147 Cnn Jobs - Page 6

Job Responsibilities 1. Understand and Participate in Establishing Requirements Gain a deep understanding of system-level requirements impacting firmware deliverables. Actively participate in the creation of firmware requirements based on system specifications. Collaborate with the broader team to define and improve system-level requirements for hearing aid firmware. Align firmware design with requirements through continuous exploration of the firmware system, review of documentation, and consultations with senior team members. 2. Design and Implement High-Quality Firmware Create designs that meet firmware requirements. At this level, the engineer is expected to solve moderate technical challenges. Senior engineers review solutions for technical sound. Document and review designs, ensuring they provide value and enhance understanding of the firmware. Apply programming knowledge (e.g., C, assembly) to implement firmware on resource-constrained hardware. Follow best practices in firmware development processes such as code reviews, design documentation, and adherence to coding conventions. Update the status of assigned tasks using established issue and project tracking software. Use version control systems to manage code effectively. Investigate, root cause, and resolve firmware issues promptly, providing feedback on potential solutions and their impact to the firmware management team. 3. Verify Firmware Functionality Support the Firmware Verification Team in developing test plans and executing tests to ensure firmware meets high-quality standards at the system level. Review test plans and provide constructive feedback. Conduct unit tests to verify the functionality of developed firmware before passing it to the verification team. Collaborate with Firmware Verification Engineers and others in R&D to identify and resolve issues. 4. Participate Effectively in Project Activities Understand and follow established organizational processes such as Advanced Development and Product Development processes. Work with the Firmware Project Sponsor/Manager to create project plans and provide work estimates for project milestones. Take proactive ownership of project assignments and follow the project management process (Scrum) for assigned projects. Communicate changes to work effort estimates and their potential impact on the project schedule. Provide updates on project activities during sprint reviews, stand-up meetings, and one-on-one meetings. Job Requirements Education and Experience: Education: Bachelors or Masters degree in Electronics and Communication, Computer Science, Embedded Technology, or a related field. Experience: 4-8 years of relevant experience with a BS degree 0-4 years of relevant experience with an MS degree Knowledge and Technical Requirements In-depth knowledge in one or more of the following domains is required: Digital Signal Processing (DSP) Real-time Signal Processing: Knowledge of hardware or embedded systems for real-time signal processing, including the use of microcontrollers, DSP chips, and FPGA. Filtering: Designing and implementing digital filters (FIR, IIR) to remove noise, smooth, or enhance signals. Knowledge of filter design tools and techniques (e.g., Butterworth, Chebyshev filters). Convolution & Correlation: Understanding how to apply these operations to signals to filter or detect patterns. Fourier Analysis: Applying Fourier transforms (FFT, DFT) to analyze signals in the frequency domain, including spectral analysis and signal reconstruction. Time-Frequency Analysis: Familiarity with techniques like Short-Time Fourier Transform (STFT) or wavelet transforms for analyzing non-stationary signals. Adaptive Filtering: Understanding algorithms that adapt their characteristics based on the signal's input, such as LMS (Least Mean Squares) and RLS (Recursive Least Squares). Signal Compression & Coding: Knowledge of data compression techniques (e.g., JPEG, MP3) for efficient transmission and storage of signals. Embedded DSP Experience in implementing DSP algorithms on embedded systems, such as using ARM, TI processors or specialized DSP hardware. Real-Time Operating Systems (RTOS): Experience with real-time operating systems, such as FreeRTOS, VxWorks, or other embedded OS, for scheduling and task management. Hardware/Software Interface: Experience interfacing with hardware components (ADC, DAC, sensors, actuators, etc.). MATLAB/Simulink: Ability to model and simulate DSP algorithms using tools like MATLAB and Simulink. Embedded Development Tools: Familiarity with IDEs (e.g., Eclipse, Keil, IAR Embedded Workbench) and debugging tools (JTAG, oscilloscopes, logic analyzers). Machine Learning (ML) & AI Integration DSP and Machine Learning: Integrating machine learning with DSP to enhance signal processing tasks such as classification, pattern recognition, and feature extraction. Deep Learning for DSP: Familiarity with neural networks, CNNs (Convolutional Neural Networks), RNNs (Recurrent Neural Networks), GANs (Generative Adversarial Networks), and other deep learning architectures. Proficiency in using TensorFlow, PyTorch, and Keras Wireless and wired communication protocols. Firmware testing methodologies and tools Proficiency in programming languages such as C or assembly. Familiarity with scripting languages like MATLAB or Python. Understanding of analog and digital circuitry. Competencies, Skills, and Abilities Strong verbal and written communication skills. Driven, methodical, and detail oriented. Ability to work both independently and as part of a team. Proficiency in problem-solving.

About the Role: We are based in Gurgaon and looking for a Senior Computer Vision Engineer to join our team and help our team to improve and create new technologies. You'll work on projects which makes online assessment more secure and cheating proof. If you're a seasoned computer vision expert with a passion for innovation and a track record of delivering impactful solutions, we would be happy to meet you. Role : Senior Computer Vision Engineer Functional Area : AI Educational Qualification: BTech/MS/MTech/PhD in Computer Science/Computer vision/Signal Processing/Deep Learning or equivalent. Should have worked in an academic or professional setting in the field of computer vision/signal processing. Experience: 2-5 years Location : Gurgaon Key Responsibilities: Develop and optimize advanced computer vision algorithms for image and video analysis tasks. Design, implement and train deep learning models for object detection, face processing, activity recognition and other related tasks. Test and refine models and systems based on real-world data and feedback. Evaluate project requirements, plan and manage the roadmap of a project. Present findings and insights in a clear and concise manner to stakeholders. Collaborate and help to integrate and deploy computer vision systems into broader product architecture. Conduct research to stay updated on emerging computer vision technologies and trends. Automate data preprocessing and annotation processes to streamline workflow efficiency. Maintain comprehensive documentation for algorithms, implementations, and evaluations. Mentor junior engineers and provide strategic guidance on project development. Requirements and skills: Proficiency in Python and knowledge of C++, Java and JS is plus. Solid understanding of neural networks, especially convolutional neural networks (CNNs). Knowledge of RCNNs and vision transformers. Proficient in understanding, designing and implementing deep learning models using frameworks such as TensorFlow, PyTorch and Keras. Understanding of fundamental image processing techniques like image filtering, edge detection, image segmentation and image augmentation. Experience in evaluating computer vision models using relevant metrics and performance indicators. Familiarity with GPU and related technologies which is utilized for improved computational efficiency such as CUDA, CUDNN, tensorRT etc. Familiarity with Python libraries such as OpenCV, NumPy, Pandas and scikit-learn etc. Basic knowledge of linear algebra, calculus, and statistics. Strong critical thinking, analytical, and problem-solving skills Self-motivated, quick learner and strong team player with ability to work with minimal supervision.

Job Title: Machine Learning Engineer Location: Jaipur Job Type: Full-Time About the Role We are looking for a Machine Learning Engineer with expertise in YOLO, custom ML models, and deep learning to join our team. If you have 4+ years of experience in developing and deploying computer vision solutions, this is an exciting opportunity to work on cutting-edge AI applications. Key Responsibilities Develop, train, fine-tune, and optimize YOLO-based object detection models (YOLOv5, YOLOv8, etc.). Design and implement custom ML models tailored to specific business needs. Handle large-scale datasets, including data collection, preprocessing, and augmentation. Deploy ML models in cloud environments (AWS, GCP, Azure) and edge computing platforms (Jetson Nano, Raspberry Pi, Coral TPU, etc.). Optimize ML models using techniques such as quantization, pruning, and model compression. Evaluate and improve model performance using mAP (mean Average Precision), IoU (Intersection over Union), precision-recall, and F1-score. Work closely with data scientists, software engineers, and DevOps teams to integrate models into production systems. Stay updated with the latest advancements in deep learning, computer vision, and AI model optimization. Required Skills & Qualifications Minimum 4+ years of experience in Machine Learning, Deep Learning, and Computer Vision. Strong expertise in YOLO-based object detection models (YOLOv5, YOLOv7, YOLOv8, etc.). Proficiency in Python, TensorFlow, PyTorch, and Keras. Experience with OpenCV, FastAPI, Flask for computer vision applications and API deployment. Knowledge of ONNX, TensorRT for model deployment and optimization. Familiarity with Docker, Kubernetes, MLflow, Kubeflow, and Airflow for MLOps and model lifecycle management. Experience working with cloud-based ML services (AWS SageMaker, Google Vertex AI, Azure ML). Strong understanding of CNNs, RNNs, Transformers, and other deep learning architectures. Hands-on experience in dataset annotation, synthetic data generation, and image preprocessing. Preferred Qualifications Experience in real-time AI applications, robotics, smart surveillance, or autonomous systems. Knowledge of Edge AI deployment on NVIDIA Jetson, Coral TPU, or Raspberry Pi. Experience with generative AI models, self-supervised learning, and synthetic data creation. Prior work in video analytics, smart security systems, healthcare AI, or industrial automation.

