6788 Tensorflow Jobs - Page 23

Notice Period : Immediate - 15 Days About the Role :We are seeking a highly skilled Senior Data Scientist to join our team and contribute to cutting-edge projects. As a key member of our data science team, you will leverage your expertise in machine learning, natural language processing, and data engineering to develop innovative solutions that drive business value. Responsibilities :- Machine Learning Model Development : Design, develop, and deploy advanced machine learning models, focusing on natural language processing tasks such as text classification, sentiment analysis, and language generation.- Data Engineering : Extract, transform, and load (ETL) data from various sources, ensuring data quality and consistency.- NLP Techniques : Apply state-of-the-art NLP techniques, including language models and text processing, to solve complex problems.- Python and ML Frameworks : Utilize Python programming language and popular ML frameworks like PyTorch or TensorFlow to build efficient and scalable models.- Cloud and Containerization : Leverage cloud platforms (GCP, AWS) and containerization technologies (Docker) for efficient deployment and management of ML models.- Database Management : Work with relational databases (Postgres, MySQL) to store, manage, and query large datasets.- Knowledge Graphs and ML Publications : Contribute to the development of knowledge graphs and stay updated with the latest advancements in the field through research and publications. Qualifications :Experience : 4-7 years of hands-on experience in data science, with a strong focus on machine learning and natural language processing.Technical Skills : - Proficiency in Python programming language.- Deep understanding of machine learning algorithms and techniques.- Expertise in NLP, including language models and text processing.- Familiarity with ML frameworks like PyTorch or TensorFlow.- Experience with cloud platforms (GCP, AWS) and containerization (Docker).- Knowledge of relational databases (Postgres, MySQL).Soft Skills : - Strong problem-solving and analytical skills.- Excellent communication and collaboration abilities.- Ability to work independently and as part of a team. Benefits :- Competitive salary and benefits package.- Opportunities for professional growth and development.- Collaborative and supportive work environment.

Roles & Responsibilities : - Responsible for developing new features and models as part of our core product through applied research. - Understand, apply and extend state-of-the-art NLP research to better serve our customers. - Work closely with engineering, product, and customers to scientifically frame the business problems and come up with the underlying AI models - Design, implement, test, deploy, and maintain innovative data and machine learning solutions to accelerate our business. - Think creatively to identify new opportunities and contribute to high-quality publications or patents. Desired Qualifications and Experience : - At Least 1 year of professional experience. - Bachelors in Computer Science or related fields from the top colleges. - Extensive knowledge and practical experience in one or more of the following areas : machine learning, deep learning, NLP, recommendation systems, information retrieval. - Experience applying ML to solve complex business problems from scratch. - Experience with Python and a deep learning framework like Pytorch/Tensorflow. - Awareness of the state of the art research in the NLP community. - Excellent verbal and written communication and presentation skills.

Responsibilities - Conduct feature engineering, data analysis, and data exploration to extract valuable insights.- Develop and optimize Machine Learning models to achieve high accuracy and performance.- Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness.- Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback.- Collaborate with cross-functional teams to align ML solutions with business goals.- Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models.- Bring in the latest advancements in ML and AI to drive innovation. Required Skills - 4-5 years of hands-on experience in Machine Learning and Deep Learning.- Strong expertise in feature engineering, data exploration, and data preprocessing.- Experience with imbalanced datasets and techniques to improve model generalization.- Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks.- Strong mathematical and statistical knowledge with problem-solving skills.- Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Skills - Experience with Big Data technologies (Hadoop, Spark, etc.)- Familiarity with containerization and orchestration tools (Docker, Kubernetes).- Experience in automating ML pipelines with MLOps practices.- Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Responsibilities - Conduct feature engineering, data analysis, and data exploration to extract valuable insights.- Develop and optimize Machine Learning models to achieve high accuracy and performance.- Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness.- Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback.- Collaborate with cross-functional teams to align ML solutions with business goals.- Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models.- Bring in the latest advancements in ML and AI to drive innovation. Required Skills - 4-5 years of hands-on experience in Machine Learning and Deep Learning.- Strong expertise in feature engineering, data exploration, and data preprocessing.- Experience with imbalanced datasets and techniques to improve model generalization.- Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks.