4555 Tensorflow Jobs - Page 3

Hiring for AI Developer Position: Full time location: Pan INDIA Intrested candidates share cv to mansoor@burgeonits.com Job Description: We are seeking an AI Developer experienced in designing, building, and deploying AI solutions using Microsoft Azure. The ideal candidate should be comfortable working with Azure AI services, MLOps tools, and Microsoft's machine learning ecosystem. Responsibilities: Design and develop AI/ML models using Azure Machine Learning Leverage Azure Cognitive Services (Vision, Speech, Language, etc.) to deliver intelligent features Develop and automate ML pipelines using Azure ML, Azure Data Factory, and Azure DevOps Work with Azure Databricks for data processing and model training Collaborate with business and tech stakeholders to deliver AI-powered solutions Required Skills: Strong knowledge of Python and Azure ML SDK Hands-on experience with Azure AI tools: Azure Machine Learning, Cognitive Services, Bot Framework Experience with MLOps, CI/CD in Azure (Pipelines, ML Ops) Proficiency in working with Azure Blob, Data Lake, and SQL Database Strong understanding of responsible AI principles and governance Kindly please fill the below details & share updated cv to mansoor@burgeonits.com Name as per Aadhar card Mobile no Alternate no Email id Alternate email (Because most of the mail is showing duplicate portal) Date Of Birth Pan card no(for client upload)mandatory* Total Exp Rev Exp Current company If any payroll (Name) Notice Period (If Serving any Np , Mention last working day & year) CCTC ECTC If Any offers (Yes/No) If yes how much offer &when joining date Current location & Preferred Location Happy to relocate(Yes/No) Available Interview time slots

Job Title Embedded Voice & ML Applications Engineer. We are seeking a passionate and skilled Embedded Systems Engineer with expertise in Voice and Machine Learning (ML) applications. The ideal candidate will have experience in embedded software development, real-time systems, and ML model deployment on resource-constrained devices. Key Responsibilities. Develop and optimize embedded software using C programming and RTOS (e.g., FreeRTOS). Perform board bring-up and hardware-software integration for embedded platforms. Implement and optimize DSP/ISP algorithms with a focus on low-power consumption. Port and optimize ML models using frameworks like TensorFlow Lite Micro or PyTorch for real-time performance. Work on debugging and optimizing multicore applications and utilize Neural Processing Units (NPUs). Collaborate on ML model conversion and tuning to fit memory and real-time constraints of embedded devices. Understand and write linker scripts (GCC, IAR, ARM) for embedded systems. Contribute to the development of voice-based ML applications, including keyword spotting, speech recognition, and audio classification. . Strong proficiency in C programming for embedded systems. Hands-on experience with FreeRTOS or similar RTOS. Solid understanding of DSP, ISP, and embedded low power optimization techniques. Experience with ML frameworks such as TensorFlow Lite Micro or PyTorch for embedded systems. Familiarity with model quantization, pruning, and inference optimization. Experience with multicore processors and NPUs. Knowledge of linker scripts and memory layout for embedded toolchains (GCC/IAR/ARM). Strong debugging skills and use of tools like JTAG, logic analyzers, and oscilloscopes. Preferred Qualifications. Experience in voice/audio processing. Knowledge of Embedded Linux or bare-metal programming. Exposure to Edge AI and TinyML concepts. (ref:hirist.tech).

We are looking for an experienced Embedded Voice & ML Applications Engineer with a strong background in embedded systems and machine learning for edge devices. The role involves developing and optimizing real-time applications for voice and ML use cases on low-power, resource-constrained platforms. Key Responsibilities. Develop embedded software in C for voice and ML applications. Work with RTOS (FreeRTOS) for real-time processing. Perform board bring-up and low-level hardware interfacing. Optimize systems for low power and performance efficiency. Implement and port models using TensorFlow Lite Micro or PyTorch. Debug multicore applications and integrate with NPUs. Work with linker scripts (GCC, IAR, ARM) and embedded toolchains. Handle DSP/ISP processing and real-time data flows. Required Skills. 5+ years of experience in embedded development. Strong in C programming, RTOS, and hardware-level debugging. Experience with ML frameworks and real-time model deployment. Good understanding of multicore systems, NPU, and signal processing. Familiarity with embedded toolchains and linker scripts. (ref:hirist.tech).

The Role. The ideal candidate for this role will be an innovative self-starter. You will be an AI expert with experience in making architectural tradeoffs to transform AI performance for a variety of use cases. You will collaborate with internal and external development engineers (architecture, hardware, validation, software services). You will contribute to development, support device characterization and benchmarking :. Proficiency in Large Models & Deep Neural Networks. Hands-on experience in working with large models & deep neural networks. Expertise in LLMs with working knowledge of large language models (LLMs). Extensive experience in System platform Architecture. Experience in Development Preferable for memory/storage/ any embedded system. In depth knowledge and extensive experience in dealing with Standardizations/Technical Papers/Patents. Extensive experience with C/C++ and Python programming. Develop and fine-tune LLMs (GPT, Llama, Mistral, Falcon, Claude, etc.) for domain-specific applications. Implement RAG pipelines using LlamaIndex, LangGraph, and vector databases (FAISS, Pinecone, Weaviate, ChromaDB) to enhance response accuracy. Build AI-powered chatbots and autonomous agents using LangGraph, CrewAI, LlamaIndex, and OpenAI APIs. Optimize and deploy generative AI models for real-time inference using cloud platforms (AWS, GCP, Azure) and MLOps tools (Docker, Kubernetes, MLflow). Fine-tune models using LoRA, QLoRA, PEFT, and RLHF to improve efficiency and personalization. Develop AI-driven workflows for structured reasoning and decision-making using CrewAI and LangGraph. Integrate multi-modal AI models (text, image, speech) into enterprise solutions. Implement memory and retrieval strategies for LLM-based systems using vector search and caching techniques. Ensure AI models follow ethical AI guidelines, bias mitigation, and security best :. Tech in Computer Science, Electrical Engineering. 8 to 10 Years of experience in relevant domain. Strong analytical & abstract thinking ability as well as technical communication skills. Able to work independently and perform in fast paced environment. Ability to troubleshoot and debug complex issues. Working Knowledge on Device Driver is desirable. Prior experience in working with Skills :. Languages & Frameworks Proficiency in Python, PyTorch, TensorFlow, JAX. (ref:hirist.tech).

