Junior Machine Learning Engineer

What role will you play in the team

As a Junior Machine Learning Engineer within our advanced artificial intelligence division, you will actively contribute to the design, training, and deployment of predictive models. You will work alongside senior data scientists and machine learning architects to translate complex business requirements into robust, scalable algorithmic solutions that directly impact our core data products.

What you will do

You will be responsible for writing clean, efficient code in Python to preprocess large datasets, extract meaningful features, and build machine learning pipelines. Furthermore, you will monitor model performance in production environments, perform hyperparameter tuning, and collaborate with software engineering teams to integrate these predictive models seamlessly into our enterprise software applications.

Key responsibility

• Design, build, and deploy scalable machine learning models using Python, TensorFlow, and scikit-learn for various enterprise applications.
• Preprocess, clean, and transform large-scale structured and unstructured datasets to ensure high data quality for model training.
• Collaborate with data engineering teams to optimize data pipelines using SQL, PostgreSQL, and Apache Spark.
• Perform rigorous statistical analysis, feature engineering, and hyperparameter tuning to enhance model accuracy and predictive performance.

• Monitor and maintain machine learning models in production, troubleshooting latency and drift issues proactively.
• Document model architectures, training procedures, and deployment steps thoroughly for cross-functional team alignment.
• Participate in code reviews, architectural discussions, and agile sprint planning sessions to drive continuous improvement.

Required Qualification and Skills

• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related quantitative discipline with a strong academic background.
• Demonstrated hands-on experience with core programming languages including Python and R for data manipulation.
• Proficiency in machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, and Keras for building predictive algorithms.
• Strong foundational knowledge of database management systems including SQL, MySQL, PostgreSQL, and MongoDB.
• Familiarity with big data technologies and ETL tools like Apache Spark, Hadoop, and Talend.
• Solid understanding of statistical analysis, linear algebra, probability, and algorithmic complexity.

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• Excellent problem-solving skills, strong verbal and written communication abilities, and a collaborative team-player mindset.

Benefits Included

• Competitive starting salary package benchmarked against top-tier technology and data science industry standards in India.
• Comprehensive health, medical, and life insurance coverage extending to immediate family members.
• Annual performance-based bonuses, stock options, and periodic salary increments based on objective evaluations.
• Robust professional development budget allocated for certifications, advanced online courses, and technical conferences.
• Flexible working hours, paid time off, mental health support programs, and well-equipped ergonomic workspaces.

A Day in the Life

Your typical workday begins with a quick agile stand-up with your engineering squad to discuss yesterday's model evaluation metrics. You will spend the morning writing Python scripts to clean a new batch of training data and running hyperparameter tuning experiments using scikit-learn. After lunch, you will collaborate with the data engineering team to optimize SQL queries for faster feature extraction, followed by a code review session with the senior machine learning architect.