Data Engineer job opportunity at Weekday AI.

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Date2026-02-07T07:53:52.984Z bot
Weekday AI Data Engineer
Experience: 2-years
Pattern: Full-time
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India

This role is for one of the Weekday's clients Salary range: Rs 500000 - Rs 1500000 (ie INR 4-5 LPA) We are seeking a Machine Learning–focused professional who is passionate about building intelligent, data-driven solutions that solve real-world problems. In this role, you will work closely with engineering, product, and data teams to design, develop, and deploy machine learning models that drive business impact. You’ll have the opportunity to work across the full ML lifecycle—from data exploration and model development to deployment and continuous improvement—in a fast-paced, growth-oriented environment. Key Responsibilities Design, develop, train, and deploy machine learning models for prediction, classification, recommendation, or optimization use cases. Work with structured and unstructured datasets to perform data preprocessing, feature engineering, and exploratory data analysis. Implement and evaluate ML algorithms using appropriate metrics to ensure model accuracy, robustness, and scalability. Collaborate with software engineers to integrate ML models into production systems and applications. Optimize model performance through tuning, experimentation, and continuous monitoring. Build reusable ML pipelines and workflows to support experimentation and deployment. Document models, assumptions, and results clearly for technical and non-technical stakeholders. Stay current with emerging trends, tools, and best practices in machine learning and applied AI. What Makes You a Great Fit Minimum 2 years of hands-on experience working on machine learning or applied data science projects. Strong foundation in machine learning concepts, algorithms, and statistical reasoning. Experience working with popular ML libraries and frameworks (such as scikit-learn, TensorFlow, PyTorch, or similar). Comfortable working with data, including cleaning, transforming, and analyzing large datasets. Programming proficiency (Python preferred) with the ability to write clean, efficient, and maintainable code. Problem-solving mindset with the ability to translate business problems into ML-driven solutions. Strong communication skills to explain model behavior, insights, and trade-offs clearly. A proactive learner who thrives in collaborative, fast-evolving environments.

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