Machine Learning Engineer

Company Description Autom8AI is an AI-powered automation company focused on helping businesses reduce repetitive work and dedicate more time to strategic initiatives. The platform transforms everyday business processes into intelligent, automated workflows across marketing, customer communication, operations, and productivity. By integrating advanced automation and machine learning, Autom8AI enables teams to save time, reduce operational costs, and scale efficiently. Joining Autom8AI means contributing to technology that streamlines business performance and delivers tangible impact for organizations of all sizes.
Role Description This is a full-time, on-site Machine Learning Engineer role based in Aligarh. The Machine Learning Engineer will design, develop, and deploy machine learning models that power Autom8AI’s automation platform, focusing on pattern recognition, predictive analytics, and intelligent decision-making. Daily responsibilities include researching and implementing algorithms, building and training neural network architectures, evaluating model performance using statistical methods, and optimizing models for scalability and efficiency in production. The role involves collaborating with product and engineering teams to translate business requirements into technical solutions, integrating models into production pipelines, monitoring their performance, and continuously improving them based on data-driven insights. The engineer will also contribute to code reviews, documentation, and best practices for machine learning and data engineering within the team.
Qualifications
Strong foundation in Computer Science, including data structures, Algorithms, and software engineering principles.
Proficiency in Pattern Recognition and Neural Networks, with experience designing and training machine learning models.
Solid understanding of Statistics and probability, including model evaluation, hypothesis testing, and performance metrics.
Experience implementing machine learning solutions end-to-end, from data preprocessing to deployment in production environments.
Hands-on experience with common ML tools and languages (e.g., Python, TensorFlow/PyTorch, scikit-learn, SQL or similar).
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field, or equivalent practical experience.
Ability to work collaboratively in cross-functional teams and communicate complex technical concepts clearly to non-technical stakeholders.
Experience with cloud platforms, MLOps practices, or real-time data processing is a plus.

Work arrangement
No