Senior Machine Learning Deployment Specialist
5 days ago
About NearTech Search
We are a cutting-edge AI/ML consultancy, seeking an experienced Lead MLOps Engineer to join our team.
The role requires leading the deployment, testing, and optimization of machine learning systems, managing a team of engineers, and setting up scalable infrastructure to support client needs.
Job SummaryThis is an exciting opportunity to shape the future of MLOps in a fast-paced, innovative environment. The Lead MLOps Engineer will be responsible for:
- Developing, deploying, and monitoring MLOps pipelines for machine learning models.
- Managing and mentoring a team of 5+ engineers, providing technical guidance and fostering collaboration.
- Designing and implementing robust testing frameworks for ML models to ensure high performance and reliability.
- Setting up and maintaining MLOps infrastructure, including cloud environments, CI/CD pipelines, and version control for ML models.
- Working closely with data scientists and engineers to integrate machine learning models into production environments.
- Optimizing deployment processes, scaling models, and ensuring efficient performance across environments.
- Staying ahead of industry trends, evaluating, and implementing new tools and technologies to improve infrastructure and workflows.
To succeed in this role, you should have at least 5 years of hands-on experience in MLOps/DevOps/DevSecOps/MLFlow, with a focus on deployment and scaling of machine learning models in production environments.
- Strong expertise in MLFlow, DevOps, or MLOps tools, and a deep understanding of model deployment pipelines.
- Experience with infrastructure automation, including tools like Kubernetes, Terraform, and Docker.
- Strong background in model versioning, model testing, and ensuring compliance with data privacy and security standards.
- Hands-on experience with cloud platforms (AWS, Azure, or GCP) and the tools required for managing machine learning workloads.
- A proven track record of managing and scaling teams of engineers (5+), with excellent leadership and communication skills.
- Familiarity with CI/CD pipelines, monitoring tools, and data engineering workflows.
£80,000 - £110,000 per annum, depending on experience.
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