Senior Machine Learning Engineer

Company Description Esse India is a Canada-focused immigration and visa consulting firm based in Delhi, offering services at a competitive and transparent price range. The organization specializes in guiding clients through complex immigration rules and regulations with an experienced team of consultants. Esse India is committed to delivering trustworthy, value-driven visa services tailored to individual needs and expectations. Since its establishment, the firm has built a strong reputation for client satisfaction by providing reliable support throughout the immigration process. The company emphasizes professionalism, integrity, and personalized service to help clients achieve their immigration goals.

Role Description The Senior Machine Learning Engineer will be responsible for designing, developing, and deploying machine learning models to support data-driven decision-making and process optimization within Esse India. This full-time, on-site role based in Abroad involves collaborating with cross-functional teams to identify business problems, define technical requirements, and build scalable ML solutions for applications such as pattern recognition in client data, risk assessment, and process automation. Day-to-day tasks include data preprocessing, feature engineering, model training and evaluation, algorithm optimization, and performance monitoring in production environments. The role also requires maintaining high-quality documentation, mentoring junior engineers, and staying current with advancements in machine learning, neural networks, and related technologies.

Qualifications

• Strong foundation in Computer Science and Algorithms, with the ability to design efficient, scalable solutions.
• Expertise in Machine Learning, including Pattern Recognition and Neural Networks for real-world applications.
• Solid understanding of Statistics and probabilistic methods for data analysis and model evaluation.
• Proficiency in programming languages commonly used in ML (such as Python), and experience with ML frameworks (such as TensorFlow, PyTorch, or scikit-learn).
• Experience in end-to-end ML lifecycle: data collection, preprocessing, model development, deployment, and monitoring.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• Ability to work collaboratively with stakeholders, communicate technical concepts clearly, and document solutions thoroughly.
• Experience with cloud platforms, data pipelines, and version control tools is an advantage.