- Strong mathematical and statistical knowledge with problem-solving skills.- Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Skills - Experience with Big Data technologies (Hadoop, Spark, etc.)- Familiarity with containerization and orchestration tools (Docker, Kubernetes).- Experience in automating ML pipelines with MLOps practices.- Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Responsibilities - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Required Skills - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Skills - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Responsibilities - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Required Skills - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Skills - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Responsibilities - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Required Skills - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Skills - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Responsibilities - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Required Skills - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Skills - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Job Title: AI/ML Architect Location: Bangalore / Pune Experience: 10+ Years Job Type: Full-Time | Permanent Work Mode: Hybrid Job Summary We are seeking an experienced and visionary AI/ML Architect to lead the end-to-end design, development, deployment, and operationalization of advanced AI/ML and Generative AI (GenAI) solutions on cloud platforms. The ideal candidate will possess deep technical expertise in ML architecture, GenAI frameworks, Retrieval-Augmented Generation (RAG) pipelines, cloud-native deployment, and MLOps practices. You will work closely with cross-functional teams, clients, and engineering teams to define scalable AI strategies and deliver cutting-edge solutions across various domains. Key Responsibilities Customer Engagement & Solution Architecture Interact with clients and stakeholders to gather business and technical requirements and translate them into scalable AI/ML solutions. Architect and design AI/ML systems across AWS, GCP, or Azure with a strong focus on cloud-native and cost-optimized architecture. Create detailed system design documents, architecture diagrams, and technical roadmaps. Define data architecture, storage, and retrieval strategies tailored to AI/ML workflows. GenAI & RAG Architecture Lead the design and implementation of Generative AI solutions using LLMs, LangChain, LlamaIndex, Prompt Engineering, and vector databases such as Pinecone, FAISS, Weaviate, or Elasticsearch. Architect RAG (Retrieval-Augmented Generation) pipelines for enterprise use cases including knowledge management, chatbot development, and document summarization. Implement prompt orchestration, retrieval optimization, and grounding techniques to enhance LLM output accuracy and relevance. AI/ML Model Development & MLOps Guide the development of Python-based APIs, data preprocessing workflows, and model training pipelines. Design and implement robust CI/CD pipelines for ML model deployment using tools like SageMaker, Vertex AI, or Azure ML. Define and implement model monitoring, retraining, and performance management strategies for production-grade ML systems. Ensure best practices in versioning, reproducibility, model lineage, and auditability (MLOps/LLMOps). Technical Leadership & Governance Review and approve system designs, PoCs, and implementation approaches. Provide hands-on leadership and mentorship to data scientists, ML engineers, and software developers. Lead architectural decision-making, code quality reviews, and sprint grooming sessions. Champion best practices in security, compliance, scalability, and performance optimization for AI/ML solutions. Project Management & Collaboration Own end-to-end technical delivery of AI/ML and GenAI projects across multiple domains (e.g., BFSI, Retail, Healthcare, Manufacturing). Coordinate with product owners, business analysts, data engineers, and DevOps teams to ensure seamless delivery. Manage stakeholder expectations, project timelines, and resource allocation efficiently. Required Qualifications 10+ years of overall IT experience, with minimum of 5+ years in designing, developing, deploying, and operationalizing AI/ML solutions. Minimum 23 years of experience in architecting end-to-end AI/ML solutions, including design, implementation, and production deployment. Proven experience in GenAI, LLMs, RAG architecture, prompt engineering, and orchestration tools like LangChain, LlamaIndex, etc. Hands-on with vector databases (e.g., Pinecone, FAISS, Elasticsearch) and unstructured data retrieval. Deep knowledge of Machine Learning and Deep Learning algorithms: CNNs, RNNs, LSTMs, Transformers, etc. Experience in Natural Language Processing (NLP), including language modeling, summarization, classification, and NER. Strong expertise in Python, with frameworks like PyTorch, TensorFlow, HuggingFace, NumPy, and Pandas. Demonstrated experience in designing cloud-native AI/ML solutions on AWS, GCP, or Azure. Skilled in deploying models via services like SageMaker, Vertex AI, Azure ML, or using containers and Kubernetes. Solid understanding of MLOps/LLMOps lifecycle: pipeline automation, model registry, monitoring, CI/CD. Excellent communication, leadership, and stakeholder management skills. Preferred Qualifications Certification in AWS/GCP or ML specializations. Experience in leading large-scale AI transformation programs. Why Join Us? Work with cutting-edge GenAI and AI/ML technologies and projects. Collaborate with top-tier clients and drive real-world impact. Leadership opportunities in a growing AI/ML practice.