About The Role : Client PnP Solutions Architect will develop and enhance a robust PnP AI/ML framework deployed across Intel Client platforms to achieve or surpass platform quality and PnP targets. Insights gained from these deployments and analytics will feed back into future client products and beyond by ensuring continuous improvement. Client PnP Solutions Architect will work on PnP KPIs/KEIs projections on customer configurations by considering dynamic factors like OS upgrades, third-party OEM components, and drivers by deploying insights from PnP AI/ML framework. Qualifications Minimum Qualifications Bachelor degree with 12+ years or Master degree with 10+ years in any of the following field:Computer Science or Data Science and Engineering, Electronics or Electrical Engineering, Applied mathematics, or related technical disciplines. Skills: Strong programming skills in Python, with the capability to debug complex asynchronous systems. Hands-on experience in database design, deployment, and maintenance with programming using dot NET,.NET, LINQ, SQL Server, Web API 2.0, Net Core, JavaScript, C, C++, and Angular. Hand-on experience in creating, and deploying automation scripts using Python, C hash, and batch scripting to streamline workflows and enhance functionality. Experience in windows batch scripting, PowerShell scripting, Python and Windows automation. Working knowledge on development and maintenance of automation solutions for Adobe software, AI applications, 3D gaming platforms, browsers, and Microsoft Teams on Windows OS. Expertise in computer architecture and x86 architecture, working experience in platform, post-silicon and PnP validation. Sound knowledge and experience in various domains such as CPU, AI, Graphics, Gaming and Camera. Machine Learning Expertise: In-depth knowledge of machine learning techniques, including regression, classification, LDA, Naive Bayes, Logistic Regression, and SVM. Deep Learning and Generative AI : Solid understanding of ML/DL techniques, algorithms, and tools. Experience with CNN, RNN (LSTM), and Transformers (BERT, BART, GPT/T5, Megatron, LLMs). Knowledge of various prompt techniques, including zero-shot, few-shot,Experience with database and tools such as SQL, MongoDB, Graph DB, and Elastic Search in native AI applications. ML Ops: Proven experience in deploying and maintaining high-scale AI-based systems.Understanding of scalable deployment of multiple microservices involving LLM-driven RAG and Agent applications in a production environment.Familiarity with Docker, Helm, Kubernetes, etc.Experience with the end-to-end software lifecycle, release packaging, and CI/CD pipeline. Preferred Skills: Good understanding of Computer Architecture and x86 architecture. Experienced in Platform Software Development and Validation. Behavioral traits: Excellent written and oral communication skills.Be able to clearly communicate technical details and concept. Inside this Business Group The Client Computing Group (CCG) is responsible for driving business strategy and product development for Intel's PC products and platforms, spanning form factors such as notebooks, desktops, 2 in 1s, all in ones. Working with our partners across the industry, we intend to deliver purposeful computing experiences that unlock people's potential - allowing each person use our products to focus, create and connect in ways that matter most to them. As the largest business unit at Intel, CCG is investing more heavily in the PC, ramping its capabilities even more aggressively, and designing the PC experience even more deliberately, including delivering a predictable cadence of leadership products. As a result, we are able to fuel innovation across Intel, providing an important source of IP and scale, as well as help the company deliver on its purpose of enriching the lives of every person on earth.

About The Role : AI/ML technologist will focus on leveraging advanced capabilities in Deep Learning, Generative AI, and Agentic AI to revolutionize traditional manual validation and debug processes, transforming them into fully automated, intelligent systems which aim to reduce human intervention, enhance accuracy, and scale validation workflows to meet increasing demands.AI/ML Technologist will work with internal validation teams and Intel Labs deliver AI based modernization of system integration and validation solutions for client products execution. Researches technical trends and utilizes deep domain and expertise to prototype solutions and develop AI software including open-source libraries and models. Optimizes performance of AI models through deep knowledge and expertise of AI frameworks, algorithms, models, and related hardware. AI/ML Technologist will lead development of self-reasoning systems for improved test case generation, enhancing fault resolution quality, creating AI-assisted debugging solutions for both internal and customer issues, and building automated recommendation systems. Analyzing and elevating the overall customer experience will be crucial for long-term success. By integrating AI, the organization will deliver higher quality products and solutions. Qualifications Minimum Qualifications Bachelor degree with 12+ years or Master degree with 10+ years in any of the following field:Computer Science or Data Science and Engineering, Electronics or Electrical Engineering, Applied mathematics, or related technical disciplines. Skills: Strong programming skills in Python, with the capability to debug complex asynchronous systems. Machine Learning Expertise: In-depth knowledge of machine learning techniques, including regression, classification, LDA, Naive Bayes, Logistic Regression, and SVM. Deep Learning and Generative AI: Solid understanding of ML/DL techniques, algorithms, and tools. Experience with CNN, RNN (LSTM), and Transformers ( BERT, BART, GPT/T5, Megatron, LLMs). Practical experience with Retrieval-Augmented Generation (RAG) and LLM-based applications. Familiarity with LLM function calling, Information Retrieval, Vector Databases, Embedding, and Re rank models. Hands-on experience with large language model (LLM) agentic pipelines. Knowledge of various prompt techniques, including zero-shot, few-shot, Chain-of-Thought, Tree-of-Thought, and React. Database and Tools: Experience with database and tools such as SQL, MongoDB, Graph DB, and Elastic Search in native AI applications. ML Ops: Proven experience in deploying and maintaining high-scale AI-based systems. Understanding of scalable deployment of multiple microservices involving LLM-driven RAG and Agent applications in a production environment. Familiarity with Docker, Helm, Kubernetes, etc. Experience with the end-to-end software lifecycle, release packaging, and CI/CD pipeline. Preferred Skills: Good understanding of Computer Architecture and x86 architecture. Experienced in Platform Software Development and Validation. Behavioral traits: Excellent written and oral communication skills.Be able to clearly communicate technical details and concept. Inside this Business Group The Client Computing Group (CCG) is responsible for driving business strategy and product development for Intel's PC products and platforms, spanning form factors such as notebooks, desktops, 2 in 1s, all in ones. Working with our partners across the industry, we intend to deliver purposeful computing experiences that unlock people's potential - allowing each person use our products to focus, create and connect in ways that matter most to them. As the largest business unit at Intel, CCG is investing more heavily in the PC, ramping its capabilities even more aggressively, and designing the PC experience even more deliberately, including delivering a predictable cadence of leadership products. As a result, we are able to fuel innovation across Intel, providing an important source of IP and scale, as well as help the company deliver on its purpose of enriching the lives of every person on earth.

