Role Overview :

As an AI Engineer, you will be at the forefront of building scalable, intelligent systems that transform complex data into actionable business insights.

You will collaborate closely with cross-functional teams, including data scientists, product managers, and engineering leads, to design and deploy state-of-the-art models that solve real-world challenges.

Your work will directly influence product innovation and user experience, ensuring our platforms remain at the cutting edge of the industry.

This role offers the opportunity to work in a high-impact environment across our key hubs in Bangalore, Hyderabad, Chennai, or Mumbai, driving the next generation of AI-powered solutions for our global clientele.

Key Responsibilities :

- Architect and implement end-to-end machine learning pipelines to automate decision-making processes for internal stakeholders, significantly reducing manual operational overhead.

- Develop and fine-tune Generative AI and NLP models to enhance customer engagement platforms, ensuring higher accuracy and more personalized user interactions.

- Optimize deep learning architectures using PyTorch to improve model inference speed and scalability, directly contributing to a more seamless experience for our end users.

- Partner with engineering teams to integrate AI models into production environments, ensuring robust performance, reliability, and security across all deployed applications.

- Conduct rigorous experimentation and performance analysis to iterate on existing algorithms, maintaining our competitive edge in the rapidly evolving AI landscape.

Required Skillset :

- Demonstrated expertise in building and deploying advanced Machine Learning and Deep Learning models, with a proven track record of translating research concepts into production-grade software.

- Proficiency in leveraging PyTorch for complex neural network design, alongside a deep understanding of NLP techniques and the latest advancements in Generative AI frameworks.

- Strong ability to communicate technical complexities to non-technical stakeholders, ensuring alignment between business objectives and engineering execution.

- A collaborative mindset that thrives in a hybrid work environment, capable of working effectively with distributed teams across Bangalore, Hyderabad, Chennai, and Mumbai.

- A solid academic foundation in Computer Science, Mathematics, or a related quantitative field, complemented by a continuous learning approach to stay ahead of industry trends.