Senior MLOps Engineer
Posted 1 day ago by Experis
Negotiable
Undetermined
Undetermined
London Area, United Kingdom
Summary: The Senior MLOps Engineer will be responsible for designing, developing, and implementing scalable systems for deploying machine learning models in production environments. This role requires a blend of software engineering, machine learning expertise, and operational knowledge, working closely with cross-functional teams to automate processes and ensure optimal model performance. The ideal candidate will have extensive experience in MLOps and a strong technical background in cloud platforms and programming. This position is suited for a collaborative individual passionate about impactful machine learning solutions.
Key Responsibilities:
- Build and deploy ML models into production, ensuring scalability and reliability.
- Architect and maintain tools and pipelines to enhance the Model Development Life Cycle (MDLC).
- Implement CI/CD pipelines for seamless updates and releases of ML models.
- Monitor system health, model performance, and data drift, with robust alerting systems.
- Collaborate with stakeholders to understand requirements and provide clear technical guidance.
Key Skills:
- 5+ years of experience in MLOps or similar roles.
- Hands-on experience delivering and leading data science and ML projects.
- Experience with Databricks or similar platforms.
- Cloud expertise in AWS, Azure, or GCP, including cloud architecting for ML.
- Strong programming skills: Python, Java, or Scala.
- Containerization and orchestration experience: Docker, Kubernetes.
- DevOps and monitoring tools: Jenkins, Ansible, Grafana, Prometheus, Elastic.
- Familiarity with CI/CD deployment practices and automated testing.
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or similar.
- Excellent ability to communicate complex technical concepts to non-technical audiences.
Salary (Rate): undetermined
City: London Area
Country: United Kingdom
Working Arrangements: undetermined
IR35 Status: undetermined
Seniority Level: Senior
Industry: IT
Senior MLOps Engineer – Machine Learning in Production
We are looking for a talented Senior MLOps Engineer to join a forward-thinking technology consultancy. This is an exciting opportunity for someone passionate about building and maintaining machine learning systems in production environments , with a blend of software engineering, ML expertise, and operational know-how.
About the Role:
You will design, develop, and implement scalable and reliable systems for deploying machine learning models into production. You’ll work closely with cross-functional teams, translating complex ML concepts into actionable solutions, automating processes, and ensuring models perform at their best throughout the ML lifecycle.
Key Responsibilities:
- Build and deploy ML models into production, ensuring scalability and reliability.
- Architect and maintain tools and pipelines to enhance the Model Development Life Cycle (MDLC).
- Implement CI/CD pipelines for seamless updates and releases of ML models.
- Monitor system health, model performance, and data drift, with robust alerting systems.
- Collaborate with stakeholders to understand requirements and provide clear technical guidance.
Requirements:
- 5+ years of experience in MLOps or similar roles.
- Hands-on experience delivering and leading data science and ML projects.
- Experience with Databricks or similar platforms.
- Cloud expertise in AWS, Azure, or GCP , including cloud architecting for ML.
- Strong programming skills: Python, Java, or Scala.
- Containerization and orchestration experience: Docker, Kubernetes .
- DevOps and monitoring tools: Jenkins, Ansible, Grafana, Prometheus, Elastic.
- Familiarity with CI/CD deployment practices and automated testing.
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or similar.
- Excellent ability to communicate complex technical concepts to non-technical audiences.
This role is ideal for someone who is curious, collaborative, and driven to implement ML solutions that make an impact .