Machine Learning Engineer (MLE) / Researcher (MLR)

Job Synopsis

We are seeking highly skilled and motivated professionals in Machine Learning to join our growing Data & AI team. Whether you are an engineer passionate about building robust, sustainable AI systems, or a researcher eager to push the boundaries of machine learning innovation, we offer an environment that fosters autonomy, technical depth, and meaningful impact. In this role, you will work on cutting-edge technologies across Generative AI, NLP, and Document AI, collaborating with cross-functional teams to solve real-world business problems. As an individual contributor, you will play a critical role in shaping and executing AI-driven solutions—either through research and experimentation or through system design, development, and deployment. You will be empowered to explore emerging models and frameworks, contribute to internal best practices, and help bring AI innovation from concept to production. If you thrive in a fast-paced, collaborative setting and are passionate about advancing the state of AI, this opportunity is for you.

What You Will Do

• Develop and Apply ML Models: Design and build end-to-end ML solutions or lead experiments to improve accuracy, efficiency, and scalability. • Explore and Innovate: Research and experiment with new ML techniques, especially in NLP, Generative AI, and Document Understanding, using models like Transformers and diffusion-based methods. • Production or Proof-of-Concept Delivery: Build robust ML pipelines and APIs for production (MLE) or develop proof-of-concepts and internal benchmarks (MLR). • Contribute to Internal Best Practices: Help shape methodologies for versioning, evaluation, experiment tracking (using MLFlow, Airflow, etc.), and model monitoring. • Drive AI Adoption: Collaborate with product managers, engineers, and R&D teams to identify and implement AI solutions aligned with business needs. • Ensure Responsible AI: Incorporate ethical AI practices, including bias mitigation, transparency, and regulatory compliance, into your workflow. • Foster a Learning Culture: Lead peer reviews, contribute to internal knowledge sharing, and provide mentorship to junior team members and interns.

• Advanced degree in Computer Science, Engineering, Data Science, AI, or a related field
• Experience in Machine Learning
• Experience with NLP, Generative AI, and Document Understanding (nice-to-have)