228 Lstm Jobs

Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, the mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods, and models. In collaboration with leading academics, industry experts, and highly skilled engineers, the goal is to equip customers to generate sophisticated new insights from the biggest of big data. Join the team to do the best work of your career and make a profound social impact as an Advisor on the Data Science Team in Bangalore. As a Data Science Advisor, you will contribute to the business strategy and influence decision-making based on information gained from deep dive analysis. You will produce actionable and compelling recommendations by interpreting insights from complex data sets. Designing processes to consolidate and examine unstructured data to generate actionable insights will be part of your responsibilities. Additionally, you will partner with business leaders, engineers, and industry experts to construct predictive models, algorithms, and probability engines. You will: - Partner with internal and external teams to understand customer requirements and develop proposals. - Conduct interactions with external customers to gather project requirements, provide status updates, and share analytical insights. - Implement preliminary data exploration and data preparation steps for model development/validation. - Apply a broad range of techniques and theories from statistics, machine learning, and business intelligence to deliver actionable business insights. - Solution, build, deploy, and set up monitoring for models. Qualifications: - 6+ years of related experience with proficiency in NLP, Machine Learning, Computer Vision, and GenAI. - Working experience in data visualization (e.g., Power BI, matplotlib, plotly). - Hands-on experience with CNN, LSTM, YOLO, and database skills including SQL, Postgres SQL, PGVector, and ChromaDB. - Proven experience in MLOps and LLMOps, with a strong understanding of ML lifecycle management. - Expertise with large language models (LLMs), prompt engineering, fine-tuning, and integrating LLMs into applications for natural language processing (NLP) tasks. Desirable Skills: - Strong product/technology/industry knowledge and familiarity with streaming/messaging frameworks (e.g., Kafka, RabbitMQ, ZeroMQ). - Experience with cloud platforms (e.g., AWS, Azure, GCP). - Experience with web technologies and frameworks (e.g., HTTP/REST/GraphQL, Flask, Django). - Skilled in programming languages like Java or JavaScript. Dell Technologies is committed to providing equal employment opportunities for all employees and creating a work environment free of discrimination and harassment. If you are looking for an opportunity to grow your career with advanced technology and some of the best minds in the industry, this role might be the perfect fit for you. Join Dell Technologies to build a future that works for everyone because Progress Takes All of Us.,

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate Job Description & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes. Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decision-making and automation. Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us. At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. " Responsibilities Position responsibilities and expectations Designing and building analytical /DL/ ML algorithms using Python, R and other statistical tools. Strong data representation and lucid presentation (of analysis/modelling output) using Python, R Markdown, Power Point, Excel etc. Ability to learn new scripting language or analytics platform. Technical Skills required (must have) HandsOn Exposure to Generative AI (Design, development of GenAI application in production) Strong understanding of RAG, Vector Database, Lang Chain and multimodal AI applications. Strong understanding of deploying and optimizing AI application in production. Strong knowledge of statistical and data mining techniques like Linear & Logistic Regression analysis, Decision trees, Bagging, Boosting, Time Series and Non-parametric analysis. Strong knowledge of DL & Neural Network Architectures (CNN, RNN, LSTM, Transformers etc.) Strong knowledge of SQL and R/Python and experience with distribute data/computing tools/IDEs. Experience in advanced Text Analytics (NLP, NLU, NLG). Strong hands-on experience of end-to-end statistical model development and implementation Understanding of LLMOps, ML Ops for scalable ML development. Basic understanding of DevOps and deployment of models into production (PyTorch, TensorFlow etc.). Expert level proficiency algorithm building languages like SQL, R and Python and data visualization tools like Shiny, Qlik, Power BI etc. Exposure to Cloud Platform (Azure or AWS or GCP) technologies and services like Azure AI/ Sage maker/Vertex AI, Auto ML, Azure Index, Azure Functions, OCR, OpenAI, storage, scaling etc. Technical Skills required (Any one or more) Experience in video/ image analytics (Computer Vision) Experience in IoT/ machine logs data analysis Exposure to data analytics platforms like Domino Data Lab, c3.ai, H2O, Alteryx or KNIME Expertise in Cloud analytics platforms (Azure, AWS or Google) Experience in Process Mining with expertise in Celonis or other tools Proven capability in using Generative AI services like OpenAI, Google (Gemini) Understanding of Agentic AI Framework (Lang Graph, Auto gen etc.) Understanding of fine-tuning for pre-trained models like GPT, LLaMA, Claude etc. using LoRA, QLoRA and PEFT technique. Proven capability in building customized models from open-source distributions like Llama, Stable Diffusion Mandatory Skill Sets AI chatbots, Data structures, GenAI object-oriented programming, IDE, API, LLM Prompts, Streamlit Preferred Skill Sets AI chatbots, Data structures, GenAI object-oriented programming, IDE, API, LLM Prompts, Streamlit Years Of Experience Required 3-6 Years Education Qualification BE, B. Tech, M. Tech, M. Stat, Ph.D., M.Sc. (Stats / Maths) Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Bachelor of Technology, Doctor of Philosophy, Bachelor of Engineering Degrees/Field Of Study Preferred Certifications (if blank, certifications not specified) Required Skills Chatbots, Data Structures, Generative AI Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, AI Implementation, Analytical Thinking, C++ Programming Language, Communication, Complex Data Analysis, Creativity, Data Analysis, Data Infrastructure, Data Integration, Data Modeling, Data Pipeline, Data Quality, Deep Learning, Embracing Change, Emotional Regulation, Empathy, GPU Programming, Inclusion, Intellectual Curiosity, Java (Programming Language), Learning Agility, Machine Learning {+ 25 more} Desired Languages (If blank, desired languages not specified) Travel Requirements Not Specified Available for Work Visa Sponsorship? No Government Clearance Required? No Job Posting End Date

