Hajoras Ltd
Website:
hajoras.com
Job details:
Note: Immediate Hiring Opportunity
Company Description
Hajoras Ltd is a premier IT services partner with operations in the UK and India, supporting clients across multiple industries. The company delivers end-to-end project solutions in areas such as AI, PEGA, Pega CDH, QA automation, e-commerce and travel software development, application support and maintenance, and business transformation. Hajoras Ltd also provides business process consulting, IT consulting, and operational excellence services tailored to each client’s needs. By offering customized strategies and technology solutions, the company helps organizations achieve their business objectives and stay competitive in dynamic markets.
Role Description
This is a full-time remote role for an ML Ops Engineer at Hajoras Ltd. We are seeking a skilled MLOps Engineer with proven experience in deploying, managing, and monitoring machine learning models in production environments. The ideal candidate will have hands-on expertise in MLOps practices, strong experience with Databricks, and advanced SQL skills (mandatory).
Excellent communication and collaboration skills are essential to work effectively with cross-functional teams and drive successful ML deployments.
Responsibilities:
- Design, implement, and manage end-to-end MLOps pipelines for model training, validation, deployment, and monitoring.
- Deploy, maintain, and optimize machine learning models in production environments to ensure high availability and performance.
- Develop, optimize, and maintain scalable data pipelines using SQL (mandatory) and other relevant technologies.
- Collaborate closely with Data Scientists, Data Engineers, and software development teams to operationalize and productionize machine learning solutions.
- Build, automate, and maintain CI/CD pipelines to streamline ML model development, testing, deployment, and release processes.
- Monitor model performance, data quality, and infrastructure health, implementing proactive measures to ensure reliability, scalability, and operational excellence.
- Leverage Databricks for data engineering, feature engineering, model training, deployment, and workflow orchestration.
- Implement MLOps best practices, including model versioning, experiment tracking, data governance, reproducibility, and security compliance.
- Troubleshoot, investigate, and resolve production issues efficiently while driving continuous improvements to ML platforms and deployment processes.
Qualifications:
- Strong experience with MLOps practices, including model deployment, monitoring, automation, CI/CD pipelines, and lifecycle management.
- Hands-on experience with Databricks for data engineering, machine learning workflows, and model deployment.
- Advanced SQL skills (mandatory) with proven experience in data manipulation, query optimization, and scalable pipeline development.
- Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related discipline.
- 4+ years of hands-on experience in MLOps, Machine Learning Engineering, or Data Engineering.
- Familiarity with containerization and orchestration technologies such as Docker and Kubernetes is highly desirable.
- Strong analytical, problem-solving, and troubleshooting skills with the ability to resolve complex production issues.
- Excellent communication, collaboration, and stakeholder management skills, with the ability to work effectively in cross-functional teams.
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