Senior ML Ops Engineer

Intellectual Capital Resources; Greater London; On-site; GBP 59,000 - 99,000; Full time

Job summary

Intellectual Capital Resources is seeking an experienced ML Engineer to own end-to-end production ML pipelines, collaborating with audio ML researchers and DSP engineers in a fast-growing audio AI company.

You will implement monitoring, CI/CD, and model lifecycle management, ensuring reproducibility and high-quality deployments across cloud, edge, and embedded environments.

Qualifications

• Proven experience building and operating production ML systems.
• Strong Python skills and experience with ML frameworks such as PyTorch or TensorFlow.
• Experience with MLOps, CI/CD, and model lifecycle management.
• Experience with cloud platforms such as AWS, GCP, or Azure, and with containers/Kubernetes.
• Experience with low-latency or real-time systems.
• Familiarity with audio or speech processing is a plus.
• Mentoring or technical leadership experience is desirable.

Responsibilities

• Own end-to-end ML pipelines from data through training, evaluation, and deployment.
• Work closely with audio ML researchers and DSP engineers to move models into production.
• Implement monitoring and CI/CD pipelines.
• Ensure reproducibility across the full model lifecycle.
• Help establish engineering standards across a small ML team through mentoring.

Skills

Production ML pipelines

Python programming

Leadership/mentoring

MLOps

Low-latency systems

Tools

PyTorch

TensorFlow

AWS

GCP

Azure

Kubernetes

CI/CD

Docker

Job description

Salary: £59,000 - 99,000 per year

Requirements

• Proven experience building and operating production ML systems
• Strong Python skills and experience with ML frameworks such as PyTorch or TensorFlow
• Experience with MLOps, CI/CD, and model lifecycle management
• Experience with cloud platforms such as AWS, GCP, or Azure, and with containers/Kubernetes
• Experience with low-latency or real-time systems
• Familiarity with audio or speech processing is a plus
• Mentoring or technical leadership experience is desirable

Responsibilities

• Own end-to-end ML pipelines from data through training, evaluation, and deployment
• Work closely with audio ML researchers and DSP engineers to move models into production
• Implement monitoring and CI/CD pipelines
• Ensure reproducibility across the full model lifecycle
• Help establish engineering standards across a small ML team through mentoring

Technologies

• AI
• AWS
• Azure
• CI/CD
• Cloud
• Embedded
• GCP
• Kubernetes
• Machine Learning
• MLOps
• PyTorch
• Python
• TensorFlow

More:

We are a fast-growing audio AI product company building cutting-edge machine learning technology that enhances how people experience sound across digital platforms. Our flagship products use machine learning and signal processing to deliver real-time audio quality improvements at scale, deployed across cloud, edge, and embedded environments. This is a high-impact role within a small ML team, working closely with audio ML researchers and DSP engineers.

last updated 36 week of 2026