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Associate Job Description & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes. Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decision-making and automation. Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us. At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. " Responsibilities Position responsibilities and expectations Designing and building analytical /DL/ ML algorithms using Python, R and other statistical tools. Strong data representation and lucid presentation (of analysis/modelling output) using Python, R Markdown, Power Point, Excel etc. Ability to learn new scripting language or analytics platform. Technical Skills required (must have) HandsOn Exposure to Generative AI (Design, development of GenAI application in production) Strong understanding of RAG, Vector Database, Lang Chain and multimodal AI applications. Strong understanding of deploying and optimizing AI application in production. Strong knowledge of statistical and data mining techniques like Linear & Logistic Regression analysis, Decision trees, Bagging, Boosting, Time Series and Non-parametric analysis. Strong knowledge of DL & Neural Network Architectures (CNN, RNN, LSTM, Transformers etc.) Strong knowledge of SQL and R/Python and experience with distribute data/computing tools/IDEs. Experience in advanced Text Analytics (NLP, NLU, NLG). Strong hands-on experience of end-to-end statistical model development and implementation Understanding of LLMOps, ML Ops for scalable ML development. Basic understanding of DevOps and deployment of models into production (PyTorch, TensorFlow etc.). Expert level proficiency algorithm building languages like SQL, R and Python and data visualization tools like Shiny, Qlik, Power BI etc. Exposure to Cloud Platform (Azure or AWS or GCP) technologies and services like Azure AI/ Sage maker/Vertex AI, Auto ML, Azure Index, Azure Functions, OCR, OpenAI, storage, scaling etc. Technical Skills required (Any one or more) Experience in video/ image analytics (Computer Vision) Experience in IoT/ machine logs data analysis Exposure to data analytics platforms like Domino Data Lab, c3.ai, H2O, Alteryx or KNIME Expertise in Cloud analytics platforms (Azure, AWS or Google) Experience in Process Mining with expertise in Celonis or other tools Proven capability in using Generative AI services like OpenAI, Google (Gemini) Understanding of Agentic AI Framework (Lang Graph, Auto gen etc.) Understanding of fine-tuning for pre-trained models like GPT, LLaMA, Claude etc. using LoRA, QLoRA and PEFT technique. Proven capability in building customized models from open-source distributions like Llama, Stable Diffusion Mandatory Skill Sets AI chatbots, Data structures, GenAI object-oriented programming, IDE, API, LLM Prompts, Streamlit Preferred Skill Sets AI chatbots, Data structures, GenAI object-oriented programming, IDE, API, LLM Prompts, Streamlit Years Of Experience Required 3-6 Years Education Qualification BE, B. Tech, M. Tech, M. Stat, Ph.D., M.Sc. (Stats / Maths) Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Doctor of Philosophy, Bachelor of Engineering, Bachelor of Technology Degrees/Field Of Study Preferred Certifications (if blank, certifications not specified) Required Skills Chatbots, Data Structures, Generative AI Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, AI Implementation, C++ Programming Language, Communication, Complex Data Analysis, Data Analysis, Data Infrastructure, Data Integration, Data Modeling, Data Pipeline, Data Quality, Deep Learning, Emotional Regulation, Empathy, GPU Programming, Inclusion, Intellectual Curiosity, Java (Programming Language), Machine Learning, Machine Learning Libraries, Named Entity Recognition, Natural Language Processing (NLP), Natural Language Toolkit (NLTK) {+ 20 more} Desired Languages (If blank, desired languages not specified) Travel Requirements Available for Work Visa Sponsorship? Government Clearance Required? Job Posting End Date