Job Title: Industry & Function AI Decision Science Consultant S&C Global Network Management Level: 9 Consultant Location: Primary - Bengaluru, Secondary - Gurugram Must-Have Skills: Data Science, AI, ML, Experience with cloud platforms such as AWS, Azure, or Google Cloud, Hands-on experience in programming languages like Python, R, PySpark, and SQL Good-to-Have Skills: Deep Learning Techniques (e.g. RNN, CNN), Visualization tools like Power BI and Tableau, Exposure to tools like ChatGPT, Llama 2, Hugging Face, etc. Job Summary : As an Industry & Function AI Decision Science Consultant, you will leverage your expertise in data science and Consumer Goods domain knowledge to design and deliver AI-driven solutions. Your role will include strategic analysis, project delivery, solution development, and technical execution to empower businesses with actionable insights and enable automated and augmented decision-making. Roles & Responsibilities: Conduct strategic analysis of the AI, analytics, and data maturity landscape for clients in the Consumer Goods domain Lead data science engagements, manage delivery teams, and build innovative AI capabilities Develop and implement advanced analytics solutions tailored to client requirements Utilize languages like Python, PySpark, R, and SQL for data wrangling and machine learning model development Leverage cloud technologies (Azure, AWS, GCP) to integrate and implement AI solutions Translate complex data into compelling narratives for effective data storytelling Mentor junior team members and contribute to thought leadership Professional & Technical Skills: Proficiency in Python, R, PySpark, and SQL Strong knowledge of traditional statistical methods, machine learning techniques, and deep learning Hands-on experience in Consumer Goods & Services domain Cloud integration skills with platforms like AWS, Azure, or Google Cloud Experience with optimization techniques (exact and evolutionary) Certifications like AWS Certified Data Analytics Specialty or Google Professional Data Engineer Familiarity with visualization tools like Tableau and Power BI Exposure to large language models (e.g., ChatGPT, Llama 2) Familiarity with version control systems like Git. Additional Information: The ideal candidate will have a strong educational background in data science, computer science, or a related field, along with a proven track record of delivering impactful AI-driven solutions in the Consumer Goods industry. About Our Company | Qualifications Experience: Minimum 4-8 years of hands-on experience in data science with a focus on the Consumer Goods industry Educational Qualification: Bachelors or Masters degree in Statistics, Economics, Mathematics, Computer Science, or equivalent degree with Data Science specialization (from a premier institute)

Job Description Developing a software pipeline for end-to-end ML Model Inference for specific hardware accelerator by achieving maximum performance & accuracy. Implementing cutting edge deep learning layers for various model categories like CNN, RNN, LSTM, GANs, etc using customized inference pipeline for NN Processor. Hardware architecture aware and computation conscious implementation of solutions in an embedded device and maximize the throughput. Develop tools and applications by producing clean, efficient code. Identify, prioritize and execute tasks based on requirement. Implementation, Review, Debug code, Product Delivery and quick turn arounds. Collaborate with team to brainstorm and create new products. Mentor fresh joiners and foster team culture. Must-Have BE/BTech/MS/MTech graduates with Computer science Engineering with 5+ yrs of experience. Solid programming experience in C/C++ with proven experience as Senior Software Engineer. Experience in implementing kernel intrinsics for Machine Learning or Computer Vision algorithms with a focus on optimization. Extensive experience in software development and project management. Strong analytical and problem-solving skills. Adaptable to execute complex tasks, under tight schedules and dynamic conditions. Familiarity with various operating systems (Linux, Mac OS, Windows). Ability to work independently and manage a team. Excellent organizational and leadership skills. Working knowledge on Deep Learning frameworks (Like ONNX, TensorFlow, PyTorch or Any Hardware Accelerator Software Pipeline Experience). Nice-to-Have Knowledge in Python. Experience in managing team size of 5 or more. Experience Working in an Agile Environment. Experience in using automated testing frameworks.

Responsibilities: Customer & Architecture Interact with customers to define problem statements and technical requirements Design and architect AI/ML cloud solutions using AWS/GCP Create system architecture diagrams and establish best practices for ML systems Define data architecture and model serving strategies Technical Leadership & Development Guide team in building Python-based APIs and AI/ML models Design and implement ML pipeline automation Establish model deployment and monitoring architectures Review technical designs and approve implementation approaches Lead architectural decision-making and technical direction Project & Team Management Overall responsibility for project/program delivery Manage and mentor AI/ML engineers Lead sprint planning and technical grooming sessions Coordinate with cross-functional teams Balance resource allocation and technical debt Qualifications Must have at least 10 years of IT experience with 5+ years experience in designing, developing, deploying, and operationalizing AI/ML solutions. Experience in GenAI and Conversational AI LLMs, frameworks like Lang chain, Llama Index etc, Vector DBs like Pinecone, Elasticsearch, etc. Deep understanding and experience with popular Deep Learning and Machine Learning techniques and algorithms such as LLMs, Neural Networks, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), LSTM, Transformers, Time Series Forecasting, Segmentation, etc. Experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps/LLMOps, Optimization techniques, and AI solution Architecture. Experience with ML Pipelines both On-Prem and Cloud (like SageMaker) Expert in Python as well as open-source frameworks such as PyTorch, TensorFlow, NumPy, etc. Experience in designing cloud-native solutions using AI and other services from Azure, GCP, AWS, etc. Ability to lead Data Engineers and ML engineers to provide guidance on technical architecture and best practices.

Job Title: Industry & Function AI Decision Science Consultant- S&C Global Network Management Level: 9- Consultant Location: Primary - Bengaluru, Secondary - Gurugram Must-Have Skills: Data Science, AI, ML, Experience with cloud platforms such as AWS, Azure, or Google Cloud, Hands-on experience in programming languages like Python, R, PySpark, and SQL Good-to-Have Skills: Deep Learning Techniques (e.g. RNN, CNN), Visualization tools like Power BI and Tableau, Exposure to tools like ChatGPT, Llama 2, Hugging Face, etc. Job Summary : As an Industry & Function AI Decision Science Consultant, you will leverage your expertise in data science and Consumer Goods domain knowledge to design and deliver AI-driven solutions. Your role will include strategic analysis, project delivery, solution development, and technical execution to empower businesses with actionable insights and enable automated and augmented decision-making. Roles & Responsibilities: Conduct strategic analysis of the AI, analytics, and data maturity landscape for clients in the Consumer Goods domain Lead data science engagements, manage delivery teams, and build innovative AI capabilities Develop and implement advanced analytics solutions tailored to client requirements Utilize languages like Python, PySpark, R, and SQL for data wrangling and machine learning model development Leverage cloud technologies (Azure, AWS, GCP) to integrate and implement AI solutions Translate complex data into compelling narratives for effective data storytelling Mentor junior team members and contribute to thought leadership Professional & Technical Skills: Proficiency in Python, R, PySpark, and SQL Strong knowledge of traditional statistical methods, machine learning techniques, and deep learning Hands-on experience in Consumer Goods & Services domain Cloud integration skills with platforms like AWS, Azure, or Google Cloud Experience with optimization techniques (exact and evolutionary) Certifications like AWS Certified Data Analytics Specialty or Google Professional Data Engineer Familiarity with visualization tools like Tableau and Power BI Exposure to large language models (e.g., ChatGPT, Llama 2) Familiarity with version control systems like Git. Additional Information: The ideal candidate will have a strong educational background in data science, computer science, or a related field, along with a proven track record of delivering impactful AI-driven solutions in the Consumer Goods industry. About Our Company | Qualifications Experience: Minimum 4-8 years of hands-on experience in data science with a focus on the Consumer Goods industry Educational Qualification: Bachelors or Masters degree in Statistics, Economics, Mathematics, Computer Science, or equivalent degree with Data Science specialization (from a premier institute)

