similar for workflow automation.
- Experience deploying machine learning models into production and managing their lifecycle.
- Experience implementing model governance, including versioning, monitoring, drift detection, and reporting.
- Familiarity with MLOps tools such as MLflow, Kubeflow, or DVC.
- Programming skills in Scala.
- Experience working with ONNX and ONNX Runtime for model optimization and deployment.
- Experience mentoring or supporting colleagues to help them grow their technical skills.
Benefits
- Competitive salary
- Company bonus
- 25 days annual leave (with the option of buying up to 5 days, and rolling over up to 10), plus national holidays + your birthday off!
- Pension scheme with a company contribution of 6% (when you contribute 3%)
- Private Healthcare with AXA, including dental & optic cover
- Life Insurance and Income Protection
- Regularly bench-marked salary rates
- Enhanced Maternity, Paternity, Adoption, or Shared Parental Leave
- Well-being days
- Volunteer Day off
- Work from Home Equipment
- Commuter, Tech and cycle to work schemes
- Octopus EV Salary Sacrifice scheme
- Free Calm App Subscription #1 app for meditation, relaxation and sleep
- Continuous Training and Development, including access to Udemy Business
- Spend up to 2 months working outside of your country of employment over a rolling 12-month period with our ‘Work from Anywhere’ policy
- Employee Referral Program
- Team Social Budget & Company-wide Socials
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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