🚀 We're Hiring: Data Scientist (AI/ML | Industrial IoT | Time Series) 📍 Location: Hyderabad 🧠 Experience: 5+ Years Join our AI/ML initiative to predict industrial alarms from complex sensor data in refinery environments. You'll lead the development of predictive models using time series data, maintenance logs, and work in an Expert-in-the-Loop (EITL) setup with domain experts. 🔍 Key Responsibilities: Develop ML models for anomaly detection & alarm prediction from sensor/IoT time series data. Collaborate with domain experts to validate model outputs. Implement data preprocessing, feature engineering & scalable pipelines. Monitor model performance, drift, explainability (SHAP, confidence), and retraining. Contribute to production-grade MLOps workflows. ✅ What You Bring: 5+ yrs experience in Data Science/ML, especially with time series models (LSTM, ARIMA, Autoencoders). Proficiency in Python, ML libraries (scikit-learn, TensorFlow, PyTorch). Hands-on with IoT/sensor data in manufacturing/industrial domains. Experience with MLOps tools (MLflow, SageMaker, Kubeflow). Strong grasp of model interpretability, ETL (Pandas, PySpark, SQL), and cloud deployment. ✨ Bonus Points: Background in oil & gas, SCADA systems, maintenance logs, or industrial control systems. Experience with cloud platforms (AWS/GCP/Azure) and alarm classification standards.

As an expectation a fitting candidate must have/be: Ability to analyze business problem and cut through the data challenges. Ability to churn the raw corpus and develop a data/ML model to provide business analytics (not just EDA), machine learning based document processing and information retrieval Quick to develop the POCs and transform it to high scale production ready code. Experience in extracting data through complex unstructured documents using NLP based technologies. Good to have : Document analysis using Image processing/computer vision and geometric deep learning Technology Stack: Python as a primary programming language. Conceptual understanding of classic ML/DL Algorithms like Regression, Support Vectors, Decision tree, Clustering, Random Forest, CART, Ensemble, Neural Networks, CNN, RNN, LSTM etc. Programming: Must Have: Must be hands-on with data structures using List, tuple, dictionary, collections, iterators, Pandas, NumPy and Object-oriented programming Good to have: Design patterns/System design, cython ML libraries: Must Have: Scikit-learn, XGBoost, imblearn, SciPy, Gensim Good to have: matplotlib/plotly, Lime/sharp Data extraction and handling: Must Have: DASK/Modin, beautifulsoup/scrappy, Multiprocessing Good to have: Data Augmentation, Pyspark, Accelerate NLP/Text analytics: Must Have: Bag of words, text ranking algorithm, Word2vec, language model, entity recognition, CRF/HMM, topic modelling, Sequence to Sequence Good to have: Machine comprehension, translation, elastic search Deep learning: Must Have: TensorFlow/PyTorch, Neural nets, Sequential models, CNN, LSTM/GRU/RNN, Attention, Transformers, Residual Networks Good to have: Knowledge of optimization, Distributed training/computing, Language models Software peripherals: Must Have: REST services, SQL/NoSQL, UNIX, Code versioning Good to have: Docker containers, data versioning Research: Must Have: Well verse with latest trends in ML and DL area. Zeal to research and implement cutting areas in AI segment to solve complex problems Good to have: Contributed to research papers/patents and it is published on internet in ML and DL Morningstar is an equal opportunity employer. Morningstar’s hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. We’ve found that we’re at our best when we’re purposely together on a regular basis, at least three days each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you’ll have tools and resources to engage meaningfully with your global colleagues. I10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal Entity

Experience : 2-7 Years Fresh Graduates with good knowledge in AI Models Tensorflow / Tensflow Lite will be considered for trainee positions. Required Skills: • Knowledge of anomaly detection techniques (statistical models, unsupervised learning) • Experience in integrating AI models (optimization for edge devices, TensorFlow Lite , etc.) • Fundamental understanding of machine learning and deep learning (CNN, RNN, GAN) • Experience with Python libraries (TensorFlow, PyTorch, scikit-learn, etc.) • Understanding of time-series data processing (experience with LSTM, GRU, etc.) • Sensor data processing (noise reduction, feature extraction, preprocessing techniques) • Data visualization and analysis skills (Pandas, Matplotlib, Seaborn) • AI model optimization and evaluation methods (cross-validation, hyperparameter tuning)

