Company Description Recruitment Company is a talent-focused organization dedicated to connecting skilled professionals with impactful roles across diverse industries. The company emphasizes data-driven hiring practices and modern technology to improve the recruitment experience for clients and candidates. Team members collaborate with a range of organizations, gaining exposure to different business domains and problem spaces. Recruitment Company values continuous learning, ethical practices, and inclusive workplaces, creating an environment where people can grow and contribute meaningfully.
Role Description This on-site Machine Learning Engineer role is based in India and involves designing, developing, and deploying machine learning models to support recruitment and business operations. Day-to-day responsibilities include collecting and preprocessing data, building and optimizing algorithms, implementing neural network architectures, and performing pattern recognition on large datasets. The role also includes conducting statistical analysis, evaluating model performance, and collaborating with cross-functional teams to translate business requirements into technical solutions. The Machine Learning Engineer will maintain production ML pipelines, document solutions clearly, and contribute to continuous improvement of systems and processes.
Qualifications
- Candidates should possess strong foundations in Computer Science and Algorithms.
- Candidates should possess skills in Pattern Recognition and Neural Networks.
- Candidates should possess solid knowledge of Statistics for data analysis and model evaluation.
- Proficiency in programming languages such as Python or Java and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) is beneficial.
- Experience with data preprocessing, model deployment, and performance tuning in production environments is preferred.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field is advantageous.
- Strong problem-solving abilities, attention to detail, and capacity to work collaboratively with technical and non-technical stakeholders are important.