Job Title : AI Engineer - Azure AI. Key Responsibilities : We are seeking a highly skilled and motivated AI Engineer to join our team. In this role, you will leverage your expertise in AI technologies and the Microsoft ecosystem to design, build, and deploy intelligent agents and automation solutions that enhance business processes and deliver value to our clients. Candidates must have extensive experience in the Microsoft environment. You will collaborate with cross-functional teams to create innovative solutions using Microsoft tools and platforms. Responsibilities : Agent Development : - Design, implement, and optimize AI agents using Microsoft Azure Framework and related technologies. - Develop custom AI solutions leveraging Power Automate, Azure OpenAI, and other Microsoft tools. Solution Integration : - Deploy AI solutions within client environments, ensuring scalability and seamless integration with existing systems. - Work with stakeholders to identify automation opportunities and tailor solutions to business needs. AI Algorithm and Model Implementation : - Design and implement machine learning algorithms, focusing on natural language processing (NLP) and conversational AI. - Perform data preprocessing, feature engineering, and model training to create high-performing solutions. Collaboration and Support : - Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to deliver integrated solutions. - Provide technical guidance and support to ensure the successful adoption and use of AI-driven tools. Continuous Improvement : - Stay updated on advancements in AI, machine learning, and Microsofts AI technologies. - Contribute to knowledge sharing by conducting training sessions and documenting best practices. Preferred Skills : - Strong knowledge of Azure OpenAI, Azure AI Search Index and open source libraries such as LangChain and LlamaIndex. - Proficiency in Python and its AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). - Familiarity with building and managing cloud-based solutions, preferably on Microsoft Azure. - Understanding of conversational AI technologies and chatbot frameworks. - Experience with data analysis tools and techniques to uncover insights and optimize models. Requirements : - Bachelors or Masters degree in Computer Science, Data Science, or a related field. - Proven experience in developing and deploying AI/ML models in real-world applications. - Strong programming skills, especially in Python, and familiarity with version control systems like Git. - Extensive experience in the Microsoft environment and related technologies.

AI/ML Developer - Python1 Position Title : AI/ML Developer - Python No of position 1 Location Pune / Hyderabad : Design machine learning systems Research and implement machine learning algorithms and tools Manage and direct research and development processes to meet the needs of our AI strategy Develop machine learning applications in alignment with project requirements and business goals Perform machine learning tests and statistical analysis in order to fine-tune the machine learning systems Select appropriate datasets and data representation methods Extend existing machine learning libraries and frameworks Train systems and retrain as necessary Work with the engineering and leadership teams on the functional design, process design, prototyping, testing, and training of AI/ML solutions Advise leaders on technology, strategy, and policy issues related to AI/ML Coordinating with development teams to determine application requirements. Writing scalable code using Python programming language. Testing and debugging applications. Developing back-end components. Integrating user-facing elements using server-side logic. Assessing and prioritizing client feature requests. Integrating data storage solutions. Coordinating with front-end developers. Reprogramming existing databases to improve functionality. Developing digital tools to monitor online traffic. Work with the Data Scientists and Data Engineers to create production quality. Machine Learning pipelines and solutions with an emphasis on Performance, Scalability, Reliability, and Maintainability. Build components and libraries that will improve existing solutions and improve the delivery of new ones Required Skills and Experience 3+ years of experience applying AI to practical uses Experience with deep learning, NLP, and TensorFlow Experience writing robust code in Python, Java, and/or R Experience in REST API development, NoSQL database design, and RDBMS design and optimizations Knowledge of basic algorithms and object-oriented and functional design principles Knowledge of data structures, data modeling, and software architecture Knowledge of math, probability, statistics, and algorithms Knowledge of machine learning frameworks Knowledge of machine learning libraries such as scikit-learn Excellent communication skills Strong analytical and problem solving skills Preferred Qualifications Bachelor's degree in a relevant technology field Experience with cloud environments

AI/ML Engineers1 AI/ML (Artificial Intelligence/Machine Learning) engineers with 3+ years of experience and having knowledge of Python, Microsoft OpenAI, and GitHub Copilot, along with AWS (Amazon Web Services) cloud experience. Design, implement, and optimize machine learning algorithms using Python to solve complex business problems. Build Prototypes, demos and Gen AI and AI/ML Solutions. Leverage Microsoft OpenAI and GitHub Copilot for enhanced code suggestions and collaboration. Train, evaluate, and fine-tune machine learning models on large datasets using frameworks like TensorFlow or PyTorch. Utilize OpenAI's models for natural language processing tasks and generate code snippets with Copilot to expedite development. Perform data preprocessing tasks, including cleaning, normalization, and feature engineering, to prepare datasets for machine learning models. Use Python libraries and tools to extract meaningful features from raw data. Deploy and manage machine learning models on AWS cloud infrastructure. Utilize AWS services like SageMaker for model training, deployment, and monitoring. Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders. Document code, models, and processes to ensure transparency and facilitate knowledge transfer. Implement CI/CD pipelines to automate the testing, deployment, and monitoring of machine learning models. Use GitHub Copilot to enhance code quality and efficiency in the development lifecycle. Monitor the performance of deployed models and optimize them for scalability, speed, and accuracy. Implement best practices for model versioning and management. Ensure that machine learning solutions adhere to security standards and compliance requirements. Implement secure coding practices and data protection measures. Stay updated on the latest advancements in AI/ML, Python, OpenAI, and cloud technologies. Experiment with new models, techniques, and tools to drive innovation within the team. Troubleshoot and debug issues related to machine learning models, Python code, and cloud infrastructure. Collaborate with support teams to address production issues promptly. Provide guidance and training to team members on AI/ML best practices, Python coding standards, and effective use of OpenAI and Copilot. Conduct workshops or knowledge-sharing sessions within the organization. Optimize cloud resources to ensure cost-effectiveness in model training and deployment on AWS. Proficiency in python, Gen AI, Microsoft OpenAI, and GitHub Copilot, along with AWS Strong knowledge of Python, TensorFlow and PyTorch Strong knowledge of NLPs like Microsoft OpenAI and Copilot Knowledge of cloud platforms like Amazon Web Services. Solid understanding of SQL and data manipulation techniques for data extraction, transformation, and loading. Ability to understand business requirements and translate them into meaningful solutions. Strong analytical and problem-solving skills. Excellent communication and collaboration skills to work effectively with business users, data analysts, and other stakeholders. Educational Qualifications Bachelor's degree in computer science, software engineering, mathematics, or a related field is often the minimum requirement Knowledge of Data science will be added advantage .

