As a Research Scientist / Research Engineer (Computer Vision & Generative), you will drive cutting‑edge AI research focused on computer vision and generative modeling, delivering novel solutions that push the boundaries of visual perception and synthesis. You will collaborate with cross‑functional teams to transform research insights into production‑ready applications, ensuring scalability, robustness, and real‑world impact. Your role will involve designing experiments, analyzing results, and iterating on models to achieve state‑of‑the‑art performance in diverse visual tasks. You will also publish findings in top-tier conferences and foster a culture of continuous learning and technical excellence within the organization.
**Requirements**
𝗞𝗲𝘆 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀
Design, implement, and benchmark advanced computer vision algorithms for image understanding and generation.
Develop and refine diffusion models and other generative frameworks tailored to specific application domains.
Conduct rigorous experimental evaluation and ablation studies to validate model performance.
Collaborate with software teams to integrate research prototypes into scalable production pipelines.
Publish research papers and present at leading conferences to establish thought leadership.
Mentor junior researchers and engineers, fostering a collaborative research environment.
Identify and prioritize high-impact research problems that align with business objectives.
Monitor emerging trends in AI and propose innovative solutions leveraging new techniques.
Maintain comprehensive documentation of research methodologies and codebases.
Participate in cross‑disciplinary projects to merge vision, NLP, and multimodal AI research.
𝗪𝗵𝗮𝘁 𝗠𝗮𝗸𝗲𝘀 𝗬𝗼𝘂 𝗮 𝗚𝗿𝗲𝗮𝘁 𝗙𝗶𝘁
PhD or master’s degree in Computer Science, Electrical Engineering, or related field with a focus on computer vision or generative modeling.
3+ years of experience in AI research or engineering, preferably in a production setting.
Proficiency with diffusion models, GANs, VAEs, and related generative architectures.
Strong programming skills in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow.
Demonstrated ability to publish at least one paper in a top-tier CV or AI conference.
Deep understanding of image processing pipelines and large‑scale training optimizations.
Experience with cloud GPU workloads and distributed training frameworks.
Excellent communication and teamwork skills, capable of translating complex ideas to diverse audiences.
Proven track record of delivering end‑to‑end AI solutions from research to deployment.
Passion for staying ahead of industry trends and continuously expanding technical horizons.
This page helps Indian job seekers prepare for Python interviews for backend, data engineering and data analyst roles, whether you are a fresher facing your first technical round or an experienced developer aiming for a senior position. It has 60 questions in three levels, easy, medium and hard, each with a concise sample answer and, where it helps, runnable Python 3.12 code. Topics include data structures, OOP, generators, decorators, the GIL and concurrency, type hints, testing and performance. Answer each question aloud in your own words first, then compare with the sample answer and run the code to check your understanding.
Questions you may be asked
What is the difference between mutable and immutable types in Python?
What is the difference between a list and a tuple?
Free · takes a minute · your resume fills your profile
Research Scientist / Research Engineer (Computer Vision & Generative
Chennai
1
Full time
On-site
3+ years
₹10L – ₹24L a year (estimate, typical for IT Jobs in India, 807 posts)
