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Mid LevelFull-timePythonRustMachine LearningData ScienceTensorFlowPyTorchGitAIML
Salary Range
$20,400 - $27,600 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for an experienced AI Engineer to design, build, and operationalize AI-driven solutions for our global Analytics organization. The ideal candidate will have strong hands-on expertise in Python, PySpark, agentic workflow development, and modern GenAI frameworks, with experience building scalable applications using LLMs, retrieval systems, and automation pipelines.
Key Responsibilities
- →Design, develop, and execute test plans and test cases to validate the functionality, performance, and reliability of AI/ML systems
- →Collaborate with the development team to understand model requirements and identify potential areas of weakness
- →Perform data validation to ensure the quality, integrity, and representativeness of the datasets used for training and testing
- →Test for and identify potential biases in AI models to ensure fairness and ethical compliance
- →Analyze and report on model performance using key metrics (e.g., accuracy, precision, recall, F1-score)
- →Ensure accuracy, consistency, tool-call reliability, trace quality, and guardrail adherence
- →Assess regression, functionality, performance, safety, and hallucination risks
- →Document and track defects and work with developers to facilitate their resolution
- →Assist in the development and maintenance of automated testing frameworks for AI applications
- →Conduct exploratory testing to discover edge cases and unexpected behaviors in our AI systems
- →Stay current with the latest advancements in AI testing methodologies and tools
- →Produce test plans, scenario libraries, coverage reports, and defect logs
- →Deliver insights to Data Science & Engineering teams to improve reliability
Requirements
- ✓Bachelor's degree in computer science, Engineering, Statistics, or a related technical field
- ✓Solid understanding of software testing principles and the software development lifecycle (SDLC)
- ✓Basic programming proficiency, preferably in Python, for writing test scripts and analyzing data
- ✓A foundational understanding of machine learning concepts (e.g., supervised/unsupervised learning, classification, regression)
- ✓Strong analytical and problem-solving skills with an exceptional eye for detail
- ✓Excellent communication and collaboration skills, with the ability to articulate technical issues clearly
- ✓Prior internship or project experience in software testing or a data-related field
- ✓Familiarity with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Scikit-learn
- ✓Experience with testing tools and frameworks like PyTest, Selenium, or Postman
- ✓Knowledge of SQL for querying and validating data
- ✓Familiarity with version control systems like Git
- ✓A genuine passion for artificial intelligence and a desire to learn and grow in the field
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