50,742 AI Professionals jobs in India

Responsibilities

• Develop ML models for vision intelligence
• Improve existing ML layers and modules
• Build data pipelines (knowledge of backend programming in Python is required)
• Build frontend and backend applications as required for Deeplearning Applications deployments.
• Train models using Adversarial networks
• Optimize inferencing software to run at better frame rates.
• Work on video pipelines and manipulate frames using OpenCV
• Design Gstreamer pipelines and work with Deepstream.
• Handle Cloud server programming for training and inferencing of the models.

Requirements

• Candidates with previous practical experience on any the ML frameworks like TensorFlow, PyTorch, etc. should apply
• Candidates with a proven record of C++ programming, specifically in concepts like pointers, maps, vectors, etc should apply
• Candidates with no prior experience in ML/AI but who have demonstrated exceptional skills in backend/frontend development will also be given equal preference
• Candidates with previous practical experience in deep-learning and developing full-stack web apps would be preferred

Skills Required
OpenCV, Python, Machine Learning, C Programming, C++ Programming, Deep Learning, Gstreamer, MQTT, Kafka

Additional Skills Desirable

• Web development using any framework like Django, Go, Flask etc
• Knowledge of Redis, RabbitMQ, Kafka
• Experience/exposure in Nvidia tools like Deepstream, CUDA etc

Skills: c++,deep learning,kafka,nvidia,opencv,mqtt,rabbitmq,gstreamer

Deep Learning Frameworks: Familiarity with frameworks like TensorFlow, PyTorch, or Keras.

Custom Model Training: Ability to fine-tune and train models on specific datasets, understand overfitting, and apply regularization techniques.

Integration Skills: Proficiency in integrating AI functionalities into applications, web services, or mobile apps.

Optimization: Knowledge of optimizing model performance and reducing latency for real-time applications.

Version Control and Collaboration Tools: Proficiency with tools like Git, which are essential for collaborative development.

About
At , we are building the future of video intelligence. Our flagship platform, FizzStream, analyzes over a billion seconds of video to power real-world applications in market research, retail analytics, and sports analytics. We've achieved an industry-leading 90-92% accuracy in human activity analysis, and we're just getting started. We are a team of passionate innovators who believe in bridging cutting-edge research with production-grade solutions to create tangible impact.

The Mission
We are seeking a hands-on Senior Deep Learning Engineer to pioneer the next generation of our core Video AI capabilities. This isn't just a research role; it's an opportunity to own the full lifecycle of new features, from concept to deployment, and directly influence a product that is already a leader in its field.

What You'll Own

• Research to Production: Lead the charge in transforming state-of-the-art research (e.g., Video Language Models, multi-camera tracking) into robust, scalable, and deployed features for our core platform.
• Model Innovation & Optimization: Design, build, and meticulously optimize Deep Learning models for sophisticated human activity analysis. You'll work with the entire lifecycle, ensuring performance and efficiency.
• End-to-End System Impact: Take full ownership of key modules, ensuring their seamless integration and performance within our broader platform. You will be a bridge between our research and full-stack engineering teams, delivering cohesive and performant solutions.
• Future-Proof Our AI: Proactively explore and integrate new architectures and techniques to continuously advance our models' accuracy and scalability.

What We're Looking For

• Experience: 2-3 years of industry experience, with at least 2 years directly focused on Deep Learning for Computer Vision or Video AI. Proven success in taking models from research to production is a must.
• Technical Proficiency:
• Exceptional proficiency in Python and PyTorch.
• Deep practical expertise with ONNX for optimization and deployment.
• Hands-on experience with robust data pipelines and model deployment for Computer Vision.
• Proficiency with Linux, CUDA, and OpenCV.
• Deep Learning Expertise:
• A strong, practical understanding of fundamental Deep Learning concepts.
• Proven experience successfully implementing activity detection or object detection algorithms.
• A keen ability to critically read, understand, and implement state-of-the-art research papers.

Your DNA

• A Builder's Mindset: You are driven by seeing your work in a real product and are excited by the challenges of translating complex ideas into elegant, production-ready solutions.
• Relentless Curiosity: You have a passion for exploring new algorithms, continuously learning, and experimenting with new approaches.
• Ownership & Impact: You are a self-starter who takes complete ownership of a project from start to finish, driving it to success and ensuring its impact is felt by the product and our users.