Job Title: Industry & Function AI Decision Science Consultant- S&C Global Network Management Level: 9- Consultant Location: Primary - Bengaluru, Secondary - Gurugram Must-Have Skills: Data Science, AI, ML, Experience with cloud platforms such as AWS, Azure, or Google Cloud, Hands-on experience in programming languages like Python, R, PySpark, and SQL Good-to-Have Skills: Deep Learning Techniques (e.g. RNN, CNN), Visualization tools like Power BI and Tableau, Exposure to tools like ChatGPT, Llama 2, Hugging Face, etc. Job Summary : As an Industry & Function AI Decision Science Consultant, you will leverage your expertise in data science and Consumer Goods domain knowledge to design and deliver AI-driven solutions. Your role will include strategic analysis, project delivery, solution development, and technical execution to empower businesses with actionable insights and enable automated and augmented decision-making. Roles & Responsibilities: Conduct strategic analysis of the AI, analytics, and data maturity landscape for clients in the Consumer Goods domain Lead data science engagements, manage delivery teams, and build innovative AI capabilities Develop and implement advanced analytics solutions tailored to client requirements Utilize languages like Python, PySpark, R, and SQL for data wrangling and machine learning model development Leverage cloud technologies (Azure, AWS, GCP) to integrate and implement AI solutions Translate complex data into compelling narratives for effective data storytelling Mentor junior team members and contribute to thought leadership Professional & Technical Skills: Proficiency in Python, R, PySpark, and SQL Strong knowledge of traditional statistical methods, machine learning techniques, and deep learning Hands-on experience in Consumer Goods & Services domain Cloud integration skills with platforms like AWS, Azure, or Google Cloud Experience with optimization techniques (exact and evolutionary) Certifications like AWS Certified Data Analytics Specialty or Google Professional Data Engineer Familiarity with visualization tools like Tableau and Power BI Exposure to large language models (e.g., ChatGPT, Llama 2) Familiarity with version control systems like Git. Additional Information: The ideal candidate will have a strong educational background in data science, computer science, or a related field, along with a proven track record of delivering impactful AI-driven solutions in the Consumer Goods industry. About Our Company | Qualifications Experience: Minimum 4-8 years of hands-on experience in data science with a focus on the Consumer Goods industry Educational Qualification: Bachelors or Masters degree in Statistics, Economics, Mathematics, Computer Science, or equivalent degree with Data Science specialization (from a premier institute)

Entity :- Accenture Strategy & Consulting Team :- Global Network - Data & AI Practice :- Comms & Media - Telecom Title :- Level 9 – Ind & Func AI Decision Science Consultant Job location :- Bangalore/Gurgaon/Hyderabad/Mumbai About Global Network – Data & AI :- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition About Comms & Media practice: Comms & Media (C&M) is one of the Industry Practices within Accenture's S&C Global Network team. It focuses in serving clients across specific Industries – Communications, Media & Entertainment. Communications – Focuses primarily on industries related with telecommunications and information & communication technology (ICT). This team serves most of the world's leading wireline, wireless, cable and satellite communications and service providers Media & Entertainment – Focuses on industries like broadcast, entertainment, print and publishing Globally, Accenture Comms & Media practice works to develop value growth strategies for its clients and infuse AI & GenAI to help deliver top their business imperatives i.e., revenue growth & cost reduction. From multi-year Data & AI transformation projects to shorter more agile engagements, we have a rapidly expanding portfolio of hyper-growth clients and an increasing footprint with next-gen solutions and industry practices. Responsibilities/Authorities A Telco domain experienced and data science consultant is responsible to help the clients with designing & delivering AI solutions. He/she should be strong in Telco domain, AI fundamentals and should have good hands-on experience working with the following: Ability to work with large data sets and present conclusions to key stakeholders; Data management using SQL. Propose solutions to the client based on gap analysis for the existing Telco platforms that can generate long term & sustainable value to the client. Gather business requirements from client stakeholders via interactions like interviews and workshops with all stakeholders – Track down and read all previous information on the problem or issue in question. Explore obvious and known avenues thoroughly. Ask a series of probing questions to get to the root of a problem. Ability to understand the as-is process; understand issues with the processes which can be resolved either through Data & AI or process solutions and design detail level to-be state Understand customer needs and identify/translate them to business requirements (business requirement definition), business process flows and functional requirements – and be able to inform the best approach to the problem. Adopt a clear and systematic approach to complex issues (i.e. A leads to B leads to C). Analyze relationships between several parts of a problem or situation. Anticipate obstacles and identify a critical path for a project. Independently able to deliver products and services that empower clients to implement effective solutions. Makes specific changes and improvements to processes or own work to achieve more. Work with other team members and make deliberate efforts to keep others up to date. Establish a consistent and collaborative presence with clients and act as the primary point of contact for assigned clients; escalate, track, and solve client issues. Partner with clients to understand end clients' business goals, marketing objectives, and competitive constraints. Storytelling – Crunch the data & numbers to craft a story to be presented to senior client stakeholders. Qualifications JOB REQUIREMENTS – Overall Experience Overall 5+ years of experience in Data Science & at least 2 years in Telecom Analytics Masters (MBA/MSc/MTech) from a Tier 1/Tier 2 and Engineering from Tier 1 school Demonstrated experience in solving real-world data problems through Data & AI Direct onsite experience (i.e., experience of facing client inside client offices in India or abroad) is mandatory. Please note we are looking for client facing roles. Proficiency with data mining, mathematics, and statistical analysis Advanced pattern recognition and predictive modeling experience; knowledge of Advanced analytical fields in text mining, Image recognition, video analytics, IoT etc. Execution level understanding of econometric/statistical modeling packages – Traditional techniques like – Linear/logistic regression, multivariate statistical analysis, time series techniques, fixed/Random effect modelling. Machine learning techniques like - Random Forest, Gradient Boosting, XG boost, decision trees, clustering etc. Knowledge of Deep learning modeling techniques – like RNN, CNN etc. Experience using digital & statistical modeling software (one or more) – Python, R, PySpark, SQL, BigQuery, Vertex AI Proficient in Excel, MS word, Power point, and corporate soft skills Knowledge of Dashboard creation platforms – Excel, tableau, Power BI etc. Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical stakeholders. Strong analytical, problem-solving skills and good communication skills Self-Starter with ability to work independently across multiple projects and set priorities Strong team player – Proactive and solution oriented, able to guide junior team members. Execution knowledge of optimization techniques is a good-to-have – Exact optimization – Linear, Non-linear optimization techniques Evolutionary optimization – Both population and search-based algorithms Cloud platform Certification, experience in Computer Vision are good-to-haves Accenture has not authorized any agency, company or individual to either collect money or arrive on any monetary arrangement in exchange for a job at Accenture. Accenture’s criterion for hiring candidates is merit. Any agency, company or individual offering employment with Accenture in exchange for money is misrepresenting their relationship with Accenture, which has not authorized any such action. If you are approached by any entity or individuals who demand money or any other form of compensation in return for a job offer at Accenture – even if they present themselves as representatives or employees of Accenture – please send the details to Accenture Business Ethics Line

Job Description: AI Engineering Manager Position Overview: We are seeking an experienced AI Engineering Manager to lead our AI projects and drive innovation in deep learning applications. The ideal candidate will have a strong background in the latest deep learning architectures, including Convolutional Neural Networks (CNNs) and Transformers, and possess project management experience in overseeing AI initiatives. Key Responsibilities: Lead the design, development, and deployment of AI solutions, ensuring alignment with organisational goals. Manage AI projects from inception to completion, coordinating cross- functional teams and resources effectively. Oversee the implementation of deep learning algorithms for various applications, particularly in medical image analysis. Mentor and guide team members, fostering a collaborative and innovative work environment. Ensure high-quality code development in Python, C, or C++, with a strong understanding of object-oriented programming concepts. Qualifications: Proven experience in managing AI projects and teams. Strong knowledge of deep learning architectures such as CNNs and Transformers. Prior experience in the medical image analysis field is preferred. Proficiency in programming languages including Python, C, and C++. Experience in people management and team leadership. Preferred Skills: Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch). Excellent communication skills and the ability to work collaboratively across teams. Candidates with publications in conferences such as ICCV, ICPR, ICIP, ISBI, MICCAI, MIDL, NeurIPS, and CVPR are preferred.