We are seeking a skilled DevOps Engineer with strong experience in Google Cloud Platform (GCP) to support AI/ML project infrastructure. The ideal candidate will work closely with data scientists, ML engineers, and developers to build and manage scalable, secure, and automated pipelines for AI/ML model training, testing, and deployment. Responsibilities: Design and manage cloud infrastructure to support AI/ML workloads on GCP. Develop and maintain CI/CD pipelines for ML models and applications. Automate model training, validation, deployment, and monitoring processes using tools like Kubeflow, Vertex AI, Cloud Composer, Airflow, etc. Set up and manage infrastructure as code (IaC) using tools such as Terraform or Deployment Manager. Implement robust security, monitoring, logging, and alerting systems using Cloud Monitoring, Cloud Logging, Prometheus, Grafana, etc. Collaborate with ML engineers and data scientists to optimize compute environments (e.g., GPU/TPU instances, notebooks). Manage and maintain containerized environments using Docker and Kubernetes (GKE). Ensure cost-efficient cloud resource utilization and governance. Required Skills Bachelor's degree in engineering or relevant field Must have 4 years of proven experience as DevOps Engineer with at least 1 year on GCP Strong experience with DevOps tools and methodologies in production environments Proficiency in scripting with Python, Bash, or Shell Experience with Terraform, Ansible, or other IaC tools. Deep understanding of Docker, Kubernetes, and container orchestration Knowledge of CI/CD pipelines, automated testing, and model deployment best practices. Familiarity with ML lifecycle tools such as MLflow, Kubeflow Pipelines, or TensorFlow Extended (TFX). Experience in designing conversational flows for AI Agents/chatbot

Position: Senior AI/ML Engineer GCP Location: Hyderabad/Bangalore/Pune Work Mode: Hybrid About the Company: Relanto is a global advisory, consulting, and technology services partner, empowering customers to accelerate innovation by harnessing the power of Data and AI, Automation, NextGen Planning, and Cloud Solutions. Overview: We're seeking an experienced individual (5-10 years) specializing in AI/ML to build and deploy cloud-based machine learning solutions. You'll work with Google Cloud Platform services to create scalable AI systems and APIs that integrate with various ML models. What You'll Do: Design and implement end-to-end ML pipelines in GCP Build and optimize AI models for production deployment using Vertex AI Develop RESTful APIs for ML model serving Implement vector search capabilities using BigQuery ML Create automated testing and deployment pipelines for ML models Set up model monitoring and performance tracking Optimize model inference and serving capabilities Must Have Skills: Strong Python programming with ML frameworks (PyTorch, TensorFlow) Experience with large language models and prompt engineering Proficiency in GCP AI services (Vertex AI, Cloud ML Engine) Vector search implementation (BigQuery ML, Matching Engine) RESTful API development with FastAPI/Flask Container orchestration with Docker and Google Kubernetes Engine (GKE) CI/CD pipeline experience for ML workflows Why Join Us: Competitive salary and benefits. Opportunities for professional growth and development. Collaborative and inclusive work culture. Flexible working arrangements for work-life balance. Exposure to innovative data analytics and visualization projects.