Join The Journey
If you are ready to make a significant impact on the future of AI and contribute to a platform that analyzes billions of seconds of video, we want to hear from you. Apply today to help us build intelligence that matters.

• Conduct cutting-edge research in deep learning and related AI fields.
• Design, develop, and implement novel deep learning models and algorithms.
• Experiment with different neural network architectures and training techniques.
• Process and analyze large-scale datasets for model training and evaluation.
• Evaluate model performance, identify limitations, and propose improvements.
• Collaborate with engineers to deploy research models into production systems.
• Stay abreast of the latest advancements in AI and machine learning research.
• Publish research findings in top-tier conferences and journals.
• Mentor junior researchers and interns.
• Contribute to grant proposals and research project planning.

• Ph.D. or Master's degree in Computer Science, AI, Machine Learning, or a related quantitative field.
• Proven track record of research and publications in leading AI conferences/journals.
• Deep understanding of various deep learning architectures (CNNs, RNNs, Transformers, GANs).
• Expertise in deep learning frameworks like TensorFlow, PyTorch, or JAX.
• Proficiency in Python and relevant libraries (NumPy, SciPy, Pandas).
• Experience with large-scale data processing and distributed computing.
• Familiarity with cloud computing platforms (AWS, Azure, GCP).
• Strong analytical, mathematical, and problem-solving skills.
• Excellent written and verbal communication skills.
• Ability to work independently and collaboratively in a research-intensive environment.

• Conduct cutting-edge research in areas such as deep learning, machine learning, computer vision, and natural language processing.
• Develop and implement novel AI algorithms and models to solve complex problems.
• Design and execute experiments to validate research hypotheses and measure performance.
• Analyze large datasets to extract insights and inform model development.
• Stay abreast of the latest advancements in AI and machine learning literature and conferences.
• Collaborate with engineering teams to integrate research prototypes into production systems.
• Publish research findings in top-tier academic journals and present at international conferences.
• Contribute to the intellectual property portfolio through patent applications.
• Mentor junior researchers and interns.
• Participate in defining the long-term research vision for the company.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Proven track record of research and publications in top AI conferences (e.g., NeurIPS, ICML, ICLR, CVPR).
• Deep expertise in deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Strong programming skills in Python and experience with scientific computing libraries.
• Solid understanding of machine learning theory, algorithms, and statistical modeling.
• Experience with large-scale data processing and distributed computing.
• Excellent analytical, critical thinking, and problem-solving skills.
• Ability to work independently and collaboratively in a hybrid team environment.
• Strong communication and presentation skills.
• Experience with cloud platforms (AWS, Azure, GCP) is a plus.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Proven track record of research and publications in reputable AI/ML venues.
• Strong theoretical foundation in machine learning, deep learning, and statistics.
• Proficiency in programming languages such as Python and experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
• Experience with large-scale data processing and distributed computing.
• Excellent analytical and problem-solving skills.
• Strong communication and teamwork abilities.
• Experience with cloud platforms (AWS, Azure, GCP) is a plus.

• Conduct fundamental and applied research in deep learning and artificial intelligence.
• Develop and implement novel deep learning models and algorithms.
• Design and execute experiments to evaluate model performance.
• Publish research findings in top-tier AI conferences and journals.
• Collaborate with a team of researchers and engineers on cutting-edge projects.
• Explore and apply AI techniques to solve complex real-world problems.
• Contribute to the company's intellectual property through patents and publications.
• Stay abreast of the latest advancements in AI and machine learning.

• Ph.D. in Computer Science, AI, Machine Learning, or a related quantitative field.
• 3+ years of research experience in deep learning (post-doctoral or industry).
• Strong publication record in leading AI conferences (e.g., NeurIPS, ICML, ICLR).
• Proficiency in deep learning frameworks like TensorFlow or PyTorch.
• Expertise in areas such as computer vision, NLP, or reinforcement learning.
• Excellent programming skills in Python.
• Strong analytical and problem-solving abilities.
• Ability to conduct independent research and work effectively in a remote team.