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 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 Title: MLOps Engineer - ML Platform Hiring Title: Flexible based on candidate experience – about Staff Engineer preferred : We are seeking a highly skilled and experienced MLOps Engineer to join our team and contribute to the development and maintenance of our ML platform both on premises and AWS Cloud. As a MLOps Engineer, you will be responsible for architecting, deploying, and optimizing the ML & Data platform that supports training of Machine Learning Models using NVIDIA DGX clusters and the Kubernetes platform, including technologies like Helm, ArgoCD, Argo Workflow, Prometheus, and Grafana. Your expertise in AWS services such as EKS, EC2, VPC, IAM, S3, and EFS will be crucial in ensuring the smooth operation and scalability of our ML infrastructure. You will work closely with cross-functional teams, including data scientists, software engineers, and infrastructure specialists, to ensure the smooth operation and scalability of our ML infrastructure. Your expertise in MLOps, DevOps, and knowledge of GPU clusters will be vital in enabling efficient training and deployment of ML models. Responsibilities will include: Architect, develop, and maintain the ML platform to support training and inference of ML models. Design and implement scalable and reliable infrastructure solutions for NVIDIA clusters both on premises and AWS Cloud. Collaborate with data scientists and software engineers to define requirements and ensure seamless integration of ML and Data workflows into the platform. Optimize the platform’s performance and scalability, considering factors such as GPU resource utilization, data ingestion, model training, and deployment. Monitor and troubleshoot system performance, identifying and resolving issues to ensure the availability and reliability of the ML platform. Implement and maintain CI/CD pipelines for automated model training, evaluation, and deployment using technologies like ArgoCD and Argo Workflow. Implement and maintain monitoring stack using Prometheus and Grafana to ensure the health and performance of the platform. Manage AWS services including EKS, EC2, VPC, IAM, S3, and EFS to support the platform. Implement logging and monitoring solutions using AWS CloudWatch and other relevant tools. Stay updated with the latest advancements in MLOps, distributed computing, and GPU acceleration technologies, and proactively propose improvements to enhance the ML platform. What are we looking for: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Proven experience as an MLOps Engineer or similar role, with a focus on large-scale ML and/or Data infrastructure and GPU clusters. Strong expertise in configuring and optimizing NVIDIA DGX clusters for deep learning workloads. Proficient in using the Kubernetes platform, including technologies like Helm, ArgoCD, Argo Workflow, Prometheus , and Grafana . Solid programming skills in languages like Python, Go and experience with relevant ML frameworks (e.g., TensorFlow, PyTorch ). In-depth understanding of distributed computing, parallel computing, and GPU acceleration techniques. Familiarity with containerization technologies such as Docker and orchestration tools. Experience with CI/CD pipelines and automation tools for ML workflows (e.g., Jenkins, GitHub, ArgoCD). Experience with AWS services such as EKS , EC2, VPC, IAM, S3, and EFS. Experience with AWS logging and monitoring tools. Strong problem-solving skills and the ability to troubleshoot complex technical issues. Excellent communication and collaboration skills to work effectively within a cross-functional team. We would love to see: Experience with training and deploying models. Knowledge of ML model optimization techniques and memory management on GPUs. Familiarity with ML-specific data storage and retrieval systems. Understanding of security and compliance requirements in ML infrastructure.

Job Area: Engineering Group, Engineering Group > Machine Learning Engineering General Summary: Job Overview: Qualcomm is a company of inventors that unlocked 5G - ushering in an age of rapid acceleration in connectivity and new possibilities that will transform industries, create jobs, and enrich lives. But this is just the beginning. It takes inventive minds with diverse skills, backgrounds, and cultures to transform 5Gs potential into world-changing technologies and products. This is the Invention Age - and this is where you come in. We are investing in several supporting technologies including 4G, 5G, Edge Computing, and Deep Learning.The Qualcomm AI team is developing hardware and software for Machine Learning solutions spanning the data center, edge, infrastructure, automotive markets and beyond. We are seeking ambitious, bright and innovative engineers with experience in Machine learning frameworks, compiler technology, vectorization and optimization, and machine learning toolchains.Job activities span the whole product life cycle from early design to commercial deployment. The environment is fast-paced and requires cross-functional interaction on a daily basis so good communication, planning and execution skills are a must. We are looking to staff engineers at multiple levels in systems & software, integration and test. Details of one of the roles we are looking to staff are listed below. Responsibilities: Research, design, develop, enhance, and implement the different components of machine learning framework, compilers based on performance and code-size needs of the customer workloads and benchmarks. Analyze software requirements, determine the feasibility of design within the given constraints, consult with architecture and HW engineers, and implement software solutions best suited for Qualcomm's SOCs. Analyze and identify system level integration issues, interface with the software development, integration and test teams. Minimum Qualifications Bachelor's degree in Engineering, Information Systems, Computer Science, or related field. 8+ years Systems Engineering or related work experience. Preferred Qualifications Has internal working knowledge of Machine learning frameworks like Pytorch, Tensorflow. Has experience in model level optimization using techniques like torch compile. LLVM or any industrial strength compiler development experience is a plus. Knowledge of the structure and function of the compiler internals. Hands on experience writing SIMD and/or multi-threaded high-performance code is a plus. Hands-on experience implementing DSP Kernels a plus Hands-on Experience in C/C++, Python development (5+ years) Hands-on Experience with Object Orientated Design, TDD development solutions such as GoogleTest etc. (4+ years) Experience with Source Code and Configuration management tools, git knowledge is required Willingness to work in a cohesive software development environment with ability to work on low level implementation (code & test) and interfacing with hardware and simulators Experience in neural network architectures + ML compiler workload synthesis, a plus Prior working experience of hardware accelerators and hardware software co-design Experience in using C++ 14/17 (advanced features) Experience at both the firmware (RTOS) and system level (Linux) in SOC Experience of profiling software and optimization techniques Passion to drive to develop leading-edge "deep learning" framework and algorithms working on mobile and embedded platforms. Minimum Qualifications: Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, 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. Job Title: MLOps Engineer - ML Platform Hiring Title: Flexible based on candidate experience – about Staff Engineer preferred : We are seeking a highly skilled and experienced MLOps Engineer to join our team and contribute to the development and maintenance of our ML platform both on premises and AWS Cloud. As a MLOps Engineer, you will be responsible for architecting, deploying, and optimizing the ML & Data platform that supports training of Machine Learning Models using NVIDIA DGX clusters and the Kubernetes platform, including technologies like Helm, ArgoCD, Argo Workflow, Prometheus, and Grafana. Your expertise in AWS services such as EKS, EC2, VPC, IAM, S3, and EFS will be crucial in ensuring the smooth operation and scalability of our ML infrastructure. You will work closely with cross-functional teams, including data scientists, software engineers, and infrastructure specialists, to ensure the smooth operation and scalability of our ML infrastructure. Your expertise in MLOps, DevOps, and knowledge of GPU clusters will be vital in enabling efficient training and deployment of ML models. Responsibilities will include: Architect, develop, and maintain the ML platform to support training and inference of ML models. Design and implement scalable and reliable infrastructure solutions for NVIDIA clusters both on premises and AWS Cloud. Collaborate with data scientists and software engineers to define requirements and ensure seamless integration of ML and Data workflows into the platform. Optimize the platform’s performance and scalability, considering factors such as GPU resource utilization, data ingestion, model training, and deployment. Monitor and troubleshoot system performance, identifying and resolving issues to ensure the availability and reliability of the ML platform. Implement and maintain CI/CD pipelines for automated model training, evaluation, and deployment using technologies like ArgoCD and Argo Workflow. Implement and maintain monitoring stack using Prometheus and Grafana to ensure the health and performance of the platform. Manage AWS services including EKS, EC2, VPC, IAM, S3, and EFS to support the platform. Implement logging and monitoring solutions using AWS CloudWatch and other relevant tools. Stay updated with the latest advancements in MLOps, distributed computing, and GPU acceleration technologies, and proactively propose improvements to enhance the ML platform. What are we looking for: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Proven experience as an MLOps Engineer or similar role, with a focus on large-scale ML and/or Data infrastructure and GPU clusters. Strong expertise in configuring and optimizing NVIDIA DGX clusters for deep learning workloads. Proficient in using the Kubernetes platform, including technologies like Helm, ArgoCD, Argo Workflow, Prometheus , and Grafana . Solid programming skills in languages like Python, Go and experience with relevant ML frameworks (e.g., TensorFlow, PyTorch ). In-depth understanding of distributed computing, parallel computing, and GPU acceleration techniques. Familiarity with containerization technologies such as Docker and orchestration tools. Experience with CI/CD pipelines and automation tools for ML workflows (e.g., Jenkins, GitHub, ArgoCD). Experience with AWS services such as EKS , EC2, VPC, IAM, S3, and EFS. Experience with AWS logging and monitoring tools. Strong problem-solving skills and the ability to troubleshoot complex technical issues. Excellent communication and collaboration skills to work effectively within a cross-functional team. We would love to see: Experience with training and deploying models. Knowledge of ML model optimization techniques and memory management on GPUs. Familiarity with ML-specific data storage and retrieval systems. Understanding of security and compliance requirements in ML infrastructure.

