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Principal Scientist / Senior Staff Research Engineer (Computer Vision & Deep Learning)

Swaayatt Robots -
Bhopal, Madhya Pradesh

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Job details

Qualifications

Image processing
Doctoral degree
PyTorch
Computer vision
Software deployment
Math
Machine learning
Deep learning
Scalability
AI

Full job description

Join Us

We Are Hiring

Swaayatt Robots is seeking motivated and passionate individuals eager to contribute to the cutting-edge fields of autonomous driving and AI. Our vision is to lead globally in these areas, and we aim to attract those who share our drive. Joining our team means working on groundbreaking projects that push technological boundaries and shape the future of transportation. We foster a collaborative environment where innovation and continuous learning are encouraged.

If you're excited to be at the forefront of transformative technologies and ready to take on challenges, join us on this journey. At Swaayatt Robots, you'll have the opportunity to make a real impact and help revolutionize autonomous driving and AI. Be part of our visionary team and help shape the future of these industries. Apply now for a rewarding career with us!

At Swaayatt Robots (स्वायत्त रोबोट्स) we are hiring a Principal Scientist / Senior Staff Research Engineer (Computer Vision & Deep Learning) to build next-generation perception systems for autonomous driving, both on- and off-roads. We are looking for an exceptional researcher/engineer who can define the technical direction for perception research across the organization.

This role is for someone with a first-principles understanding of machine learning and deep learning - someone who can reason about optimization, representation learning, network design, and training dynamics at a fundamental level while translating research into production-scale systems.

What we're looking for:

Deep expertise in computer vision, perception, and modern deep learning
Strong mathematical foundation in optimization, probability, linear algebra, and statistical learning
Thorough understanding of optimization algorithms, convergence behavior, gradient flow, loss landscapes, regularization techniques and normalization strategies
Proven ability to design novel neural network architectures and develop task-specific loss functions, training objectives, and optimization strategies
Expertise in supervised and self-supervised multimodal learning paradigms
Hands-on experience with multi-sensor fusion involving camera, LiDAR, radar, and IMU/GNSS
Solid grasp of 2D and 3D perception, geometric vision, state estimation, sensor calibration, and uncertainty modeling
Experience training large-scale models on distributed GPU clusters with an understanding of data pipelines, dataset curation, sampling strategies, curriculum learning, hard-negative mining, domain adaptation, and data quality assessment
- optimizer selection, learning-rate scheduling, initialization strategies, gradient clipping, mixed-precision training, and memory-efficient training techniques
Experience building production-grade perception systems with an understanding of latency, scalability, robustness, model compression, quantization, and deployment constraints
Strong software engineering skills with production experience in PyTorch, CUDA, distributed training frameworks, and high-performance ML infrastructure
Ability to mentor senior engineers, conduct technical reviews, define research roadmaps, and establish engineering best practices across the perception stack

Preferred Background:

PhD in Computer Vision, Machine Learning, Robotics, Artificial Intelligence, or a related field. Exceptional candidates with an MS from a Tier-1 school and significant research or industry impact will also be considered.

We're looking for someone who is naturally curious, enjoys solving fundamental research problems, challenges conventional approaches with sound scientific reasoning, and elevates the technical standard of everyone around them. It's a high-ownership technical leadership role shaping the future of our perception stack.

Want to join Swaayatt Robots?

Check out current openings and send your resume to [email protected]

Apply Now

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