Responsibilities - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Required Skills - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Skills - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Job Area: Engineering Group, Engineering Group > Systems Engineering General Summary: The Advanced Tech R&D team is looking for a research engineer with a passion for machine learning applied to generative audio, video, and natural language use cases. You will be working with a team of machine learning experts to develop advanced technology and solutions for mobile phones, headsets, and variety of IoT devices as well as cloud outlets. The team includes and works with algorithm, hardware and software engineers across company to develop, port newly designed solutions to real live prototypes shown at tradeshows and other customer events, and support commercialization activities in upcoming products. Responsibilities Develop innovative machine learning algorithms for Audio and speech generative models,; file corresponding papers and patent disclosures; achieve state-of-the-art performance and beyond in various /audio/NLP applications Combine features from multi-modalities such as video, audio, sensors, and location After successful demos to technical and business audiences, work with commercialization teams to transfer and deploy newly developed solutions onto Qualcomm platforms and customer devices Minimum Qualifications R&D experience of audio and speech generative networks, audio/speech synthesis, speech restoration, text to speech kind of models Familiarity with recent trends in machine learning (diffusion models, U-Nets, Transformer, BERT, BART, etc.) and traditional statistical modeling/feature extraction techniques Preferred Qualifications R&D experience developing generative models in audio and speech Proficiency in designing, implementing and training DL algorithms in high-level languages/frameworks (e.g. PyTorch, TensorFlow) Willingness to engage in hands-on R&D in modeling of audio/speech/text data Working in cross disciplinary, geographically-dispersed teams Education RequiredMaster's degree in Computer Engineering / Computer Science / Electrical Engineering PreferredDoctorate, Computer Engineering / Computer Science / Electrical Engineering 2+ years of R&D experience in Computer Vision/image/NLP/multimodal applications in academic/industry Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field.

Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: CPU architecture team is driving the core math libraries needed for ML/AI acceleration. This position/s will expose you to Qualcomm’s cutting edge SoC and ML/AI platforms in the industry. Participate in Optimizing the core ML kernels using the latest advancements like SME, SVE of the ARM CPU architecture and enhance the performance of the ML models on the CPU of the QCOM Soc Required Skills== 3+ experince with Understanding of ARM CPU architecture fundamentals and ARM Arch64 ISA Optimizing kernels for vector Processors Understanding of the basic linear algebra functions used in AI/ML Algorithm design (logic, critical thinking) Performance Evaluation and Optimization of the applications for ARM architecture Inferencing of the ML models written in Pytorch/TensorFlow/Keras Understanding of the typical Open-Source Library framework design Preferred Skills=== Strong Programming skills and deep understanding of the ARM ISA understanding of the algorithms suitable for Vector and matrix accelerators Strong Analytical and debugging skills Good understanding of Optimizing the Linear Algebra algorithms Performance evaluation using QEMU, Simulators, Emulators and on Real Hardware Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field. 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.

Job Area: Engineering Group, Engineering Group > Systems Engineering General Summary: We are looking for Developer Advocates to enable developers building with generative AI and AI-driven hardware applications. You will engage with the community, create resources to onboard developers on our platforms. Qualcomm products touch multiple industries and applications. These applications span across mobile, laptops, mixed-reality, robotics, industrial IoT, among others. You will closely collaborate with product, e ngineering and regional sales teams to drive awareness and engagement for our platforms. You are a builder. You love to write code, more so, bring AI models to various a pplications. You can effortlessly integrate open - source models (Large or small), distill ed models and embed them in application s . T hese could be language-based u s e-cases , computer-vision, audio or other applied areas of AI. You are a great community builder. You like to network, engage, ideate and help the ecosystem realize their development goals. You are a constant learner, you thrive on writing code, content, documentatio n, videos that enhances development experience for developers writing on Qualcomm hardware. Your experience and learnings from the community will drive product improvements. You will influence future feature prioritization s , improve tooling , foster ideas for collaboration. In the process, you will end up creating a rich repository of community contributed sample applications, content, tutorial, etc. You will also engage with community builders, influencers to seed sub-ecosystems for constant engagement and outreach. The i deal candidate has e xperience in building end to end applications for one or more of Computer Vision, Audio, LVM, LLM use cases using AI/ML tools/workflow on Linux/ Windows for CPU, GPU and AI accelerators . Responsibilities Develop plans to engage with external developers focused on at least one of the following application areasIoT, Automotive, Microsoft device ecosystem. Cross-functional collaboration across software, hardware engineering, developer marketing and product management teams. Understand trends in ML model