Some of the key responsibilities include: Data mining involves extracting usable data from valuable sources. Possesses extensive knowledge of Python, including a deep understanding of machine learning libraries. Utilises machine learning tools to select features, create and optimise classifiers, and carry out preprocessing of both structured and unstructured data. Proficient with deep learning models such as ANN, CNN, and NLP. Enhances data collection procedures to encompass all relevant information for developing analytical systems. Processes, cleanses, and validates the integrity of data for analysis. Analyses large volumes of information to identify patterns and solutions. Develops prediction systems and machine learning algorithms. Proposes solutions and strategies to address business challenges. Collaborates with business and IT teams. Required Technical Skills: Programming Skills Knowledge of statistical programming languages such as R and Python, along with database query languages like SQL, is desirable. Statistics Strong applied statistical skills, encompassing knowledge of statistical tests, distributions, regression, and maximum likelihood estimators, are essential for data-driven companies. Machine Learning A good understanding of machine learning methods is required. Strong Math Skills (Multivariable Calculus and Linear Algebra) - Understanding the fundamentals of Multivariable Calculus and Linear Algebra is crucial, as they form the basis of many predictive performance and algorithm optimization techniques. Data Wrangling Proficiency in managing data imperfections is a key aspect of a data scientist's job description. Experience with Data Visualisation Tools such as Matplotlib, which assist in visually encoding data. Required Skills: Good with ML, Computer Vision & DL concepts Strong experience in creating data pipelines Proficiency in database management Hands-on expertise in model retraining and deployment Proficiency in Python coding Cloud AWS/Azure Looking for 6+Yrs of experience. Looking for Immediate to 30 Days of Notice Period (Also Serving NP Professionals)

About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: Senior AIML Engineer Experience : 6+ Yrs Location: Pune Skillsets- AIML , Gen AI, MLOps, AWS, Python, ML(Machine Learning), Data Science , SQL,AWS Job Summary: We are seeking a highly skilled and experienced Data Scientist with a strong background in machine learning, computer vision, natural language processing (NLP), generative artificial intelligence (AI), and cloud technologies. As a Data Scientist, you will be working for a client and driving the development and implementation of advanced data models and algorithms to extract meaningful insights from complex datasets. You will work closely with cross-functional teams, including engineers, researchers, and product managers, to design and deploy cutting-edge AI solutions that address our business needs. The ideal candidate will have a minimum of 3 years of real hands on experience in machine learning , with a proven track record of successfully delivering projects in computer vision, NLP, generative AI, and at least one cloud platform. The Role: As our Tech Lead in AI/ML, you will play a crucial role in the hands-on development of mentoring peers and delivery of AI products powered by our internal AI models and machine learning pipelines. You'll identify new opportunities for AI solutions throughout the organization, and set the direction and roadmap required to implement MLOPS. You will partner with the team through the creation of AI models, and develop, and deploy LLM-based applications in production, evaluating and improving their performance and accuracy over time. Collaborating closely with Product, Research, and Engineering teams, youll ensure seamless integration of AI technologies into our products, setting new standards for data quality and model performance. Responsibilities: Design, develop, and maintain a AI/ML platform that is accurate, secure, and fast Lead workstreams within a lean and agile environment from requirements gathering to creating a plan of actionable tasks for the team Provide coaching, and mentorship to members of the data team on architecture, software development best practices, and new technologies Establish evaluation criteria for data quality tracking and production ML model tracking Partner with product, research, and engineering to ensure product changes integrate effectively . Required Qualifications: 6+ years in MLOps, ML engineering, MLOps, and data science with 2+ years leading and mentoring agile teams. Proven expertise in deploying essential MLOps components like CI/CD, model registry, and input loading. Skilled in creating and launching diverse models (statistical, LLM, GenAI, GPT 3.5/4.0) from POC to production. Proven ability to manage projects and programs, leading small teams (2-5 members) and directly handling data analysis, modeling, data pipeline setup, and MLOps Skilled in AIML, using platforms like AWS, Amazon Bedrock, and Snowflake, and proficient in Python, SQL, Tableau, and Alteryx 3+ years of experience working with Jupyter Notebooks, Git, GitHub, JIRA, and weights & biases, enhancing collaboration and version control in project development. Significant collaboration with research teams, contributing hands-on research skills that advance project outcomes. Preferred Qualifications: 2+ years of Tech Lead and management experience; taking on role as player coach and providing mentorship. Experience migrating data sets and workflows between legacy data platforms and services. Familiarity with stream processing and event driven architecture Comfortable moving quickly and working in a fast-paced, agile XP, lean environment. Experience in leading offshore and nearshore teams is highly valued.

About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: Senior AIML Engineer Experience : 6+ Yrs Location: Pune Skillsets- AIML , Gen AI, MLOps, AWS, Python, ML(Machine Learning), Data Science , SQL,AWS Job Summary: We are seeking a highly skilled and experienced Data Scientist with a strong background in machine learning, computer vision, natural language processing (NLP), generative artificial intelligence (AI), and cloud technologies. As a Data Scientist, you will be working for a client and driving the development and implementation of advanced data models and algorithms to extract meaningful insights from complex datasets. You will work closely with cross-functional teams, including engineers, researchers, and product managers, to design and deploy cutting-edge AI solutions that address our business needs. The ideal candidate will have a minimum of 3 years of real hands on experience in machine learning , with a proven track record of successfully delivering projects in computer vision, NLP, generative AI, and at least one cloud platform. The Role: As our Tech Lead in AI/ML, you will play a crucial role in the hands-on development of mentoring peers and delivery of AI products powered by our internal AI models and machine learning pipelines. You'll identify new opportunities for AI solutions throughout the organization, and set the direction and roadmap required to implement MLOPS. You will partner with the team through the creation of AI models, and develop, and deploy LLM-based applications in production, evaluating and improving their performance and accuracy over time. Collaborating closely with Product, Research, and Engineering teams, youll ensure seamless integration of AI technologies into our products, setting new standards for data quality and model performance. Responsibilities: Design, develop, and maintain a AI/ML platform that is accurate, secure, and fast Lead workstreams within a lean and agile environment from requirements gathering to creating a plan of actionable tasks for the team Provide coaching, and mentorship to members of the data team on architecture, software development best practices, and new technologies Establish evaluation criteria for data quality tracking and production ML model tracking Partner with product, research, and engineering to ensure product changes integrate effectively . Required Qualifications: 6+ years in MLOps, ML engineering, MLOps, and data science with 2+ years leading and mentoring agile teams. Proven expertise in deploying essential MLOps components like CI/CD, model registry, and input loading. Skilled in creating and launching diverse models (statistical, LLM, GenAI, GPT 3.5/4.0) from POC to production. Proven ability to manage projects and programs, leading small teams (2-5 members) and directly handling data analysis, modeling, data pipeline setup, and MLOps Skilled in AIML, using platforms like AWS, Amazon Bedrock, and Snowflake, and proficient in Python, SQL, Tableau, and Alteryx 3+ years of experience working with Jupyter Notebooks, Git, GitHub, JIRA, and weights & biases, enhancing collaboration and version control in project development. Significant collaboration with research teams, contributing hands-on research skills that advance project outcomes. Preferred Qualifications: 2+ years of Tech Lead and management experience; taking on role as player coach and providing mentorship. Experience migrating data sets and workflows between legacy data platforms and services. Familiarity with stream processing and event driven architecture Comfortable moving quickly and working in a fast-paced, agile XP, lean environment. Experience in leading offshore and nearshore teams is highly valued.

