9 Tensor Flow Jobs

Responsibilities: AI/ML Model Development: 1. Design and implement machine learning models and algorithms to address specific business needs. 2. Develop and optimize algorithms for accuracy, efficiency, and scalability. Data Analysis and Preprocessing: 1. Collect, preprocess, and analyze large datasets to extract meaningful insights. 2. Develop data pipelines and maintain data quality for model training and evaluation. Integration and Deployment: 1. Integrate machine learning models into existing systems and applications. 2. Deploy models in production environments and monitor their performance. Research and Innovation: 1. Stay updated with the latest advancements in AI and machine learning technologies. 2. Conduct research to explore new techniques and methodologies that can enhance our solutions. Collaboration: 1. Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to understand requirements and deliver effective solutions. 2. Provide technical guidance and support to team members and stakeholders.

Job overview: In this role, youll be part of our Data Science team. With a track record of innovation and taking large ML-based products from conception to delivering value, you will be responsible for developing ML and deep learning models to improve innovation within our Knowledge Graph curation. Your success will result in informed decision-making and stakeholder empowerment for Knowledge Graph use cases within Crayon. You will also directly impact the evolution of our content catalogue. Can you say Yes, I have! to the following? experience with developing solutions using machine learning, operation research and pattern searching methods on large scale data. B.E/B.Tech/MS in Machine Learning, Computer Science, Applied Statistics, Mathematics, or related fields. PhD is a plus Good understanding of statistical models like hierarchical models, stochastic models, time series, survival and econometric models Expert in at least one of the deep learning frameworks such as PyTorch, MxNet, or Tensor flow Hands-on experience in using Spark (Scala or Py spark) to process data at large scale and database schema design for ML pipelines a must Contribution to open-source ML packages/research publications will be a huge bonus

Roles and Responsibilities Design, develop, and deploy advanced AI models with a focus on generative AI, including transformer architectures (e.g., GPT, BERT, T5) and other deep learning models used for text, image, or multimodal generation. Work with extensive and complex datasets, performing tasks such as cleaning, preprocessing, and transforming data to meet quality and relevance standards for generative model training. Collaborate with cross-functional teams (e.g., product, engineering, data science) to identify project objectives and create solutions using generative AI tailored to business needs. Implement, fine-tune, and scale generative AI models in production environments, ensuring robust model performance and efficient resource utilization. Develop pipelines and frameworks for efficient data ingestion, model training, evaluation, and deployment, including A/B testing and monitoring of generative models in production. Stay informed about the latest advancements in generative AI research, techniques, and tools, applying new findings to improve model performance, usability, and scalability. Documentandcommunicatetechnicalspecifications, algorithms, and project outcomes to technical and non-technical stakeholders, with an emphasis on explainability and responsible AI practices. Qualifications Required Educational Background: Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or a related field. Relevant Ph.D. or research experience in generative AI is a plus. Experience: 8-12 years of experience in machine learning, with 2+ years in designing and implementing generative AI models or working specifically with transformer-based models. Skills and Experience Required GenerativeAI: Transformer Models, GANs, VAEs, Text Generation, Image Generation Machine Learning: Algorithms, Deep Learning, Neural Networks Programming: Python, SQL; familiarity with libraries such as Hugging Face Transformers, PyTorch, Tensor Flow MLOps: Docker, Kubernetes, MLflow, Cloud Platforms (AWS, GCP, Azure) Data Engineering: Data Preprocessing, Feature Engineering, Data Cleaning

Dear Candidate, We are hiring a Robotics Engineer to develop intelligent robotic systems for automation and industrial applications. The role requires expertise in robotics programming, sensor integration, and AI-driven automation. Key Responsibilities: Design and develop robotic systems using ROS, C++, and Python. Implement AI-based perception and motion planning algorithms. Integrate sensors, actuators, and embedded controllers. Optimize robotic navigation and real-time decision-making. Test and validate robotic applications in real-world environments. Required Skills & Qualifications: Robotics Frameworks: ROS, OpenCV, TensorFlow Programming: C++, Python, MATLAB Hardware Integration: LIDAR, IMU, Cameras, Actuators Control Systems: PID, Kalman Filters, Path Planning Experience with autonomous vehicles or robotic arms is a plus. Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Srinivasa Reddy Kandi Delivery Manager Integra Technologies

Job Description: Core Skills 3+ years of hands-on experience in AI development, with a strong focus on Traditional AI , Generative AI , and Agent-based AI . Strong proficiency in Python , along with experience using AI libraries and frameworks like TensorFlow , PyTorch , Keras , Hugging Face , and others. Experience with Natural Language Processing (NLP) , Reinforcement Learning (RL) , Computer Vision , and Deep Learning . Solid understanding of AI algorithms , model training , data preprocessing , and evaluation metrics . Experience in working with cloud platforms such as AWS, Azure, or Google Cloud for deploying and scaling AI systems. Familiarity with Generative AI models (like GPT, DALL•E, etc.) and Agent-based systems (autonomous agents, bots, recommendation engines, etc.). Preferred Skills Experience with Generative AI technologies and creative AI solutions for content generation, such as text, images, or videos. Knowledge of AI ethics , bias mitigation , and explainability techniques in AI systems. Hands-on experience in Reinforcement Learning or Multi-Agent Systems . Understanding of DevOps principles and CI/CD pipelines for AI systems deployment. Experience with Data Engineering and working with large datasets. Soft Skills Strong problem-solving and analytical skills. Excellent communication skills with the ability to articulate complex technical concepts to non-technical stakeholders. Ability to lead a team, mentor junior developers, and foster collaboration across departments. Passionate about AI technology and continuous learning.

