Role Overview :

As a Machine Learning Engineer, you will be at the forefront of transforming complex data into scalable, high-impact AI solutions that drive business intelligence and operational efficiency. Your day-to-day involves architecting robust ML pipelines, refining deep learning models, and bridging the gap between raw data and production-ready applications.

You will collaborate closely with cross-functional teams, including data scientists, product managers, and engineering stakeholders, to translate ambiguous business challenges into technical roadmaps. By deploying cutting-edge models, you will directly influence product performance and customer experience, ensuring our technological infrastructure remains competitive in a rapidly evolving market.

Key Responsibilities :

- Design and deploy end-to-end machine learning systems that automate decision-making processes, directly enhancing the scalability of our core product offerings.

- Optimize deep learning architectures using PyTorch to improve model accuracy and inference speed for large-scale production environments.

- Collaborate with data engineering teams to build and maintain robust big data pipelines, ensuring high-quality data availability for model training and real-time analytics.

- Conduct rigorous statistical analysis and A/B testing to validate model performance, providing actionable insights to stakeholders that drive strategic business pivots.

- Mentor junior engineers and contribute to technical documentation, fostering a culture of excellence and knowledge sharing across the engineering organization.

Required Skillset :

- Demonstrated expertise in building and scaling machine learning models within production environments, backed by 5 to 8 years of hands-on experience in the field.

- Advanced proficiency in deep learning frameworks, specifically PyTorch, and a strong command of statistical modeling to solve complex, non-linear problems.

- Proven ability to manage and process large-scale datasets using big data technologies, ensuring data integrity and efficient computational performance.

- Exceptional communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders and influence cross-functional project outcomes.

- Strong academic background in Computer Science, Mathematics, or a related quantitative discipline, reflecting a deep understanding of algorithmic foundations.

- High degree of adaptability and self-motivation, with a proven track record of delivering high-quality results in remote or distributed team environments across India.