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. Job Title: MLOps Engineer - ML Platform Hiring Title: Flexible based on candidate experience – about Staff Engineer preferred : We are seeking a highly skilled and experienced MLOps Engineer to join our team and contribute to the development and maintenance of our ML platform both on premises and AWS Cloud. As a MLOps Engineer, you will be responsible for architecting, deploying, and optimizing the ML & Data platform that supports training of Machine Learning Models using NVIDIA DGX clusters and the Kubernetes platform, including technologies like Helm, ArgoCD, Argo Workflow, Prometheus, and Grafana. Your expertise in AWS services such as EKS, EC2, VPC, IAM, S3, and EFS will be crucial in ensuring the smooth operation and scalability of our ML infrastructure. You will work closely with cross-functional teams, including data scientists, software engineers, and infrastructure specialists, to ensure the smooth operation and scalability of our ML infrastructure. Your expertise in MLOps, DevOps, and knowledge of GPU clusters will be vital in enabling efficient training and deployment of ML models. Responsibilities will include: Architect, develop, and maintain the ML platform to support training and inference of ML models. Design and implement scalable and reliable infrastructure solutions for NVIDIA clusters both on premises and AWS Cloud. Collaborate with data scientists and software engineers to define requirements and ensure seamless integration of ML and Data workflows into the platform. Optimize the platform’s performance and scalability, considering factors such as GPU resource utilization, data ingestion, model training, and deployment. Monitor and troubleshoot system performance, identifying and resolving issues to ensure the availability and reliability of the ML platform. Implement and maintain CI/CD pipelines for automated model training, evaluation, and deployment using technologies like ArgoCD and Argo Workflow. Implement and maintain monitoring stack using Prometheus and Grafana to ensure the health and performance of the platform. Manage AWS services including EKS, EC2, VPC, IAM, S3, and EFS to support the platform. Implement logging and monitoring solutions using AWS CloudWatch and other relevant tools. Stay updated with the latest advancements in MLOps, distributed computing, and GPU acceleration technologies, and proactively propose improvements to enhance the ML platform. What are we looking for: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Proven experience as an MLOps Engineer or similar role, with a focus on large-scale ML and/or Data infrastructure and GPU clusters. Strong expertise in configuring and optimizing NVIDIA DGX clusters for deep learning workloads. Proficient in using the Kubernetes platform, including technologies like Helm, ArgoCD, Argo Workflow, Prometheus , and Grafana . Solid programming skills in languages like Python, Go and experience with relevant ML frameworks (e.g., TensorFlow, PyTorch ). In-depth understanding of distributed computing, parallel computing, and GPU acceleration techniques. Familiarity with containerization technologies such as Docker and orchestration tools. Experience with CI/CD pipelines and automation tools for ML workflows (e.g., Jenkins, GitHub, ArgoCD). Experience with AWS services such as EKS , EC2, VPC, IAM, S3, and EFS. Experience with AWS logging and monitoring tools. Strong problem-solving skills and the ability to troubleshoot complex technical issues. Excellent communication and collaboration skills to work effectively within a cross-functional team. We would love to see: Experience with training and deploying models. Knowledge of ML model optimization techniques and memory management on GPUs. Familiarity with ML-specific data storage and retrieval systems. Understanding of security and compliance requirements in ML infrastructure.