About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: AI Operations (AI Ops) Engineer Experience : 8+ Yrs Location: Pune, Hyderabad, Gurugram Skillsets- Azure, Gen AI, MLOps, Python, ML(Machine Learning), Data Science , SQL Job Summary: AI Operations (AI Ops) Engineer AI Ops Engineer with a strong background in Python, API development, Large Language Models (LLM) concepts, ML Ops, Azure Cloud and AI operations with 8-10 years of experience working on advanced AI/ML systems, cloud infrastructure, and API integrations, with a focus on operationalizing AI models and maintaining robust systems for AI-driven applications. This role requires a combination of technical expertise in cloud computing, machine learning, and software engineering. Collaborate with IT operations and business teams to support business user issues, requests, Production support and deployments; advocate best practices and recommend technical solutions for improvements in usability of application and systems performance Key Responsibilities: Technical Operations: Review, Implement and support enterprise-level AI platforms and services to drive IT operation excellence. Ensuring that new use cases are onboarded smoothly and operationalized Optimization: Analyze business processes to identify areas for automation and work with business stakeholders and IT teams to determine requirements and design software bots to reduce operational toil. AI Ops & Model Deployment: Lead the operationalization and deployment of AI/ML models into production environments, ensuring they are highly available, scalable, and performant. Implement and monitor Continuous Integration (CI) and Continuous Deployment (CD) pipelines. Python Development: Design and develop Python-based solutions for automating and managing the lifecycle of AI/ML models, including data ingestion, model training, and real-time prediction workflows. API Integration: Build and maintain robust APIs for model serving and integration with other systems. Ensure seamless communication between models, data pipelines, and consumer applications. LLM Concepts and Implementation: Apply knowledge of Large Language Models (LLMs) to develop AI-driven applications and services, ensuring models are optimized and performing efficiently in production. ML Ops: Implement and maintain Machine Learning Operations (ML Ops) practices for version control, monitoring, logging, and debugging of AI/ML models in production. Support model retraining, versioning, and A/B testing. Cloud Infrastructure: Leverage Azure Cloud services for hosting and scaling AI applications, ensuring security, compliance, and performance. Implement infrastructure as code (IaC) using tools like Azure DevOps. Collaboration: Work closely with backend engineers, data engineers/developers, infrastructure engineers , operational SMEs and business stakeholders to tackle evolving challenges in the field of AI/ML to ensure AI solutions meet business requirements and performance benchmarks. Monitoring & Optimization: Continuously monitor the performance of deployed AI models and optimize them for efficiency, cost-effectiveness, and accuracy. Implement alerting and logging mechanisms by scripts or through observability solution. Documentation & Best Practices: Document AI Ops processes, Use cases, tools, and workflows. Establish and enforce best practices for managing AI models in production environments. Required Skills & Qualifications:(Python Developer + ML-Engineer + MLOPS+ Azure) Experience: 8-10 years of experience in software development, with a focus on AI/ML operations, cloud infrastructure, and DevOps practices. -Data ScienePython: Advanced proficiency in Python, including experience with AI/ML libraries such as TensorFlow, PyTorch, scikit-learn, and Pandas. MLOPS Engineer APIs: Strong experience in designing, developing, and maintaining RESTful APIs for AI/ML model deployment and integration. ML Ops: In-depth understanding of Machine Learning Operations, including model versioning, monitoring, deployment, and automation of ML workflows. Data Science LLM Concepts: Familiarity with Large Language Models (LLMs), including experience working with transformer-based models such as GPT, BERT, or T5. Data Engineer Azure Cloud: Hands-on experience with Azure Cloud services (Azure ML, Azure DevOps, Azure Functions, etc.) and cloud infrastructure management. DevOps & CI/CD: Proficient in setting up CI/CD pipelines for AI/ML models and using tools like Jenkins, GitLab, or Azure DevOps for automation. DE Data Management & Tools: Experience working with data storage and processing tools like Azure Blob Storage, Azure SQL Database, Kafka, or similar. Version Control: Expertise with Git and version control best practices for collaborative development of AI systems. Problem Solving: Strong analytical and troubleshooting skills, with the ability to identify root causes and optimize AI/ML models and systems. Communication & Collaboration: Excellent communication skills and the ability to work effectively in a cross-functional team environment. Preferred Skills: Cloud Certifications: Azure certifications such as Azure Solutions Architect, Azure AI Engineer, or Azure DevOps Engineer. Security & Compliance: Understanding of security best practices in AI model deployment and experience with secure handling of sensitive data in the cloud. Big Data Tools: Familiarity with big data processing frameworks (e.g., Apache Spark, Hadoop) and integration with AI/ML pipelines. Agile Methodologies: Experience working in Agile teams, with knowledge of Scrum, Kanban, or similar frameworks. Education: A Bachelor's or Masters degree in Computer Science, Engineering, Data Science, or a related field is preferred.

About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: AI Operations (AI Ops) Engineer Experience : 8+ Yrs Location: Pune, Hyderabad, Gurugram Skillsets- Azure, Gen AI, MLOps, Python, ML(Machine Learning), Data Science , SQL Job Summary: AI Operations (AI Ops) Engineer AI Ops Engineer with a strong background in Python, API development, Large Language Models (LLM) concepts, ML Ops, Azure Cloud and AI operations with 8-10 years of experience working on advanced AI/ML systems, cloud infrastructure, and API integrations, with a focus on operationalizing AI models and maintaining robust systems for AI-driven applications. This role requires a combination of technical expertise in cloud computing, machine learning, and software engineering. Collaborate with IT operations and business teams to support business user issues, requests, Production support and deployments; advocate best practices and recommend technical solutions for improvements in usability of application and systems performance Key Responsibilities: Technical Operations: Review, Implement and support enterprise-level AI platforms and services to drive IT operation excellence. Ensuring that new use cases are onboarded smoothly and operationalized Optimization: Analyze business processes to identify areas for automation and work with business stakeholders and IT teams to determine requirements and design software bots to reduce operational toil. AI Ops & Model Deployment: Lead the operationalization and deployment of AI/ML models into production environments, ensuring they are highly available, scalable, and performant. Implement and monitor Continuous Integration (CI) and Continuous Deployment (CD) pipelines. Python Development: Design and develop Python-based solutions for automating and managing the lifecycle of AI/ML models, including data ingestion, model training, and real-time prediction workflows. API Integration: Build and maintain robust APIs for model serving and integration with other systems. Ensure seamless communication between models, data pipelines, and consumer applications. LLM Concepts and Implementation: Apply knowledge of Large Language Models (LLMs) to develop AI-driven applications and services, ensuring models are optimized and performing efficiently in production. ML Ops: Implement and maintain Machine Learning Operations (ML Ops) practices for version control, monitoring, logging, and debugging of AI/ML models in production. Support model retraining, versioning, and A/B testing. Cloud Infrastructure: Leverage Azure Cloud services for hosting and scaling AI applications, ensuring security, compliance, and performance. Implement infrastructure as code (IaC) using tools like Azure DevOps. Collaboration: Work closely with backend engineers, data engineers/developers, infrastructure engineers , operational SMEs and business stakeholders to tackle evolving challenges in the field of AI/ML to ensure AI solutions meet business requirements and performance benchmarks. Monitoring & Optimization: Continuously monitor the performance of deployed AI models and optimize them for efficiency, cost-effectiveness, and accuracy. Implement alerting and logging mechanisms by scripts or through observability solution. Documentation & Best Practices: Document AI Ops processes, Use cases, tools, and workflows. Establish and enforce best practices for managing AI models in production environments. Required Skills & Qualifications:(Python Developer + ML-Engineer + MLOPS+ Azure) Experience: 8-10 years of experience in software development, with a focus on AI/ML operations, cloud infrastructure, and DevOps practices. -Data ScienePython: Advanced proficiency in Python, including experience with AI/ML libraries such as TensorFlow, PyTorch, scikit-learn, and Pandas. MLOPS Engineer APIs: Strong experience in designing, developing, and maintaining RESTful APIs for AI/ML model deployment and integration. ML Ops: In-depth understanding of Machine Learning Operations, including model versioning, monitoring, deployment, and automation of ML workflows. Data Science LLM Concepts: Familiarity with Large Language Models (LLMs), including experience working with transformer-based models such as GPT, BERT, or T5. Data Engineer Azure Cloud: Hands-on experience with Azure Cloud services (Azure ML, Azure DevOps, Azure Functions, etc.) and cloud infrastructure management. DevOps & CI/CD: Proficient in setting up CI/CD pipelines for AI/ML models and using tools like Jenkins, GitLab, or Azure DevOps for automation. DE Data Management & Tools: Experience working with data storage and processing tools like Azure Blob Storage, Azure SQL Database, Kafka, or similar. Version Control: Expertise with Git and version control best practices for collaborative development of AI systems. Problem Solving: Strong analytical and troubleshooting skills, with the ability to identify root causes and optimize AI/ML models and systems. Communication & Collaboration: Excellent communication skills and the ability to work effectively in a cross-functional team environment. Preferred Skills: Cloud Certifications: Azure certifications such as Azure Solutions Architect, Azure AI Engineer, or Azure DevOps Engineer. Security & Compliance: Understanding of security best practices in AI model deployment and experience with secure handling of sensitive data in the cloud. Big Data Tools: Familiarity with big data processing frameworks (e.g., Apache Spark, Hadoop) and integration with AI/ML pipelines. Agile Methodologies: Experience working in Agile teams, with knowledge of Scrum, Kanban, or similar frameworks. Education: A Bachelor's or Masters degree in Computer Science, Engineering, Data Science, or a related field is preferred.