design, and workflow through application developer engagements and latest academic research . Develop and ensure sample application comprehensiveness for AI on Linux/ Windows on Snapdragon to cover the gamut of models used, and use-cases including use of additional snapdragon optimized libraries outside of Snapdragon AI functions. Interface with 3rd party application developers and other cross-site and cross-functional teams to arrive at easy-to-use sample application, and documentation that are directly leveraged by 3rd party app developers for Windows on Snapdragon Contribute new features and designs to the Qualcomm AI toolkit to enhance the workflow experience of Application Developers Minimum Qualifications Bachelor's or advanced degree in computer science, artificial intelligence, or a related field. and 6 + years of Software Engineering, Systems Engineering, or related work experience. Preferred Qualifications Excellent understanding of AI frameworks (e.g., TensorFlow, PyTorch ), GPU programming, and parallel computing. Experience with large language models/foundational models' development and deployment a plus Good Understanding of complete AI Software stack and familiarity with AI performance tuning techniques on GPU, NPU based systems Experience with development of end-to-end AI application on Windows using Windows ML, DirectML Experience in full workflow involved in training and deployment of models on servers and porting to client Windows compute platforms involving model inference deployment and performance tuning Proficiency in programming languages such as Python, C++ Excellent communication skills to articulate complex technical concepts to non-technical and technical stakeholders. Strong leadership abilities to motivate and guide development teams. Detail-oriented with strong problem-solving, analytical, and debugging skills Demonstrated ability to learn, think and adapt in a fast-changing environment Familiarity with software development methodologies, version control systems, and agile project management practices. 12+ years’ experience in application development involving High Performance Computing with 5+ years in AI application development on Windows Bachelors in Computer Science or Electrical Engineering Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.

Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces. Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. 2+ years of work experience with Programming Language such as C, C++, Java, Python, etc. General Summary As a Qualcomm Machine Learning Engineer, you will create and implement machine learning techniques, frameworks, and tools that enable the efficient utilization of state-of-the-art machine learning solutions over a broad set of technology verticals or designs. In this position you will be responsible for assisting with the software design and development of the Qualcomm AI Stack, SDKs and associated tools, targeting Snapdragon platforms. You will have the opportunity to show your passion for software design and development with your analytical, design, programming, and debugging skills. Responsibilities Software development of the AI orchestration framework, engine, and tools to develop agentic workflows and execution of the latest Neural Networks on Snapdragon chips. Validate the performance and accuracy of your software through detailed analysis and test of the use cases. Minimum Qualifications 7+ years software development experience using C/C++ and/or Python Strong software development skills (e.g. data structure and algorithm design, object oriented or other software design paradigm knowledge, software debugging and testing, etc.) Experience in developing applications using Inter-Process Communication (IPC), like AIDL or SOME/IP. Strong communication skills (verbal, presentation, written) Preferred Qualifications Experience in developing embedded applications with low level interactions between operating systems (e.g., Linux, Android, Windows, QNX) and Hardware. Experience using/integrating Qualcomm AI Stack products (e.g. QNN, SNPE, QAIRT) Experience with LLM, LVM, LMM models, and other NN architectures. Experience with Machine Learning frameworks (e.g., Tensor Flow, Pytorch, Keras). Software development experience with Java Ability to collaborate across a globally diverse team and multiple interests Education RequiredBachelor's degree in Engineering, Information Systems, Computer Science, or related field. PreferredBachelor's Computer Science, Computer Engineering, or Electrical Engineering

Job Area: Engineering Group, Engineering Group > Machine Learning Engineering General Summary: CPU architecture team is driving the core math libraries needed for ML/AI acceleration. This position/s will expose you to Qualcomm’s cutting edge SoC and ML/AI platforms in the industry. Participate in Optimizing the core ML kernels using the latest advancements like SME, SVE of the ARM CPU architecture and enhance the performance of the ML models on the CPU of the QCOM Soc Required Skills== 7+ experince with Understanding of ARM CPU architecture fundamentals and ARM Arch64 ISA Optimizing kernels for vector Processors Understanding of the basic linear algebra functions used in AI/ML Algorithm design (logic, critical thinking) Performance Evaluation and Optimization of the applications for ARM architecture Inferencing of the ML models written in Pytorch/TensorFlow/Keras Understanding of the typical Open-Source Library framework design Preferred Skills=== Strong Programming skills and deep understanding of the ARM ISA understanding of the algorithms suitable for Vector and matrix accelerators Strong Analytical and debugging skills Good understanding of Optimizing the Linear Algebra algorithms Performance evaluation using QEMU, Simulators, Emulators and on Real Hardware Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. 2+ years of work experience with Programming Language such as C, C++, Java, Python, etc.

