59,085 AI Professionals jobs in India

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.

• Lead the design, development, and implementation of advanced deep learning models and algorithms for diverse AI applications.
• Architect scalable and robust AI systems, from initial concept to production deployment.
• Conduct cutting-edge research in areas such as computer vision, natural language processing, reinforcement learning, and generative models.
• Optimize model performance, efficiency, and scalability for deployment in various environments.
• Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to integrate AI solutions into products and services.
• Stay abreast of the latest research papers, industry trends, and advancements in AI and machine learning.
• Mentor junior AI engineers and contribute to the team's technical growth and innovation.
• Develop and maintain high-quality code and comprehensive documentation for AI models and systems.
• Evaluate and select appropriate AI frameworks and tools for project needs.
• Contribute to the company's intellectual property through patents and publications.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Minimum of 8 years of experience in AI and machine learning, with a strong specialization in deep learning.
• Proven track record of successfully designing, building, and deploying deep learning models in production environments.
• Expertise in deep learning frameworks such as TensorFlow, PyTorch, Keras, and associated libraries.
• Proficiency in programming languages like Python, and experience with relevant AI/ML libraries.
• Deep understanding of various neural network architectures (CNNs, RNNs, Transformers, GANs).
• Strong knowledge of cloud platforms (AWS, Azure, GCP) and MLOps practices.
• Excellent problem-solving, analytical, and research skills.
• Exceptional communication and leadership abilities, with experience mentoring teams.

• Lead and conduct cutting-edge research in Deep Learning, Reinforcement Learning, Computer Vision, Natural Language Processing, or related AI fields.
• Develop novel AI algorithms and models, and advance the state-of-the-art in machine learning.
• Design and implement experiments to test and validate AI hypotheses and models.
• Publish research findings in top-tier academic conferences and journals.
• Collaborate with engineering teams to translate research breakthroughs into practical applications and products.
• Mentor junior researchers and contribute to the growth of the AI research community within the organization.
• Stay abreast of the latest advancements in AI and machine learning, identifying emerging trends and opportunities.
• Contribute to the strategic direction of the company's AI research initiatives.
• Develop and maintain high-quality, well-documented code for AI models and experiments.
• Present research findings to technical and non-technical audiences.
• Protect intellectual property through patent applications and other means.
• Evaluate and benchmark new AI technologies and frameworks.

• Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a closely related quantitative field.
• 10+ years of experience in AI research and development, with a strong focus on Deep Learning.
• Demonstrated track record of significant contributions to the field, evidenced by publications in top venues (e.g., NeurIPS, ICML, CVPR, ICLR).
• Expertise in one or more core AI areas (e.g., deep neural networks, reinforcement learning, generative models, computer vision, NLP).
• Proficiency in programming languages such as Python and experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
• Strong analytical, problem-solving, and critical-thinking skills.
• Proven ability to lead research projects and mentor other researchers.
• Excellent communication, presentation, and interpersonal skills.
• Experience with large-scale data processing and distributed computing environments is a plus.
• Ability to work independently and collaboratively in a remote research environment.

• Conduct fundamental and applied research in deep learning and artificial intelligence.
• Design, implement, and evaluate novel deep learning models and algorithms.
• Experiment with various neural network architectures and training techniques.
• Optimize model performance for accuracy, efficiency, and scalability.
• Process and analyze large-scale datasets for model training and validation.
• Collaborate with engineering teams to integrate research prototypes into production systems.
• Stay abreast of the latest advancements in AI and machine learning research.
• Publish research findings in leading academic journals and conferences.
• Contribute to the intellectual property and patent portfolio.
• Mentor junior researchers and interns.

• PhD or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Strong publication record in top AI/ML venues (e.g., NeurIPS, ICML, ICLR, CVPR).
• Deep understanding of machine learning, deep learning, and statistical modeling.
• Proficiency in Python and deep learning frameworks (TensorFlow, PyTorch, Keras).
• Experience with large-scale data processing and distributed computing.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong programming skills and software development practices.
• Effective communication and presentation skills for conveying complex research ideas.

• Conduct original research in deep learning, machine learning, and related AI fields.
• Develop, implement, and evaluate novel deep learning architectures and algorithms for various applications (e.g., computer vision, natural language processing, reinforcement learning).
• Design and execute experiments to test hypotheses and validate models.
• Publish research findings in top-tier academic conferences and journals.
• Collaborate with engineering teams to integrate research prototypes into production systems.
• Stay abreast of the latest advancements in AI and machine learning research globally.
• Mentor junior researchers and interns, providing guidance and technical leadership.
• Contribute to the intellectual property portfolio through patents and publications.
• Analyze large datasets to extract insights and identify patterns relevant to AI model development.
• Develop efficient training methodologies and optimize model performance for scalability and speed.
• Present research findings and project updates to technical and non-technical audiences.
• Contribute to defining the long-term research vision and strategy for the AI team.
• Ensure ethical considerations and responsible AI practices are integrated into research and development.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Strong publication record in leading AI/ML conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL).
• Deep understanding of fundamental deep learning concepts, neural network architectures (CNNs, RNNs, Transformers), and optimization techniques.
• Proficiency in programming languages such as Python and libraries like TensorFlow, PyTorch, Keras.
• Experience with large-scale data processing and distributed computing frameworks.
• Strong analytical and problem-solving skills.
• Excellent written and verbal communication skills.
• Ability to work independently and collaboratively in a fast-paced research environment.
• Experience with cloud platforms (AWS, GCP, Azure) for AI workloads is a plus.
• Demonstrated ability to conduct cutting-edge research and deliver impactful results.

• Conduct research and development in deep learning, machine learning, and related AI fields.
• Design, implement, and evaluate novel deep learning models and algorithms.
• Experiment with various neural network architectures, training techniques, and optimization strategies.
• Process and analyze large datasets to extract meaningful insights and inform model development.
• Collaborate with cross-functional teams to integrate AI solutions into products and services.
• Stay abreast of the latest research trends and advancements in AI and deep learning.
• Publish research findings in reputable conferences and journals.
• Develop and maintain robust, well-documented code for AI models and experiments.
• Contribute to the strategic direction of the AI research group.
• Mentor junior researchers and contribute to knowledge sharing within the team.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Proven track record of research and publication in top-tier AI conferences and journals.
• Strong theoretical understanding of deep learning concepts (e.g., CNNs, RNNs, Transformers).
• Proficiency in Python and deep learning frameworks (e.g., TensorFlow, PyTorch).
• Experience with data preprocessing, feature engineering, and model evaluation.
• Familiarity with cloud computing platforms (AWS, GCP, Azure) and MLOps.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and collaboration skills for a remote team environment.