Entity :- Accenture Strategy & Consulting Team :- Strategy & Consulting Global Network Practice :- Data & AI - CMT Title :- Consultant Level 9 Job location :- Bangalore/Gurgaon/Hyderabad Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition As part of our Data & AI practice, you will join a worldwide network of over 20,000 smart and driven colleagues experienced in leading AI/ML/Statistical tools, methods and applications. From data to analytics and insights to actions, our forward-thinking consultants provide analytically informed, issue-based insights at scale to help our clients improve outcomes and achieve high performance. About Comms & Media practice within Strategy & Consulting: Comms & Media (C&M) is one of the Industry Practices within Accenture's S&C Global Network team. It focuses in serving clients across specific Industries Communications, Media & Entertainment. Communications Focuses primarily on industries related with telecommunications and information & communication technology (ICT). This team serves most of the world's leading wireline, wireless, cable and satellite communications and service providers Media & Entertainment Focuses on industries like broadcast, entertainment, print and publishing Globally, Accenture Comms & Media practice works to develop value growth strategies for its clients and infuse AI & GenAI to help deliver top their business imperatives i.e., revenue growth & cost reduction. From multi-year Data & AI transformation projects to shorter more agile engagements, we have a rapidly expanding portfolio of hyper-growth clients and an increasing footprint with next-gen solutions and industry practices. Responsibilities/Authorities A Telco domain experienced and data science consultant is responsible to help the clients with designing & delivering AI solutions. He/she should be strong in Telco domain, AI fundamentals and should have good hands-on experience working with the following: Ability to work with large data sets and present conclusions to key stakeholders; Data management using SQL. Propose solutions to the client based on gap analysis for the existing Telco platforms that can generate long term & sustainable value to the client. Gather business requirements from client stakeholders via interactions like interviews and workshops with all stakeholders Track down and read all previous information on the problem or issue in question. Explore obvious and known avenues thoroughly. Ask a series of probing questions to get to the root of a problem. Ability to understand the as-is process; understand issues with the processes which can be resolved either through Data & AI or process solutions and design detail level to-be state Understand customer needs and identify/translate them to business requirements (business requirement definition), business process flows and functional requirements and be able to inform the best approach to the problem. Adopt a clear and systematic approach to complex issues (i.e. A leads to B leads to C). Analyze relationships between several parts of a problem or situation. Anticipate obstacles and identify a critical path for a project. Independently able to deliver products and services that empower clients to implement effective solutions. Makes specific changes and improvements to processes or own work to achieve more. Work with other team members and make deliberate efforts to keep others up to date. Establish a consistent and collaborative presence with clients and act as the primary point of contact for assigned clients; escalate, track, and solve client issues. Partner with clients to understand end clients' business goals, marketing objectives, and competitive constraints. Storytelling Crunch the data & numbers to craft a story to be presented to senior client stakeholders. Should be able to travel or relocate to Japan as per business requirement. Qualifications JOB REQUIREMENTS Overall Experience Overall 5+ years of experience in Data Science & at least 3 years in Telecom Analytics Masters (MBA/MSc/MTech) from a Tier 1/Tier 2 and Engineering from Tier 1 school Demonstrated experience in solving real-world data problems through Data & AI Direct onsite experience (i.e., experience of facing client inside client offices in India or abroad) is mandatory. Please note we are looking for client facing roles. Proficiency with data mining, mathematics, and statistical analysis Advanced pattern recognition and predictive modeling experience; knowledge of Advanced analytical fields in text mining, Image recognition, video analytics, IoT etc. Execution level understanding of econometric/statistical modeling packages Traditional techniques like Linear/logistic regression, multivariate statistical analysis, time series techniques, fixed/Random effect modelling. Machine learning techniques like - Random Forest, Gradient Boosting, XG boost, decision trees, clustering etc. Knowledge of Deep learning modeling techniques like RNN, CNN etc. Experience using digital & statistical modeling software (one or more) Python, R, PySpark, SQL, BigQuery, Vertex AI Proficient in Excel, MS word, Power point, and corporate soft skills Knowledge of Dashboard creation platforms Excel, tableau, Power BI etc. Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical stakeholders. Strong analytical, problem-solving skills and good communication skills Self-Starter with ability to work independently across multiple projects and set priorities Strong team player Proactive and solution oriented, able to guide junior team members. Execution knowledge of optimization techniques is a good-to-have Exact optimization Linear, Non-linear optimization techniques Evolutionary optimization Both population and search-based algorithms Cloud platform Certification, experience in Computer Vision are good-to-haves

Zycus is seeking for talented Machine Learning Engineers to join our dynamic team. Candidates with strong background in Analytics and Data mining (Web, Social and Big data), Machine Learning, Pattern Recognition, Natural Language Processing, Computational Linguistics, Statistical Modelling, Inferencing, Information Retrieval, Large Scale Distributed Systems, Cloud Computing, Econometrics, Quantitative Marketing, Applied Game Theory, Mechanism Design, Operations Research, Optimization, Human Computer Interaction and Information Visualization. Applicants with a background in other quantitative areas are also encouraged to apply. Role & responsibilities Develop and implement AI solutions leveraging expertise in Analytics and Data Mining across Web, Social, and Big Data platforms. Good understanding and implementation of Generative AI for content generation, creative applications, and problem-solving across various domains. Work as the data strategist, identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with the engineering team to strategize and execute the development of data products. Utilize Machine Learning techniques for pattern recognition and inference to enhance existing products and develop new strategic initiatives. Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks. Collaborate with cross-functional teams to integrate Natural Language Processing and Computational Linguistics into product development processes. Apply Statistical Modeling and Econometrics to analyze data and derive actionable insights for quantitative marketing strategies and to make predictions based on historical data. Contribute to the design and optimization of Large Scale Distributed Systems and Cloud Computing infrastructure. Enhance user experience through Human-Computer Interaction principles and Information Visualization techniques. Preferred candidate profile Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Statistics, Mathematics, or a related field. 6-11 years of experience Graduate/Post Graduate from Tier I institutes Strong background in Analytics, Data Mining, Machine Learning, and related disciplines. Experience with programming languages such as Python, R, Java, or C++. Experience in working with NLP, Computer Vision/Image Processing, Regression and Deep Learning algorithms. Proficiency in handling large datasets and implementing statistical models. Familiarity with Cloud Computing platforms and distributed systems architecture. Experience using Web Services like Redshift/S3/Spark/DigitalOcean, etc. Experience with Distributed Data and Computing tools. Experience in EDA (Exploratory Data Analysis.) Excellent Communication and Teamwork capabilities. Perks and benefits Five Reasons Why You Should Join Zycus: Cloud Product Company : We are a Cloud SaaS Company and our products are created by using the latest technologies like ML and AI. Our UI is in Angular JS and we are developing our mobile apps using React. A Market Leader : Zycus is recognized by Gartner (world's leading market research analyst) as a Leader in Procurement Software Suites. Move between Roles: We believe that change leads to growth and therefore we allow our employees to shift careers and move to different roles and functions within the organization Get a Global Exposure: You get to work and deal with our global customers. Create an Impact: Zycus gives you the environment to create an impact on the product and transform your ideas into reality. Even our junior engineers get the opportunity to work on different product features.

