- Translate business problems into machine learning problems.
- Understand and apply machine learning techniques (e.g., classification, regression) to analyze largescale, multistructured datasets.
- Stay uptodate on the latest research papers, tools, and techniques in the field of machine learning and explore their potential applications within our business processes.
- Identify opportunities to leverage machine learning for automated test case generation and data validation.
- Software Development Lifecycle (SDLC) Integration:
- Collaborate effectively with cross-functional teams (Business Analysts, Data Scientists, Software Developers) throughout the SDLC to ensure quality throughout the machine learning model development process.
- Develop and maintain automated test scripts using frameworks like Selenium and Java.
- Take endtoend responsibility for model development, including data exploration, training data preparation, feature engineering, model development, validation, scoring, and deployment.
- Identify and address data quality issues that could impact model performance.
- Develop and implement unit tests for machine learning code.
- Communicate effectively with both technical (IT, Data Engineering) and nontechnical stakeholders (Business Analysts, Product Managers).
- Clearly document test plans, findings, and recommendations in a concise and easytounderstand manner.
- Experience with software development methodologies (e.g., Agile)
- Experience with SQL for data retrieval and manipulation
- Experience with testing frameworks like BDD (Behavior-Driven Development) and Page Object Model (POM)
- Experience with Rest API testing
- Programming experience in Java or Python (a plus)
- Familiarity with Machine Learning concepts (classification, regression, etc.)
- Experience with data exploration and manipulation tools
- Excellent analytical and problemsolving skills
- Strong communication and collaboration skills
- Experience with cloud platforms (AWS, Azure, GCP)
- Experience with machine learning libraries (Scikitlearn, TensorFlow, PyTorch)
- Experience with model deployment tools (MLflow, Kubeflow)
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Quality Assurance Engineer - Bangalore, India - Indium Software
Description
Job Description :
You will combine your software testing expertise with your understanding of machine learning to design and execute comprehensive test plans that identify and mitigate issues before models are deployed to production.
Responsibilities :
Machine Learning Expertise :
Full Model Lifecycle Ownership :
Communication and Collaboration :
Technical Skills & Requirements :
Bonus Points :