Software Engineer - ML Ops
Posted Today by Haystack
£600 Per day
Undetermined
Remote
London Area, United Kingdom
Summary: The MLOps Engineer role involves taking full ownership of deploying, monitoring, and scaling machine learning models in a remote capacity. The position requires expertise in Python, AWS, and Kubernetes to ensure reliability for production-ready AI. The engineer will collaborate with Data Science teams and enhance automation tooling for model evaluation metrics. This role offers a competitive daily rate and the opportunity to work on enterprise-level ML infrastructure.
Key Responsibilities:
- Lead the deployment and maintenance of production ML models, ensuring seamless integration into automated CI/CD pipelines and high-performance environments.
- Radical platform monitoring using Grafana and Domino Data Lab to track model health, endpoint performance, and reliability.
- Drive operational excellence by managing incident response via ServiceNow, performing critical code fixes, and optimizing resource usage.
- Collaborate closely with Data Science teams to streamline the handoff from experimentation to production, ensuring strict version control and governance.
- Build and enhance automation tooling for model evaluation metrics, identifying data drift, overfitting, and feature importance in real-time.
Key Skills:
- Deep expertise in Python programming and a proven track record of deploying ML models in complex, scalable production environments.
- Strong hands-on experience with AWS cloud infrastructure, specifically managing S3, Redshift, and associated data services.
- Advanced proficiency with monitoring and orchestration tools, including Grafana, Docker, and Kubernetes.
- A solid grasp of ML lifecycle concepts such as data drift, feature importance, and model validation metrics.
- Experience with Domino Data Lab is highly desirable; background in troubleshooting and incident management within a fast-paced environment is essential.
Salary (Rate): £600 daily
City: London
Country: United Kingdom
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
MLOps Engineer | London | Remote | £500 - £600 day rate
We're working with a leading global talent solutions and workforce technology specialist on this exciting opportunity. We are looking for a heavyweight MLOps Engineer to take full ownership of the deployment, monitoring, and scaling of high-impact machine learning models. This is a platform-first role where you will leverage a sophisticated tech stack including Python, AWS, and Kubernetes to ensure industrial-grade reliability for production-ready AI.
The Role
- Lead the deployment and maintenance of production ML models, ensuring seamless integration into automated CI/CD pipelines and high-performance environments.
- Radical platform monitoring using Grafana and Domino Data Lab to track model health, endpoint performance, and reliability.
- Drive operational excellence by managing incident response via ServiceNow, performing critical code fixes, and optimizing resource usage.
- Collaborate closely with Data Science teams to streamline the handoff from experimentation to production, ensuring strict version control and governance.
- Build and enhance automation tooling for model evaluation metrics, identifying data drift, overfitting, and feature importance in real-time.
What You'll Need
- Deep expertise in Python programming and a proven track record of deploying ML models in complex, scalable production environments.
- Strong hands-on experience with AWS cloud infrastructure, specifically managing S3, Redshift, and associated data services.
- Advanced proficiency with monitoring and orchestration tools, including Grafana, Docker, and Kubernetes.
- A solid grasp of ML lifecycle concepts such as data drift, feature importance, and model validation metrics.
- Experience with Domino Data Lab is highly desirable; background in troubleshooting and incident management within a fast-paced environment is essential.
What's On Offer
- Competitive daily rate of £500 - £600 in a high-impact, platform-centric role.
- Flexible, remote-friendly working environment based out of a central London hub.
- Opportunity to work on enterprise-level ML infrastructure and cutting-edge MLOps tooling.
Apply via Haystack today!