Responsibilities - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Required Skills - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Skills - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Position Overview Job Title: AI Lead , VP Location: Pune, India Role Description Engineer is responsible for managing or performing work across multiple areas of the bank's overall IT Platform/Infrastructure including analysis, development, and administration. It may also involve taking functional oversight of engineering delivery for specific departments. Work includes: Planning and developing entire engineering solutions to accomplish business goals Building reliability and resiliency into solutions with appropriate testing and reviewing throughout the delivery lifecycle Ensuring maintainability and reusability of engineering solutions Ensuring solutions are well architected and can be integrated successfully into the end-to-end business process flow Reviewing engineering plans and quality to drive re-use and improve engineering capability Participating in industry forums to drive adoption of innovative technologies, tools and solutions in the Bank. Deutsche Bank’s Corporate Bank division is a leading provider of cash management, trade finance and securities finance. We complete green-field projects that deliver the best Corporate Bank - Securities Services products in the world. Our team is diverse, international, and driven by shared focus on clean code and valued delivery. At every level, agile minds are rewarded with competitive pay, support, and opportunities to excel. You will work as part of a cross-functional agile delivery team. You will bring an innovative approach to software development, focusing on using the latest technologies and practices, as part of a relentless focus on business value. You will be someone who sees engineering as team activity, with a predisposition to open code, open discussion and creating a supportive, collaborative environment. You will be ready to contribute to all stages of software delivery, from initial analysis right through to production support. What We’ll Offer You As part of our flexible scheme, here are just some of the benefits that you’ll enjoy Best in class leave policy Gender neutral parental leaves 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Employee Assistance Program for you and your family members Comprehensive Hospitalization Insurance for you and your dependents Accident and Term life Insurance Complementary Health screening for 35 yrs. and above Your Key Responsibilities Proven ability to design, build, and deploy end-to-end AI/ML systems in production. Expertise in data science, including statistical analysis, experimentation, and data storytelling. Experienced in working with large-scale, real-world datasets for model training and analysis. Comfortable navigating urgency, ambiguity, and fast-changing priorities. Skilled at solving complex ML problems independently, from idea to implementation. Strong leadership experience building and guiding high-performing AI teams. Hands-on with deep learning, NLP, LLMs, and classical ML techniques. Fluent in model experimentation, tuning, optimisation, and evaluation at scale. Solid software engineering background and comfort working with data and full-stack teams. Experience with cloud platforms (GCP, AWS, Azure) and production-grade ML pipelines. Bias for action — willing to jump into code, data, or ops to ship impactful AI products. Your Skills And Experience PhD in Computer Science, Data Science, Machine Learning, AI, or a related field. Strong programming skills in Python (preferred), with experience in Java, Scala, or Go a plus. Deep expertise with ML frameworks like TensorFlow, PyTorch, Scikit-learn. Experience with large-scale datasets, distributed data processing (e.g. Spark, Beam, Airflow). Solid foundation in data science: statistical modeling, A/B testing, time series, and experimentation. Proficient in NLP, deep learning, and working with transformer-based LLMs. Experience with MLOps practices — CI/CD, model serving, monitoring, and lifecycle management. Hands-on with cloud platforms (GCP, AWS, Azure) and tools like Vertex AI, SageMaker, or Databricks. Strong grasp of API design, system integration, and delivering AI features in full-stack products. Comfortable working with SQL/NoSQL, and data warehouses like BigQuery or Snowflake. Familiar with ethical AI, model explainability, and secure, privacy-aware AI development How We’ll Support You Training and development to help you excel in your career Coaching and support from experts in your team A culture of continuous learning to aid progression A range of flexible benefits that you can tailor to suit your needs About Us And Our Teams Please visit our company website for further information: https://www.db.com/company/company.htm We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively. Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group. We welcome applications from all people and promote a positive, fair and inclusive work environment.