Job Summary: We are looking for a talented AI/ML Developer with full-stack development skills to join our team and contribute to the development of Agentic AI applications. The ideal candidate should have a strong foundation in machine learning, deep learning, natural language processing (NLP), and full-stack web development. You will be responsible for designing, building, and deploying AI-driven applications that can autonomously interact with users and external systems Key Responsibilities: Design, develop, and implement AI/ML models for Agentic AI applications. Build scalable full-stack applications integrating AI models with frontend and backend services. Develop APIs and microservices to support AI-driven interactions. Work with cloud platforms (AWS, Azure, or GCP) to deploy and scale AI applications. Optimize and fine-tune AI models for efficiency and accuracy. Implement real-time data processing pipelines and integrate with external APIs. Ensure application security, performance, and scalability. Collaborate with cross-functional teams to refine business requirements and translate them into technical solutions. Conduct testing and debugging to ensure robustness and reliability. Required Skills & Qualifications: AI/ML Expertise: Experience with Python, Tensor Flow, Py Torch, Open AI API, Lang Chain, or similar AI frameworks. Full-Stack Development: Proficiency in frontend (React.js, Vue.js, Angular) and backend (Node.js, Django, Flask, Fast API) technologies. Cloud & DevOps: Experience with AWS, Azure, or GCP, and familiarity with Docker, Kubernetes, and CI/CD pipelines. Data Engineering: Knowledge of databases (SQL & NoSQL), data pipelines, and real-time streaming technologies. API Development: Hands-on experience with RESTful and Graph QL APIs. NLP & LLMs: Understanding of transformer models, conversational AI, and large language models (LLMs). Version Control & Collaboration: Experience with Git, GitHub, and Agile methodologies. Strong problem-solving skills and ability to work independently. Preferred Qualifications: Experience working on Generative AI or Autonomous Agents. Knowledge of vector databases and retrieval-augmented generation (RAG). Familiarity with reinforcement learning and self-improving AI systems. Exposure to AI-driven chatbots or virtual assistants. Contribution to open-source AI projects or published research papers.

Dear Candidate, We are hiring a Robotics Engineer to develop intelligent robotic systems for automation and industrial applications. The role requires expertise in robotics programming, sensor integration, and AI-driven automation. Key Responsibilities: Design and develop robotic systems using ROS, C++, and Python. Implement AI-based perception and motion planning algorithms. Integrate sensors, actuators, and embedded controllers. Optimize robotic navigation and real-time decision-making. Test and validate robotic applications in real-world environments. Required Skills & Qualifications: Robotics Frameworks: ROS, OpenCV, TensorFlow Programming: C++, Python, MATLAB Hardware Integration: LIDAR, IMU, Cameras, Actuators Control Systems: PID, Kalman Filters, Path Planning Experience with autonomous vehicles or robotic arms is a plus. Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Delivery Manager Integra Technologies

Job overview: In this role, youll be part of our Data Science team. With a track record of innovation and taking large ML-based products from conception to delivering value, you will be responsible for developing ML and deep learning models to improve innovation within our Knowledge Graph curation. Your success will result in informed decision-making and stakeholder empowerment for Knowledge Graph use cases within Crayon. You will also directly impact the evolution of our content catalogue. Can you say Yes, I have! to the following? experience with developing solutions using machine learning, operation research and pattern searching methods on large scale data. B.E/B.Tech/MS in Machine Learning, Computer Science, Applied Statistics, Mathematics, or related fields. PhD is a plus Good understanding of statistical models like hierarchical models, stochastic models, time series, survival and econometric models Expert in at least one of the deep learning frameworks such as PyTorch, MxNet, or Tensor flow Hands-on experience in using Spark (Scala or Py spark) to process data at large scale and database schema design for ML pipelines a must Contribution to open-source ML packages/research publications will be a huge bonus

Responsibilities: AI/ML Model Development: 1. Design and implement machine learning models and algorithms to address specific business needs. 2. Develop and optimize algorithms for accuracy, efficiency, and scalability. Data Analysis and Preprocessing: 1. Collect, preprocess, and analyze large datasets to extract meaningful insights. 2. Develop data pipelines and maintain data quality for model training and evaluation. Integration and Deployment: 1. Integrate machine learning models into existing systems and applications. 2. Deploy models in production environments and monitor their performance. Research and Innovation: 1. Stay updated with the latest advancements in AI and machine learning technologies. 2. Conduct research to explore new techniques and methodologies that can enhance our solutions. Collaboration: 1. Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to understand requirements and deliver effective solutions. 2. Provide technical guidance and support to team members and stakeholders.