Job Area: Engineering Group, Engineering Group > Machine Learning Engineering General Summary: Job Overview Qualcomm is a company of inventors that unlocked 5G - ushering in an age of rapid acceleration in connectivity and new possibilities that will transform industries, create jobs, and enrich lives. But this is just the beginning. It takes inventive minds with diverse skills, backgrounds, and cultures to transform 5Gs potential into world-changing technologies and products. This is the Invention Age - and this is where you come in. We are investing in several supporting technologies including 4G, 5G, Edge Computing, and Deep Learning. The Qualcomm AI team is developing hardware and software for Machine Learning solutions spanning the data center, edge, infrastructure, automotive markets and beyond. We are seeking ambitious, bright and innovative engineers with experience in Machine learning frameworks, compiler technology, vectorization and optimization, and machine learning toolchains. Job activities span the whole product life cycle from early design to commercial deployment. The environment is fast-paced and requires cross-functional interaction on a daily basis so good communication, planning and execution skills are a must. We are looking to staff engineers at multiple levels in systems & software, integration and test. Details of one of the roles we are looking to staff are listed below. Responsibilities Research, design, develop, enhance, and implement the different components of machine learning framework, compilers based on performance and code-size needs of the customer workloads and benchmarks. Analyze software requirements, determine the feasibility of design within the given constraints, consult with architecture and HW engineers, and implement software solutions best suited for Qualcomm's SOCs. Analyze and identify system level integration issues, interface with the software development, integration and test teams. Minimum Qualifications Bachelor's degree in Engineering, Information Systems, Computer Science, or related field. 8+ years Systems Engineering or related work experience. Preferred Qualifications Has internal working knowledge of Machine learning frameworks like Pytorch, Tensorflow. Has experience in model level optimization using techniques like torch compile. LLVM or any industrial strength compiler development experience is a plus. Knowledge of the structure and function of the compiler internals. Hands on experience writing SIMD and/or multi-threaded high-performance code is a plus. Hands-on experience implementing DSP Kernels a plus Hands-on Experience in C/C++, Python development (5+ years) Hands-on Experience with Object Orientated Design, TDD development solutions such as GoogleTest etc. (4+ years) Experience with Source Code and Configuration management tools, git knowledge is required Willingness to work in a cohesive software development environment with ability to work on low level implementation (code & test) and interfacing with hardware and simulators Experience in neural network architectures + ML compiler workload synthesis, a plus Prior working experience of hardware accelerators and hardware software co-design Experience in using C++ 14/17 (advanced features) Experience at both the firmware (RTOS) and system level (Linux) in SOC Experience of profiling software and optimization techniques Passion to drive to develop leading-edge "deep learning" framework and algorithms working on mobile and embedded platforms. Minimum Qualifications: Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 5+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Job Job TitleGraduate Engineer Trainee Company NameTitan Job TypeRP Job CategoryCentral Technology Services DepartmentCentral Technology Services LocationHosur, Tamil Nadu, India : Titan, a leading company in the Central Technology Services industry, is seeking a highly motivated and talented Graduate Engineer Trainee to join our team in Hosur, Tamil Nadu, India. As a Graduate Engineer Trainee, you will have the opportunity to work with cutting-edge technology and gain valuable experience in the field of Central Technology Services. Key Responsibilities: - Participate in training programs to learn about the company's products, services, and processes - Work closely with senior engineers to assist in the design, development, and implementation of new technology solutions - Conduct research and analysis to identify areas for improvement and make recommendations for process enhancements - Collaborate with cross-functional teams to support project initiatives and ensure timely delivery of projects - Assist in troubleshooting and resolving technical issues as needed - Stay updated on industry trends and advancements in technology to contribute innovative ideas to the team Qualifications: - Bachelor's degree in Engineering or a related field - Strong academic record with a minimum GPA of 3.0 - Excellent problem-solving and analytical skills - Proficiency in programming languages such as Java, C++, or Python - Familiarity with database management and SQL - Ability to work independently and in a team environment - Excellent communication and interpersonal skills - Willingness to learn and adapt to new technologies and processes Additional Parameters: - Previous internship or work experience in the Central Technology Services industry is a plus - Knowledge of Agile methodology is preferred - Willingness to relocate for future career opportunities within the company At Titan, we value diversity and equal opportunity in the workplace. We are committed to creating an inclusive environment for all employees and welcome applicants of all backgrounds to apply. Join our team and be a part of our mission to revolutionize the Central Technology Services industry. Work Experience Good knowledge in Linear Algebra, Vectors, Calculus, Statistics, Fourier Analysis Good knowledge in Signal processing Techniques like Wavelets, Shearlets, Curvelets, Bandlets etc., Good knowledge in Applied Mathematics like Gradient Descent, Convex Optimization, Lagrange, Quadratic Programming, Partial Differential Equations, and Summations Good Knowledge in machine learning algorithms, neural networks, natural language processing, and related AI technologies. Proficiency in programming languages such as C++, Python, R, Java, and experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Knowledge in data preprocessing, feature engineering, and model development and evaluation. Strong analytical and problem-solving skills, with the ability to analyze complex datasets and derive actionable insights. Good Communication & Inter Personnel Skills Major Deliverables / Tasks : 1. Discovering New Possibilities - The role should deliver the below towards new Possibilities : - New AI/ML techniques, Tools / Models / algorithms for Industry 4.0 and Smart wearables - Use-cases based on emerging trends - Data Models with Reports for efficient Algorithms - Prototype Testing and Validation 2. Algorithm/ Code Development - The role should perform the below towards meeting the above objectives: - Conduct analysis to identify patterns, trends, and insights from large and complex datasets. - Collaborate with data engineers and data scientists to ensure data quality, integrity, and accessibility for AI and ML initiatives. - Monitor and evaluate AI and ML performance metrics, providing recommendations for improvements and optimization. - Develop Standard Plug-ins and Models for easy integration 3 . Reports and Documentation The role is expected to meticulously Compile all the support Details and Documents hailing from the core activities mentioned above and deliver the Blueprint of the Development Process

Develop and deploy advanced AI solutions using the latest Generative AI techniques including: - Retrieval-Augmented Generation (RAG) pipelines. - Designing and building Agentic AI systems to automate complex decision-making workflows. - Fine-tuning Foundation and Small Language Models (SLMs) tailored for domain specific content

Data Scientist – 3 – Kotak811 Kotak811 is a Neobank incubated by Kotak Mahindra Bank, with a view of providing completely digitized banking services in the convenience of the customer’s mobile phone. 811 is an early mover in the Indian fintech space that started off as a downloadable savings bank account in 2017, post demonetization, when India took one step closer to a digital economy. The Data Scientist-3 in Bangalore (or Mumbai) will be part of the 811 Data Strategy Group that comprises Data Engineers, Data Scientists and Data Analytics professionals. He/she will be associated with one of the key functional areas such as Product Strategy, Cross Sell, Asset Risk, Fraud Risk, Customer Experience etc. and help build robust and scalable solutions that are deployed for real time or near real time consumption and integrated into our proprietary Customer Data Platform (CDP). This is an exciting opportunity to work on data driven analytical solutions and have a profound influence on the growth trajectory of a super fast evolving digital product. Key of The Role Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 7 - 10 Years of relevant experience in the space Expertise in mining AI/ML opportunities from open ended business problems and drive solution design/development while closely collaborating with engineering, product and business teams Strong understanding of advanced data mining techniques, curating, processing and transforming data to produce sound datasets. Strong experience in NLP, time series forecasting and recommendation engines preferred Create great data stories with expertise in robust EDA and statistical inference. Should have at least a foundational understanding in Experimentation design Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. Exposure to Deep Learning applications and tools like TensorFlow, Theano, Torch, Caffe preferred Experience with analytical programming languages, tools and libraries (Python a must) as well as Shell scripting. Should be proficient in developing production ready code as per best practices. Experience in using Scala/Java/Go based libraries a big plus Very proficient is SQL and other relational databases along with PySpark or Spark SQL. Proficient is using NoSQL databases. Experience in using GraphDBs like Neo4j a plus. Candidate should be able to handle unstructured data with ease. Candidate should have experience in working with MLEs and be proficient (with experience) in using MLOps tools. Should be able to consume the capabilities of said tools with deep understanding of deployment lifecycle. Experience in CI/CD deployment is a big plus. Knowledge of key concepts in distributed systems like replication, serialization, concurrency control etc. a big plus Good understanding of programming best practices and building code artifacts for reuse. Should be comfortable with version controlling and collaborate comfortably in tools like git Ability to create frameworks that can perform model RCAs using analytical and interpretability tools. Should be able to peer review model documentations/code bases and find opportunities Experience in end-to-end delivery of AI driven Solutions (Deep learning , traditional data science projects) Strong communication, partnership and teamwork skills Should be able to guide and mentor teams while leading them by example. Should be an integral part of creating a team culture focused on driving collaboration, technical expertise and partnerships with other teams Ability to work in an extremely fast paced environment, meet deadlines, and perform at high standards with limited supervision A self-starter who is looking to build grounds up and contribute to the making of a potential big name in the space Experience in Banking and financial services is a plus. However, sound logical reasoning and first principles problem solving are even more critical A typical day in the life of the job role1. As a key partner at the table, attend key meetings with the business team to bring in the data perspective to the discussions 2. Perform comprehensive data explorations around to generate inquisitive insights and scope out the problem 3. Develop simplistic to advanced solutions to address the problem at hand. We believe in making swift (albeit sometimes marginal) impact to business KPIs and hence adopt an MVP approach to solution development 4. Build re-usable code analytical frameworks to address commonly occurring business questions 5. Perform 360-degree customer profiling and opportunity analyses to guide new product strategy. This is a nascent business and hence opportunities to guide business strategy are plenty 6. Guide team members on data science and analytics best practices to help them overcome bottlenecks and challenges 7. The role will be an approximate 60% IC – 40% leading and the ratios can vary basis need and fit 8. Develop Customer-360 Features that will be integrated into the Customer Data Platform (CDP) to enhance the single view of our customer Websitehttps://www.kotak811.com/