You are invited to join our team as a Software Engineer specializing in AI/ML tools. With a minimum of 3 to 6 years of experience, you will play a crucial role in transforming natural language data into valuable features using NLP techniques to support classification algorithms. Your responsibilities will include statistical analysis, machine learning methods, and text representation techniques, ensuring the effective design of software architecture. As an ideal candidate, you will have proven experience as an NLP Engineer or in a similar role, along with a deep understanding of NLP techniques for text representation, Information Extraction, semantic extraction techniques, data structures, and modeling. Proficiency in Generative AI, LLM Model, LangChain, and text representation techniques like n-grams, bag of words, sentiment analysis, word embedding, as well as knowledge of deep learning algorithms such as LSTM/GRU/CNN will be essential. You should also have experience with machine learning frameworks like Keras or PyTorch, and libraries such as scikit-learn. The ability to write robust and testable code, coupled with strong analytical and problem-solving skills, will be key to your success in this role. A degree in Computer Science, Mathematics, Computational Linguistics, or a related field is required. If you possess the relevant qualifications and skills in AI/ML, NLP, LLM Model, LangChain, n-grams, LSTM/GRU/CNN, and Keras/PyTorch, we welcome your application. We are an equal opportunity employer and encourage candidates who are on a career break but are passionate about restarting their professional journey to apply. Join us and be a part of a dynamic team that values innovation and excellence.,

Qualcomm India Private Limited is seeking a candidate to join their Multimedia Audio Systems Group as a Voice AI Engineer. As part of the team, you will be responsible for prototyping and productizing Voice AI Models for tasks such as Automatic Speech Recognition (ASR), Text-to-Speech (TTS), NLP, Multilingual Translation, Summarization, Language modeling, and other Speech/text generation tasks. You will work closely with a team of engineers to develop, train, and optimize Voice AI models for efficient offload to NPU, GPU, and CPU. Additionally, you will conduct model evaluation studies, competitive analysis, and collaborate with other R&D and Systems teams for system integration, use case validation, efficient offload to HW accelerators, and commercialization support. The ideal candidate should have strong programming skills in C/C++ and Python, along with experience in ML inference optimizations. Proficiency in designing, implementing, and training DL models using high-level languages/frameworks such as PyTorch, TensorFlow, and ONNX is required. Knowledge of ML architectures and operators like Transformers, LSTM, GRUs, and familiarity with recent trends in machine learning and traditional statistical modeling/feature extraction techniques are essential. Experience in Speech-to-text, Text-to-Speech, Speech-to-Speech, NLP applications, model quantization, compression techniques, software development on embedded platforms, software design patterns, multi-threaded programming, computer architecture, operating systems, data structures, algorithms, fixed-point coding, and AI HW accelerators (NPU or GPU) is a plus. Candidates should hold a Bachelor's/Masters/PhD degree in Engineering, Electronics and Communication, Computer Science, or related field, along with 3+ years of experience in Audio Systems engineering, Audio Signal Processing modules, ML Model development, or related work. Minimum qualifications include a Bachelor's degree in Engineering, Information Systems, Computer Science, or related field with 2+ years of Systems Engineering or related work experience, or a Master's degree with 1+ year of experience, or a PhD in a related field. Qualcomm is an equal opportunity employer committed to providing accessible processes for individuals with disabilities. Individuals seeking accommodation during the application/hiring process can contact Qualcomm for support. The company expects its employees to adhere to all applicable policies and procedures, including security requirements regarding protection of confidential information. Please note that Qualcomm does not accept unsolicited resumes or applications from agencies. Staffing and recruiting agencies are not authorized to submit profiles, applications, or resumes on behalf of individuals. For more information about this role, please contact Qualcomm Careers.,

