Senior Research Engineer - Artificial Intelligence/Machine Learning (5-10 yrs)

We are looking for a Senior Research Engineer to lead applied innovation and push the boundaries of what's possible in our product and technology stack.

This role sits at the intersection of deep research and real-world impact where ideas are not just published but implemented.

Youll work alongside top minds in engineering, product, and academia to solve high-complexity problems and translate research insights into scalable solutions.

Key Responsibilities :

Research & Prototyping :

- Drive exploratory and applied research in [domain e.g., machine learning, computer vision, systems engineering].

- Develop proofs of concept, simulations, and working prototypes.

Innovation Pipeline :

- Identify research directions aligned with company strategy.

- Translate concepts into tangible product or technology roadmaps.

Collaboration :

- Work cross-functionally with engineering, data science, and product teams to implement research outputs in production-grade systems.

Technical Leadership :

- Review architectures, guide implementation decisions, and mentor junior researchers and engineers.

Publication & IP :

- Contribute to internal knowledge and external thought leadership through patents, white papers, or conference publications (as per company policy).

Performance Optimization :

- Analyze system-level performance of research models or algorithms.

- Drive improvements in speed, accuracy, efficiency, or scalability.

Ideal Profile :

- Bachelors/Masters/PhD in Computer Science, Electrical Engineering, Applied Mathematics, or related fields.

- 510 years of experience in R&D roles, with a strong portfolio of shipped features, products, or

published research.

- Deep expertise in at least one domain: AI/ML, systems architecture, embedded systems, NLP, signal processing, etc.

- Hands-on proficiency with Python/C++/Java and relevant tools (e.g., PyTorch, TensorFlow, MATLAB, or hardware simulators).

- Strong understanding of scientific methods, algorithm design, and experimentation.