Notice Period: (Immediate Joiner - Only) Key Responsibilities: Fine-tune and optimize Large Language Models (LLMs) for mid-to-large-scale live production-quality applications. Host and deploy LLMs on custom infrastructure, ensuring high availability and performance. Conduct LLM evaluation following best practices as outlined in the Hugging Face LLM Evaluation Guide. Collaborate with cross-functional teams to design, develop, and implement AI-driven solutions tailored to business needs. Ensure model scalability, security, and compliance with industry standards. Required Skills and Experience : Experience: 4 years of hands-on experience with Generative AI and LLMs. (Total IT experience is not a priority.) Domain Expertise: Prior experience in the fintech or financial services domain is essential. LLM Fine-Tuning: Demonstrated expertise in fine-tuning LLMs for live production environments (academic or PoC projects are not relevant). Infrastructure Management: Experience with hosting and deploying LLMs on custom infrastructure. LLM Evaluation: Proficiency in conducting LLM evaluations using industry-recognized methodologies and frameworks. Technical Skills : Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Strong understanding of LLM architectures and their optimization techniques. Familiarity with cloud-based or on-premise infrastructure for AI deployments.

Key Responsibilities: Fine-tune and optimize Large Language Models (LLMs) for mid-to-large-scale live production-quality applications. Host and deploy LLMs on custom infrastructure, ensuring high availability and performance. Conduct LLM evaluation following best practices as outlined in the Hugging Face LLM Evaluation Guide. Collaborate with cross-functional teams to design, develop, and implement AI-driven solutions tailored to business needs. Ensure model scalability, security, and compliance with industry standards. Required Skills and Experience : Experience: 4 years of hands-on experience with Generative AI and LLMs. (Total IT experience is not a priority.) Domain Expertise: Prior experience in the fintech or financial services domain is essential. LLM Fine-Tuning: Demonstrated expertise in fine-tuning LLMs for live production environments (academic or PoC projects are not relevant). Infrastructure Management: Experience with hosting and deploying LLMs on custom infrastructure. LLM Evaluation: Proficiency in conducting LLM evaluations using industry-recognized methodologies and frameworks. Technical Skills : Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Strong understanding of LLM architectures and their optimization techniques. Familiarity with cloud-based or on-premise infrastructure for AI deployments.

Role Purpose: As a Software Development Engineer in the MLOps team, you will help design and build scalable, high-performance infrastructure for deploying and serving machine learning models. Role Value: As an SDE III, youll architect robust ML infrastructure to support efficient model deployment, serving, and optimization. You'll develop CI/CD pipelines for ML workflows, utilize compiler and hardware-based optimizations to improve inference performance, and drive cost efficiency. You will also influence development processes and tooling for continuous improvement. Key Responsibilities: Design and optimize model serving infrastructure with a focus on low latency and cost efficiency Build scalable inference pipelines across different hardware acceleration options Implement monitoring and observability solutions for ML systems Collaborate with ML Engineers to define best practices for deployment Develop enterprise-grade, cost-efficient ML solutions Work closely with MLEs, QA, and DevOps teams in a distributed environment Evaluate new technologies and contribute to system architecture decisions Drive continuous improvements in ML infrastructure Required Experience & Skills: 5+ years of experience in software engineering using Python Hands-on experience with ML frameworks (especially PyTorch) Experience optimizing ML models using hardware accelerators (e.g., AWS Neuron, ONNX, TensorRT) Familiarity with AWS ML services and hardware-accelerated compute (e.g., SageMaker, Inferentia, Trainium) Proven ability to build and maintain serverless architectures on AWS Strong understanding of event-driven patterns (SQS/SNS) and caching strategies Proficiency with Docker and container orchestration tools Solid grasp of RESTful API design and implementation Focus on secure, high-quality code with experience using static code analysis tools Strong problem-solving, algorithmic thinking, and communication skills Nice to Have: Experience with model compilation, quantization, and inference benchmarking Exposure to regulated environments with compliance-heavy requirements for cloud-based solutions Role & responsibilities Preferred candidate profile

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Good to have skills : NAMinimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :These roles have many overlapping skills with GENAI Engineers and architects. Description may scaleup/scale down based on expected seniority. Roles & Responsibilities:-Implement generative AI models, identify insights that can be used to drive business decisions. Work closely with multi-functional teams to understand business problems, develop hypotheses, and test those hypotheses with data, collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.-Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services.-Optimizing existing generative AI models for improved performance, scalability, and efficiency.-Ensure data quality and accuracy-Leading the design and development of prompt engineering strategies and techniques to optimize the performance and output of our GenAI models.-Implementing cutting-edge NLP techniques and prompt engineering methodologies to enhance the capabilities and efficiency of our GenAI models.-Determining the most effective prompt generation processes and approaches to drive innovation and excellence in the field of AI technology, collaborating with AI researchers and developers-Experience working with cloud based platforms (exampleAWS, Azure or related)-Strong problem-solving and analytical skills-Proficiency in handling various data formats and sources through Omni Channel for Speech and voice applications, part of conversational AI-Prior statistical modelling experience-Demonstrable experience with deep learning algorithms and neural networks-Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.-Contributing to the establishment of best practices and standards for generative AI development within the organization. Professional & Technical Skills: -Must have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.-Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.-Must have strong knowledge of data structures, algorithms, and software engineering principles.-Must be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.-Need to have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.-Must be familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.-Need to have knowledge of software development methodologies, such as Agile or Scrum.-Possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions. Additional Information:-Must have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is highly desirable.-strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.-You possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Qualification 15 years full time education