Stantec Digital Solutions is a unique consulting team. We pride ourselves on being customer obsessed and highly focused on Digital Engineering transformation. We apply predictive technology to large volumes of data to solve a wide spectrum of problems. Stantec Digital Solutions works together with internal & external customers to address their business needs with Artificial Intelligence (AI) solutions. Digital Solutions has an opening for the position of Senior Machine Learning Engineer in the Pune, India office. The selected candidate will help solve problems and derive business value through the application of Machine Learning (ML) to engineering and science problems. The position calls for using massive amounts of disparate data to develop ML models. This person will get to work closely with a global innovation team and solve problems across different geographies. If youre eager to apply ML to a diverse array of enterprise Architectural, Environmental and Physical Engineering use cases, this is likely the position for you. Role & responsibilities Model Development and Deployment: Design, develop, and deploy machine learning models for computer vision, geospatial analyses, and LLM chatbots. Data Pipeline Management: Collect, preprocess, and analyze large datasets from diverse sources, including satellite imagery, geospatial data, and textual data. Performance Monitoring and Optimization: Monitor the performance of deployed models and implement improvements to enhance accuracy, efficiency, and scalability. Troubleshooting: Troubleshoot and resolve issues related to model performance, data drift, and software. Collaboration and Communication: Collaborate with data scientists, software engineers, and domain experts to integrate machine learning solutions into existing systems. Research and Innovation: Stay up-to-date with the latest advancements in machine learning, computer vision, geospatial analysis, and natural language processing Preferred candidate profile Education: Bachelors degree in a quantitative field Experience: 5 years’ experience working on projects involving or directly adjacent to machine learning Cloud Computing: Proven experience with Cloud Platforms like Azure, AWS, or GCP. Programming Languages: Strong proficiency in Python & SQL. ML Algorithms: Experience with deep learning techniques and architectures (e.g., CNNs, RNNs, Transformers).

Entity :- Accenture Strategy & Consulting Team :- Strategy & Consulting Global Network Practice :- Communications & Media - AI & Data Architectures Title :- Ind & Func AI Value Strategy Sr Manager Job location :- Bangalore About S&C - Global Network:- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition. WHAT'S IN IT FOR YOU? Accenture has committed to invest USD 3Billion into GenAI in next 3 years. We will continually invest in your learning and growth. Youll work with Accenture's highly skilled and experienced practitioners, and Accenture will support you in growing your own career path and interests. You'll be part of a diverse, vibrant, global Accenture Data and AI community, continually pushing the boundaries of business capabilities. What you would do in this role AI Architecture strategy and Assessment: Lead the development and assessment of AI architectures, ensuring they align with business goals and objectives. Evaluate existing AI solutions, identifying areas for improvement, optimization, and innovation. Operating Model Design: Design robust operating models for Generative AI implementations, considering scalability, efficiency, and business impact. Collaborate with cross-functional teams to integrate AI capabilities seamlessly into existing operational workflows. Develop comprehensive blueprints for Generative AI solutions, outlining technical specifications, data requirements, and integration points. Ensure blueprints adhere to industry best practices and standards. Roadmap Building: Create strategic roadmaps for the implementation and evolution of Generative AI solutions. Define milestones, key performance indicators (KPIs), and success criteria to measure the progress of AI initiatives. Incubating GenAI Solutions: Identify emerging trends and technologies in Generative AI and incubate innovative solutions. Work closely with research and development teams to experiment and prototype new Generative AI concepts. Oversee the end-to-end implementation of Generative AI solutions, collaborating with engineering teams to ensure successful deployment. Provide technical leadership and guidance throughout the implementation lifecycle. Qualifications Who we are looking for? Bachelors or advanced degree in Computer Science, Artificial Intelligence, or a related field. 15+ years of hands-on experience in AI, with a focus on Generative AI. Proven track record of designing and implementing successful AI solutions in real-world business environments. In-depth knowledge of AI architectures, frameworks, and tools. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities, with experience working cross-functionally. Demonstrated leadership in driving AI initiatives from conception to deployment. Experience in Telecom or Hi Tech or Software and platform industry desirable Tools & Techniques: Proficiency in Python programming language and key libraries like Pandas, TensorFlow, PyTorch, and Keras. Understanding and implemention knowledge of deep learning architectures such as CNNs, RNNs, and GANs. Good software engineering practices, including code modularization, documentation, and testing Familiarity with cloud platforms like AWS, Google Cloud, or Microsoft Azure can be beneficial for deploying and scaling GenAI models. If you are a visionary AI architect with a passion for innovation and a proven track record of delivering impactful Generative AI solutions, we invite you to apply and contribute to our dynamic and forward-thinking organization.

Entity :- Accenture Strategy & Consulting Team :- Strategy & Consulting Global Network Practice :- Communications & Media - AI & Data Architectures Title :- Ind & Func AI Value Strategy Manager Job location :- Bangalore About S&C - Global Network:- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition. WHAT'S IN IT FOR YOU? Accenture has committed to invest USD 3Billion into GenAI in next 3 years. We will continually invest in your learning and growth. Youll work with Accenture's highly skilled and experienced practitioners, and Accenture will support you in growing your own career path and interests. You'll be part of a diverse, vibrant, global Accenture Data and AI community, continually pushing the boundaries of business capabilities. What you would do in this role AI Architecture Strategy and Assessment: Lead the development and assessment of AI architectures, ensuring they align with business goals and objectives. Evaluate existing AI solutions, identifying areas for improvement, optimization, and innovation. Operating Model Design: Design robust operating models for Generative AI implementations, considering scalability, efficiency, and business impact. Collaborate with cross-functional teams to integrate AI capabilities seamlessly into existing operational workflows. Develop comprehensive blueprints for Generative AI solutions, outlining technical specifications, data requirements, and integration points. Ensure blueprints adhere to industry best practices and standards. Roadmap Building: Create strategic roadmaps for the implementation and evolution of Generative AI solutions. Define milestones, key performance indicators (KPIs), and success criteria to measure the progress of AI initiatives. Incubating GenAI Solutions: Identify emerging trends and technologies in Generative AI and incubate innovative solutions. Work closely with research and development teams to experiment and prototype new Generative AI concepts. Oversee the end-to-end implementation of Generative AI solutions, collaborating with engineering teams to ensure successful deployment. Provide technical leadership and guidance throughout the implementation lifecycle. Qualifications Who we are looking for? Bachelors or advanced degree in Computer Science, Artificial Intelligence, or a related field. 15+ years of hands-on experience in AI, with a focus on Generative AI. Proven track record of designing and implementing successful AI solutions in real-world business environments. In-depth knowledge of AI architectures, frameworks, and tools. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities, with experience working cross-functionally. Demonstrated leadership in driving AI initiatives from conception to deployment. Experience in Telecom or Hi Tech or Software and platform industry desirable Tools & Techniques: Proficiency in Python programming language and key libraries like Pandas, TensorFlow, PyTorch, and Keras. Understanding and implemention knowledge of deep learning architectures such as CNNs, RNNs, and GANs. Good software engineering practices, including code modularization, documentation, and testing Familiarity with cloud platforms like AWS, Google Cloud, or Microsoft Azure can be beneficial for deploying and scaling GenAI models. If you are a visionary AI architect with a passion for innovation and a proven track record of delivering impactful Generative AI solutions, we invite you to apply and contribute to our dynamic and forward-thinking organization. Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law.