Qureos Mentor

Zinnov Management Consulting

Key Responsibilities<ul><li>Develop and maintain automated test suites for ML pipelines and data workflows using Python and Pytest</li><li>Validate data integrity and model performance using SQL and statistical metrics</li><li>Design QA strategies for scalable ML model deployment (batch, real-time, and streaming)</li><li>Ensure reproducibility, traceability, and auditability of ML experiments using MLflow</li><li>Collaborate with data scientists and ML engineers to identify testing bottlenecks early in the development cycle</li><li>Build and maintain continuous testing pipelines within AWS (especially with SageMaker, Lambda, S3, etc.)</li><li>Conduct performance testing of APIs and model endpoints in production</li><li>Help enforce best practices for version control, test coverage, and CI/CD integration</li></ul>Required Qualifications<ul><li>3&ndash;6 years of QA or SDET experience in software or ML environments</li><li>Strong programming skills in Python (unit testing, scripting, API testing)</li><li>Proficiency in SQL for data validation, transformations, and test scenario building</li><li>Experience with Pytest or other test frameworks</li><li>Solid understanding of machine learning lifecycle, model validation, and data pipelines</li><li>Experience with MLflow for experiment tracking and model management</li><li>Hands-on experience with AWS services, especially SageMaker, S3, Lambda, EC2</li><li>Familiar with CI/CD pipelines and DevOps tools (e.g., GitHub Actions, Jenkins)</li></ul>Job Types: Full-time, PermanentPay: Up to &#8377;2,000,000.00 per yearBenefits:<ul><li>Health insurance</li><li>Provident Fund</li></ul>Application Question(s):<ul><li>Where do you stay in Bangalore?</li><li>What is your current Notice Period?</li></ul>Work Location: In person

QA Engineer – AI/ML

Key Responsibilities:<ul><li>Design, implement and maintain ML pipelines for model training, validation, and deployment</li><li>Automate model deployment processes using CI/CD pipelines and containerization technologies</li><li>Monitor model performance, data drift, and system health in production environments</li><li>Collaborate with data scientists to operationalize machine learning models and algorithms</li><li>Implement version control for models, datasets, and ML experiments using MLOps tools</li><li>Optimize ML infrastructure for scalability, reliability, and cost-effectiveness</li><li>Troubleshoot and resolve issues related to model deployment and production systems</li><li>Maintain documentation for ML workflows, deployment processes, and system architecture</li><li>This position may require availability outside of standard business hours as part of a rotational on-call schedule.</li></ul>What You&rsquo;ll Need to Be Successful (Required Skills):<ul><li>2-4 years of experience in software development, DevOps, or data engineering</li><li>Proficiency in Python, SQL, and at least one ML framework such as TensorFlow, PyTorch, Scikit-learn</li><li>Experience with containerization (Docker) and orchestration tools (Kubernetes)</li><li>Knowledge of cloud platforms such as AWS, Azure, GCP and their ML services</li><li>Understanding of CI/CD pipelines, version control (Git), and infrastructure as code</li><li>Familiarity with monitoring tools and logging frameworks for production systems</li><li>Experience with data pipeline tools such as Apache Airflow, Kubeflow, or similar</li><li>Strong problem-solving skills and ability to work in fast-paced, collaborative environments.</li></ul>Preferred Skills:<ul><li>Experience with MLOps platforms such as MLflow, Weights &amp; Biases, Neptune</li><li>Knowledge of streaming data processing such as Kafka, Kinesis</li><li>Familiarity with infrastructure monitoring tools such as Prometheus, Grafana</li><li>Understanding of model interpretability and explainability techniques</li><li>Experience with feature stores and data versioning tools</li><li>Certification in cloud platforms such as AWS ML, Azure AI, GCP ML.</li></ul>Job Types: Full-time, PermanentPay: &#8377;3,000,000.00 - &#8377;4,000,000.00 per yearBenefits:<ul><li>Food provided</li><li>Health insurance</li><li>Provident Fund</li></ul>Application Question(s):<ul><li>Are you ok with 5 days' work from office?</li><li>What is your current notice period?</li><li>Where do you stay in Bangalore?</li></ul>Work Location: In person

Machine Learning Ops Engineer

Join Zinnov Management Consulting and explore 2   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Zinnov Management Consulting

ABOUT_COMPANY

QA Engineer – AI/ML

Machine Learning Ops Engineer