Job Title - S&C GN AI - Insurance Decision Scientist- Analyst Management Level: 11-Analyst Location: Pune, PDC2C Must-have skills: Data Analysis Good to have skills: Ability to leverage design thinking, business process optimization, and stakeholder management skills. Job Summary : This role involves driving strategic initiatives, managing business transformations, and leveraging industry expertise to create value-driven solutions. Roles & Responsibilities: Provide strategic advisory services, conduct market research, and develop data-driven recommendations to enhance business performance. WHATS IN IT FOR YOU Accenture Global Network is a unified powerhouse that combines the capabilities of Strategy & Consulting with the force multipliers of Data and Artificial Intelligence. It is central to Accenture's future growth and Accenture is deeply invested in providing individuals with continuous opportunities for learning and growth. Youll be part of a diverse, vibrant, global community, continually pushing the boundaries of business capabilities. Accenture is also ranked 10th* on the 2023 Worlds Best Workplaces list, making it a great place to work. What you would do in this role Help the team architect, design, build, deploy, deliver, and monitor advanced analytics models for different insurance problems Collaborate with cross-functional global teams to understand complex business & engineering problems in insurance and translate them into data-driven solutions that deliver insights for action and operational improvements Consume data from multiple sources and present information in a crisp and digestible manner that delivers valuable insights to both technical and non-technical audiences Provide coaching to junior team-members on advanced analytical concepts Professional & Technical Skills: - Relevant experience in the required domain. - Strong analytical, problem-solving, and communication skills. - Ability to work in a fast-paced, dynamic environment. Who we are looking for 2-4 years of experience in data-driven techniques including exploratory data analysis and data pre-processing & machine learning to solve business problems for the Insurance Industry Bachelors degree in mathematics, statistics, economics, computer science or related fields Strong foundation in Statistical Modeling, Machine Learning algorithms including k-means clustering, linear & logistic regression, decision trees and others Proficiency in programming languages such as Python, SQL, PySpark with experience in data manipulation, statistical analysis, and machine learning libraries (e.g., pandas, scikit-learn, TensorFlow, PyTorch) Good communication and presentation skills to effectively convey complex data insights and recommendations to clients and stakeholders Prior experience in the Insurance industry is mandatory Additional Information: - Opportunity to work on innovative projects. - Career growth and leadership exposure. About Our Company | Accenture Qualification Experience: 3-5Years Educational Qualification: Any Degree

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :These roles have many overlapping skills with GENAI Engineers and architects. Description may scaleup/scale down based on expected seniority. Roles & Responsibilities:-Implement generative AI models, identify insights that can be used to drive business decisions. Work closely with multi-functional teams to understand business problems, develop hypotheses, and test those hypotheses with data, collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.-Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services.-Optimizing existing generative AI models for improved performance, scalability, and efficiency.-Ensure data quality and accuracy-Leading the design and development of prompt engineering strategies and techniques to optimize the performance and output of our GenAI models.-Implementing cutting-edge NLP techniques and prompt engineering methodologies to enhance the capabilities and efficiency of our GenAI models.-Determining the most effective prompt generation processes and approaches to drive innovation and excellence in the field of AI technology, collaborating with AI researchers and developers-Experience working with cloud based platforms (exampleAWS, Azure or related)-Strong problem-solving and analytical skills-Proficiency in handling various data formats and sources through Omni Channel for Speech and voice applications, part of conversational AI-Prior statistical modelling experience-Demonstrable experience with deep learning algorithms and neural networks-Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.-Contributing to the establishment of best practices and standards for generative AI development within the organization. Professional & Technical Skills: -Must have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.-Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.-Must have strong knowledge of data structures, algorithms, and software engineering principles.-Must be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.-Need to have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.-Must be familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.-Need to have knowledge of software development methodologies, such as Agile or Scrum.-Possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions. Additional Information:-Must have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is highly desirable.-strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.-You possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Qualification 15 years full time education

About the Role: We are looking for a highly skilled and experienced Machine Learning / AI Engineer to join our team at Zenardy. The ideal candidate needs to have a proven track record of building, deploying, and optimizing machine learning models in real-world applications. You will be responsible for designing scalable ML systems, collaborating with cross-functional teams, and driving innovation through AI-powered solutions. Location: Chennai, Hyderabad Key Responsibilities: Design, develop, and deploy machine learning models to solve complex business problems Work across the full ML lifecycle: data collection, preprocessing, model training, evaluation, deployment, and monitoring Collaborate with data engineers, product managers, and software engineers to integrate ML models into production systems Conduct research and stay up-to-date with the latest ML/AI advancements, applying them where appropriate Optimize models for performance, scalability, and robustness Document methodologies, experiments, and findings clearly for both technical and non-technical audiences Mentor junior ML engineers or data scientists as needed Required Qualifications: Bachelors or Masters degree in Computer Science, Machine Learning, Data Science, or related field (Ph.D. is a plus) Minimum of 5 hands-on ML/AI projects, preferably in production or with real-world datasets Proficiency in Python and ML libraries/frameworks like TensorFlow, PyTorch, Scikit-learn, XGBoost Solid understanding of core ML concepts: supervised/unsupervised learning, neural networks, NLP, computer vision, etc. Experience with model deployment using APIs, containers (Docker), cloud platforms (AWS/GCP/Azure) Strong data manipulation and analysis skills using Pandas, NumPy, and SQL Knowledge of software engineering best practices: version control (Git), CI/CD, unit testing Preferred Skills: Experience with MLOps tools (MLflow, Kubeflow, SageMaker, etc.) Familiarity with big data technologies like Spark, Hadoop, or distributed training frameworks Experience working in Fintech environments would be a plus Strong problem-solving mindset with excellent communication skills Experience in working with vector database. Understanding of RAG vs Fine-tuning vs Prompt Engineering Why Join Us: Work on impactful, real-world AI challenges Collaborate with a passionate and innovative team Opportunities for career advancement and learning Flexible work environment (remote/hybrid options) Competitive compensation and benefits

Project Role : Application Lead Project Role Description : Lead the effort to design, build and configure applications, acting as the primary point of contact. Must have skills : Edge Computing Good to have skills : Kubernetes, Microsoft Azure IaaSMinimum 12 year(s) of experience is required Educational Qualification : BE/BTECH/MCA Project Role :Application Lead Project Role Description :Lead the effort to design, build and configure applications, acting as the primary point of contact. Must have Skills :Edge Computing, SSINON SSI:Good to Have Skills :SSI:Kubernetes, Microsoft Azure Architecture, Microsoft Azure IaaS NON SSI :Job :Key Responsibilities :Python or Go Embedded Linux C/C Application Containerization using Docker or Moby Machine learning, Deep learning and Artificial Intelligence on the Edge Computing HW Devices Experience in designing and developing end to end Edge Compute Solution Design and Development of distributed Edge Computing Solutions and services Leading the development activities and guiding the team on technical front in designing MEC based or pure on-premise HCI based Edge computing SolutionsReview of code and Technical Experience :Experience designing Kubertnetes Clusters for EDGE COMPUTINGEdge Model Management and MonitoringExperience working on Nvidia Jetson or Intel Movidius Neural Compute Stick or Google Coral DevicesExperience in scalable inference services using OVMS, Triton ,DeepStreamExperience in designing and developing end to end Edge Compute Solution either using AWS IoT Green Grass or Azure IoT Gateway Solutions C or Java using OpenJDK on Embedded Linux or Yocto or ROS Experience in TensorFlow,PyTorch,O Professional Attributes :Must have good communications skills and ability to manage the team membersMust be able to produce clear and concise documentation including requirements documents, design specs, status reports, system documentation and emailsMust have proven track record of technical leadership roles delivering s Educational Qualification:BE/BTECH/MCAAdditional Info :Connected Device Streaming data analytics Experience in Azure Stack Edge or AWS Snowball Edge Qualification BE/BTECH/MCA

