MLOps Engineer (Databricks Specialist) - £438 Inside IR35 - Hybrid
Stealth IT Consulting
- Industry Type
- IT
- Functional Area
- IT Information Technology Industry IT Information Technology
- Nationality
- Any
- Keywords
- Machine Learning ML Implementation Model Deployment Monitoring and Governance Capabilities MLOps Capabilities
Job Description
Stealth IT Consulting is looking for an MLOps Engineer (Databricks Specialist) to implement model training, deployment, monitoring, and governance capabilities. The role involves working hybrid with three days on-site in London each week. Candidates should be skilled in implementing Machine Learning workloads and MLOps on the Global AI Platform.
- Position
- MLOps Engineer (Databricks Specialist)
- Company
- Stealth IT Consulting
- Location
- London, United Kingdom
- Industry
- IT
- Experience
- 1 to 20 years
Responsibilities
- Implement model training, deployment, monitoring, and governance capabilities.
Requirements
- Proficiency in implementing Machine Learning workloads and MLOps capabilities on the Global AI Platform.
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About the role: MLOps Engineer (Databricks Specialist) - £438 Inside IR35 - Hybrid
General information about this type of role, not from the employer. The employer's actual requirements may differ, so always check the job details above.
MLOps Engineers specializing in Databricks focus on developing and maintaining machine learning operations pipelines using the Databricks platform. They typically work in IT companies, technology departments, or data-driven organizations to support the deployment and management of machine learning models in production environments.
What this role usually involves
- Design and implement machine learning pipelines using Databricks.
- Collaborate with data scientists and engineers to deploy models efficiently.
- Monitor and maintain machine learning models and infrastructure.
- Automate workflows and ensure scalability of ML operations.
- Troubleshoot issues related to data processing and model deployment.
Skills employers usually look for
- Proficiency with Databricks and Apache Spark.
- Strong understanding of machine learning lifecycle and MLOps practices.
- Experience with cloud platforms and containerization tools.
- Programming skills in languages like Python or Scala.
- Knowledge of CI/CD pipelines and automation tools.
Usual qualifications
- A degree or diploma in computer science, data science, or related field.
- Experience or certification in Databricks or big data technologies.
- Familiarity with machine learning concepts and tools.
- Training in cloud computing and DevOps methodologies.
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