Job Title Digital Transformation Lead, (Mumbai) About Godrej Agrovet Godrej Agrovet Limited (GAVL) is a diversified, Research & Development focused agri- business Company, dedicated to improving the productivity of Indian farmers by innovating products and services that sustainably increase crop and livestock yields. GAVL holds leading market positions in the different businesses in which it operates - Animal Feed, Crop Protection, Oil Palm, Dairy and Poultry and Processed Foods. With FY ’18- ’19 Sales of 6000 Crore INR, GAVL has a pan India presence with sales of over a million tonnes annually of high quality feed and cutting-edge nutrition products for cattle, poultry, aqua feed and specialty feed. Apart from these businesses, the Company has a joint venture with the ACI group of Bangladesh for animal feed business in Bangladesh. Godrej Agrovet has 50 manufacturing facilities across India with a network of 10,000 rural distributors/dealers and over 2500 employees. Our People Philosophy Core to our employer brand, is the philosophy of tough love. We expect a lot from our team members, differentiate on the basis of performance and potential through career opportunities and rewards and lay particular emphasis on developing, mentoring and training. We believe that passionate, rounded individuals with diverse interests make for better Godrejites. And we understand that our team members play multi-faceted roles. This is why we encourage them, not just to explore their whole selves, but also create an enabling space for them to do so. Watch ‘Why Godrej’ by Nadir Godrej, a video on our people philosophy. https://www.youtube.com/watch?v=RxiHCMR64Hs&feature=emb_logo Read more about our people philosophy here. https://godrejcareers.com/people-philosophy.aspx Yo Position Summary: As a skilled Data Scientist, you will leverage your analytical skills to uncover insights from complex datasets, build predictive models, and inform data-driven decisions across the organization. You’ll work closely with cross-functional teams, including business, engineering, and product, to apply advanced statistical methods, machine learning, and domain knowledge to solve real-world problems. Job Responsibilities Data Cleaning, Preprocessing & exploration: Prepare data for analysis, ensuring quality, consistency, and completeness by handling missing values, outliers, and transforming data. Explore and analyze large and complex datasets to identify patterns, trends, and anomalies Machine Learning Model Development: Build, train, and deploy machine learning models on the Databricks platform, leveraging tools such as MLflow for experiment with techniques like regression, classification, clustering, and time series analysis Model Evaluation & Deployment: Develop and select features to improve model performance, leveraging Databricks' distributed computing capabilities for efficient processing. Familiarity with CI/CD tools (e.g., Jenkins, GitLab) for automating deployment and testing of data pipelines Collaboration: Collaborate with data engineers, analysts, and business stakeholders to understand business requirements and translate them into data-driven solutions. Data Visualization and Reporting: Create visualizations and dashboards within Databricks, Power BI and other tools to communicate insights to technical and non-technical stakeholders. Continuous Learning: Stay up to date with the latest developments in data science, machine learning, and industry best practices to continually enhance skills and processes. Technical Skills Knowledge of statistical analysis techniques, hypothesis testing, and machine learning Familiarity with NLP, time series analysis, and computer vision or A/B testing Databricks and Apache Spark: Proficiency with Databricks, Spark DataFrames and MLlib Programming: Proficiency in (Python, TensorFlow, Pandas, scikit-learn, PySpark, NumPy) with experience in writing scalable code for large datasets SQL: Strong SQL skills for data extraction, manipulation, and analysis Familiarity with MLflow for tracking, model versioning, and reproducibility. Familiarity with cloud data storage and processing tools (e.g., Azure Data Lake, AWS S3). Qualifications Education: Bachelor’s degree in Statistics, Mathematics, Computer Science, or a related field Experience: 3+ years of experience in a data science or analytical role. Job location: Vikhroli, Mumbai.