Ml Engineer

About the Role

We are looking for a Machine Learning Engineer to design, develop, and deploy intelligent machine learning solutions that solve real-world business problems. The ideal candidate should have strong programming skills, hands-on ML experience, and the ability to work with large datasets and production systems.

Key Responsibilities

• Develop, train, and deploy machine learning models for business applications.
• Perform data preprocessing, feature engineering, model training, and evaluation.
• Work with supervised and unsupervised learning techniques.
• Build and optimize ML pipelines for production environments.
• Analyze large datasets to identify patterns, trends, and actionable insights.
• Implement model monitoring, performance evaluation, and continuous improvement.
• Collaborate with Data Scientists, Software Engineers, Product, and Business teams.
• Integrate ML models with existing applications and APIs.
• Research and implement relevant ML/AI techniques and industry best practices.
• Maintain technical documentation and ensure code quality and scalability.

Required Skills

• Strong proficiency in Python.
• Good knowledge of Machine Learning algorithms and statistics.
• Hands-on experience with Scikit-learn, Pandas, NumPy and similar libraries.
• Experience with TensorFlow or PyTorch is preferred.
• Knowledge of SQL and databases.
• Understanding of model deployment, APIs, and ML pipelines.
• Familiarity with Git and cloud platforms such as AWS, Azure, or GCP is an advantage.
• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

• Bachelor's/Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field.
• Experience working on real-world ML/AI projects.
• Knowledge of Deep Learning, NLP, Generative AI, or LLMs will be an added advantage.