Quality Assurance Analyst

Job Description

We’re looking for a passionate Machine Learning Engineer to join our AI team and help design, build, and scale cutting-edge machine learning models. You’ll work closely with data scientists, product managers, and engineers to bring intelligent features to life and solve real-world problems through automation and predictive analytics.
You should have a strong background in algorithms, data structures, and statistical modeling, with experience deploying models into production environments.

Key Responsibilities

Design, develop, and deploy machine learning models for real-time and batch inference.
Collaborate with cross-functional teams to understand business problems and translate them into data-driven solutions.
Perform data preprocessing, feature engineering, and model selection/tuning.
Optimize and monitor model performance over time.
Implement and maintain scalable ML pipelines using tools like Airflow, MLflow, or similar.
Stay up to date with the latest developments in AI/ML and evaluate new tools, frameworks, and techniques.
Work with data engineers to ensure high-quality and reliable data infrastructure.
Document model design, assumptions, and performance metrics for reproducibility.

Responsibilities

Design, develop, and deploy machine learning models for real-time and batch inference.
Collaborate with cross-functional teams to understand business problems and translate them into data-driven solutions.
Perform data preprocessing, feature engineering, and model selection/tuning.
Optimize and monitor model performance over time.
Implement and maintain scalable ML pipelines using tools like Airflow, MLflow, or similar.
Stay up to date with the latest developments in AI/ML and evaluate new tools, frameworks, and techniques.
Work with data engineers to ensure high-quality and reliable data infrastructure.
Document model design, assumptions, and performance metrics for reproducibility.

Perks and Benefits

Design, develop, and deploy machine learning models for real-time and batch inference.
Collaborate with cross-functional teams to understand business problems and translate them into data-driven solutions.
Perform data preprocessing, feature engineering, and model selection/tuning.
Optimize and monitor model performance over time.
Implement and maintain scalable ML pipelines using tools like Airflow, MLflow, or similar.
Stay up to date with the latest developments in AI/ML and evaluate new tools, frameworks, and techniques.
Work with data engineers to ensure high-quality and reliable data infrastructure.
Document model design, assumptions, and performance metrics for reproducibility.

How to Apply

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