Technical Test Lead/Machine Learning / Python
Automate your job search with Sonara.
Submit 10x as many applications with less effort than one manual application.1
Reclaim your time by letting our AI handle the grunt work of job searching.
We continuously scan millions of openings to find your top matches.
Overview
Compensation
$45-$52/hour
Job Description
We are looking for a highly skilled Technical Test Lead with strong expertise in Machine Learning systems testing and Python automation. The candidate will be responsible for designing and implementing test strategies, automation frameworks, and validation processes for ML models and data pipelines. The role requires close collaboration with data scientists, ML engineers, and development teams to ensure the quality, reliability, and performance of machine learning solutions.
Key Responsibilities
Test Strategy & Planning
- Define and implement comprehensive testing strategies for Machine Learning applications and data-driven systems.
- Lead test planning activities including test scope, effort estimation, and resource planning.
- Identify risks and ensure quality assurance across the ML lifecycle.
ML Model Testing
- Validate machine learning models, ensuring accuracy, reliability, and performance.
- Design and execute tests for model training, inference pipelines, and feature engineering workflows.
- Verify data quality, bias detection, and model drift monitoring.
Test Automation
- Develop and maintain automation frameworks using Python.
- Automate test cases for data validation, model performance, and API testing.
- Integrate automated tests into CI/CD pipelines.
Technical Leadership
- Lead and mentor QA engineers and automation testers.
- Provide technical guidance on testing frameworks, tools, and best practices.
- Ensure alignment with quality standards and engineering processes.
Collaboration
- Work closely with data scientists, ML engineers, DevOps teams, and product stakeholders.
- Participate in design discussions, code reviews, and sprint planning.
- Ensure test coverage across data pipelines, ML models, and APIs.
Required Skills
- Strong Python programming for automation and data validation.
- Experience testing Machine Learning and AI-based applications.
- Knowledge of ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Experience with test automation frameworks (PyTest, Robot Framework, or similar).
- Understanding of data pipelines, ETL processes, and large datasets.
- Experience with CI/CD tools (Jenkins, GitHub Actions, etc.).
- Strong analytical and problem-solving skills.
Preferred Skills
- Experience with MLOps practices and model lifecycle management.
- Knowledge of cloud platforms (AWS, Azure, or GCP).
- Familiarity with data validation tools such as Great Expectations.
- Experience with performance testing and API testing tools.
Top Responsibilities
- Lead the testing strategy for ML-based applications.
- Develop Python-based automation frameworks for ML validation.
- Ensure quality, reliability, and performance of machine learning models and data pipelines.
Automate your job search with Sonara.
Submit 10x as many applications with less effort than one manual application.
FAQs About Technical Test Lead/Machine Learning / Python Jobs at Argyllinfotech
What is the work location for this position at Argyllinfotech?
This job at Argyllinfotech is located in south kent, CT, according to the details provided by the employer. Some roles may also include multiple work locations depending on the requirement.
What pay range can candidates expect for this role at Argyllinfotech?
Candidates can expect a pay range of $45–$52 per hour for this role.
What employment applies to this position at Argyllinfotech?
The employer has not provided this information. This may be discussed during the hiring process.
What is the process to apply for this position at Argyllinfotech?
You can apply for this role at Argyllinfotech either through Sonara's automated application system, which helps you submit applications 10X faster with minimal effort, or by applying manually using the direct link on the job page.