Project Role : Security Architect Project Role Description : Define the cloud security framework and architecture, ensuring it meets the business requirements and performance goals. Document the implementation of the cloud security controls and transition to cloud security-managed operations. Must have skills : Product Security Good to have skills : NAMinimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :AI Red Teaming Expert Adversarial ML, Threat Simulation, and AI Security StrategyWe are seeking a highly experienced and visionary AI Red Teaming Expert 12+ years of experience across cybersecurity and machine learning. This role is ideal for professionals who thrive in dynamic environments and possess a passion for securing cutting-edge AI/ML systems. You will lead red teaming operations, simulate adversarial threats, and guide the organizations AI security posture at strategic and technical levels. The ideal candidate demonstrates deep technical expertise, exceptional leadership, and a keen understanding of adversarial machine learning and risk mitigation frameworks. Roles & Responsibilities:Define and execute the AI red teaming strategy across the organization.Simulate realistic and advanced adversarial attacks against AI/ML systems aligned with business contexts.Review AI/ML system architecture to identify security gaps and advocate for secure design patterns.Establish internal standards and workflows for AI threat modeling, risk assessment, and adversarial testing.Stay ahead of evolving adversarial ML threats and guide the development of defensive strategies.Contribute to secure development practices for model deployment pipelines and lifecycle management.Lead and mentor a specialized team of AI security analysts and red teamers.Represent AI security strategy in executive forums and drive cross-functional alignment.Collaborate with engineering, data science, compliance, and legal stakeholders to integrate security into AI innovation cycles.Drive internal policy-making efforts around responsible and secure AI development practices.Own and lead remediation initiatives, translating findings into actionable improvements across teams. Professional & Technical Skills: Exceptional communication and leadership skills with the ability to convey technical issues to non-technical stakeholders.Proven experience managing high-impact security initiatives and leading diverse teams.Strategic thinker capable of aligning AI security objectives with business goals.Passionate about AI safety, responsible innovation, and emerging threat landscapes.Strong analytical and problem-solving skills in high-pressure environments.Hands-on expertise in red teaming AI/ML systems at scale.Strong understanding of adversarial ML techniques, threat simulation tools, and AI model manipulation tactics.Experience implementing and aligning with frameworks such as OWASP Top 10 for LLMs, ISO 42001, NIST AI RMF.Proficiency in AI/ML pipeline security, model risk evaluation, and secure MLOps practices.Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch) and their associated vulnerabilities.Demonstrated ability to design, execute, and scale red teaming programs in AI-native environments.- Additional Information:Bachelors or Masters degree in Computer Science, Information Security, Machine Learning, or related field.Recognized certifications such as CEH, OSCP, CISSP, or credentials specific to AI security (e.g., MITRE ATLAS experience) are a plus.- 12+ years of experience spanning cybersecurity, AI/ML, and adversarial testing- This position is based at our Bengaluru office- A 15 years full time education is required. Qualification 15 years full time education

Management Level :07 - Manager Location :Gurgaon/Bangalore/Mumbai Must have skills :Python Programming, Machine Learning, Generative AI (GPT, DALLE, GANs), Model Deployment, Cloud (AWS/Azure/GCP), Statistical Analysis, Data Science, API Development, Docker/Kubernetes Good to have skills :PyTorch, TensorFlow, NLP, Computer Vision, Performance Optimization, Ethical AI Practices, Cloud Integrations, Open-Source Contributions Job Summary : Accenture AI is seeking a talented and motivated Generative AI Data Scientist Lead to join our Banking team. The ideal candidate will leverage their expertise in Generative AI models, Machine Learning, Data Analysis and Cloud Platforms to drive and lead the development & delivery of the innovative solutions and enhance our AI capabilities. This role will involve collaborating with cross-functional teams to design, develop, and implement generative AI solutions that meet our business needs. Roles & Responsibilities: Independent Project Leadership :Take ownership of end-to-end project delivery, from problem definition to solution deployment, with minimal supervision. Pod Leadership :Lead and mentor a small development pod (team) of data scientists and engineers, ensuring collaboration, innovation, and timely delivery of high-quality solutions. Model Development :Design, develop, and deploy state-of-the-art generative AI models (e.g., GPT, DALLE, Stable Diffusion, GANs) for applications such as text generation, image synthesis, content creation, and more. Strategy Development :Provide strategic recommendations to clients on how to integrate generative AI into their workflows and business processes. Ethical AI Practices :Ensure responsible use of generative AI by addressing biases, ethical concerns, and compliance with regulations. Performance Evaluation :Develop evaluation metrics and methodologies to assess the performance of generative models and ensure they meet quality standards. Collaboration :Work closely with product managers, engineers, and other stakeholders to understand requirements and deliver impactful AI solutions. Research and Innovation :Stay up-to-date with the latest advancements in generative AI and machine learning, applying that knowledge to improve existing models and techniques. Mentorship :Guide and mentor junior team members, fostering a culture of innovation and continuous learning. Professional & Technical Skills: 6+ years of experience in Data Science , Machine Learning , or related fields with a focus on Generative AI models (LLMs) . Expert proficiency in Python programming and experience with machine learning frameworks (e.g., TensorFlow , PyTorch ). Hands-on experience with cloud platforms (AWS, GCP, Azure), including deployment and solution building . Ability to work with Docker , Kubernetes , and API Development to deploy generative AI models. Strong analytical, problem-solving , and critical thinking skills. Expertise in ethical AI practices and understanding of the biases and regulations surrounding Generative AI . Excellent verbal and written communication skills, with the ability to clearly convey complex concepts to diverse audiences. Additional Information: Experience with large-scale data processing and cloud computing platforms. Familiarity with NLP , computer vision , and other AI applications. Publications or contributions to open-source AI/ML projects . Experience in cloud integrations and performance optimization . Strong leadership skills with experience in guiding teams and managing AI projects. About Our Company | AccentureQualification Experience :Minimum 6+ years of experience in Data Science, Machine Learning, or a related field with a focus on Generative AI models (LLMs) and leadership in AI solutions. Educational Qualification :Masters or Ph.D. in Computer Science , Data Science , Statistics , or related field.