AI/ML ENGINEER

Company Description Art Acquirer connects talent with a wide range of career opportunities across global enterprises and innovative startups. The organization focuses on providing comprehensive, current job listings that align with diverse skills, interests, and long-term growth aspirations. By curating roles across multiple domains, Art Acquirer helps professionals stay ahead of market trends and discover meaningful career paths. Candidates can stay informed about new openings and industry movements through regular job updates designed to support ongoing career development.
Role Description As an AI/ML Engineer at Art Acquirer, you will design, develop, and deploy machine learning models and algorithms to solve complex, real-world problems. You will work on data preparation and feature engineering, train and evaluate models, and optimize performance for production environments. Day-to-day responsibilities include collaborating with cross-functional teams to define requirements, implementing scalable ML pipelines, conducting experiments, and documenting methodologies and results. You will also maintain and improve existing AI systems, monitor model behavior, and ensure reliability and fairness of ML solutions. This is a full-time, on-site role based in the Mohali district.
Qualifications
Strong foundation in Computer Science and Algorithms, with experience designing efficient, scalable solutions.
Proficiency in Pattern Recognition and Statistics to analyze data, identify trends, and build robust predictive models.
Hands-on experience with Neural Networks and modern machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Solid programming skills in languages commonly used in AI/ML (such as Python, R, or Java) and familiarity with data processing tools.
Experience building and deploying ML models in production, including use of version control, testing, and monitoring tools.
Ability to interpret business needs, communicate technical concepts clearly, and collaborate effectively with diverse teams.
Bachelor’s or master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field (or equivalent practical experience).
Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and MLOps practices is an advantage.

Work arrangement
No