Job Posting TitleSR. DATA SCIENTIST Band/Level5-2-C Education ExperienceBachelors Degree (High School +4 years) Employment Experience5-7 years At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world. Job Overview Solves complex problems and help stakeholders make data- driven decisions by leveraging quantitative methods, such as machine learning. It often involves synthesizing large volume of information and extracting signals from data in a programmatic way. Roles & Responsibilities Key Responsibilities Design, train, and evaluate supervised & unsupervised models (regression, classification, clustering, uplift). Apply automated hyperparameter optimization (Optuna, HyperOpt) and interpretability techniques (SHAP, LIME). Perform deep exploratory data analysis (EDA) to uncover patterns & anomalies. Engineer predictive features from structured, semistructured, and unstructured data; manage feature stores (Feast). Ensure data quality through rigorous validation and automated checks. Build hierarchical, intermittent, and multiseasonal forecasts for thousands of SKUs. Implement traditional (ARIMA, ETS, Prophet) and deeplearning (RNN/LSTM, TemporalFusion Transformer) approaches. Reconcile forecasts across product/category hierarchies; quantify accuracy (MAPE, WAPE) and bias. Establish model tracking & registry (MLflow, SageMaker Model Registry). Develop CI/CD pipelines for automated retraining, validation, and deployment (Airflow, Kubeflow, GitHub Actions). Monitor data & concept drift; trigger retuning or rollback as needed. Design and analyze A/B tests, causal inference studies, and Bayesian experiments. Provide statisticallygrounded insights and recommendations to stakeholders. Translate business objectives into datadriven solutions; present findings to exec & nontech audiences. Mentor junior data scientists, review code/notebooks, and champion best practices. Desired Candidate Minimum Qualifications M.S. in Statistics (preferred) or related field such as Applied Mathematics, Computer Science, Data Science. 5+ years building and deploying ML models in production. Expertlevel proficiency in Python (Pandas, NumPy, SciPy, scikitlearn), SQL, and Git. Demonstrated success delivering largescale demandforecasting or timeseries solutions. Handson experience with MLOps tools (MLflow, Kubeflow, SageMaker, Airflow) for model tracking and automated retraining. Solid grounding in statistical inference, hypothesis testing, and experimental design. Preferred / NicetoHave Experience in supplychain, retail, or manufacturing domains with highgranularity SKU data. Familiarity with distributed data frameworks (Spark, Dask) and cloud data warehouses (BigQuery, Snowflake). Knowledge of deeplearning libraries (PyTorch, TensorFlow) and probabilistic programming (PyMC, Stan). Strong datavisualization skills (Plotly, Dash, Tableau) for storytelling and insight communication. Competencies ABOUT TE CONNECTIVITY TE Connectivity plc (NYSETEL) is a global industrial technology leader creating a safer, sustainable, productive, and connected future. Our broad range of connectivity and sensor solutions enable the distribution of power, signal and data to advance next-generation transportation, energy networks, automated factories, data centers, medical technology and more. With more than 85,000 employees, including 9,000 engineers, working alongside customers in approximately 130 countries, TE ensures that EVERY CONNECTION COUNTS. Learn more atwww.te.com and onLinkedIn , Facebook , WeChat, Instagram and X (formerly Twitter). WHAT TE CONNECTIVITY OFFERS: We are pleased to offer you an exciting total package that can also be flexibly adapted to changing life situations - the well-being of our employees is our top priority! Competitive Salary Package Performance-Based Bonus Plans Health and Wellness Incentives Employee Stock Purchase Program Community Outreach Programs / Charity Events IMPORTANT NOTICE REGARDING RECRUITMENT FRAUD TE Connectivity has become aware of fraudulent recruitment activities being conducted by individuals or organizations falsely claiming to represent TE Connectivity. Please be advised that TE Connectivity never requests payment or fees from job applicants at any stage of the recruitment process. All legitimate job openings are posted exclusively on our official careers website at te.com/careers, and all email communications from our recruitment team will come only from actual email addresses ending in @te.com . If you receive any suspicious communications, we strongly advise you not to engage or provide any personal information, and to report the incident to your local authorities. Across our global sites and business units, we put together packages of benefits that are either supported by TE itself or provided by external service providers. In principle, the benefits offered can vary from site to site.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Software Engineer II We are the global technology company behind the world’s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. The Mastercard Launch program is aimed at early career talent, to help you develop skills and gain cross-functional work experience. Over a period of 18 months, Launch participants will be assigned to a business unit, learn and develop skills, and gain valuable on the job experience. Mastercard has over 2 billion payment cards issued by 25,000+ banks across 190+ countries and territories, amassing over 10 petabytes of data. Millions of transactions are flowing to Mastercard in real-time providing an ideal environment to apply and leverage AI at scale. The AI team is responsible for building and deploying innovative AI solutions for all divisions within Mastercard securing a competitive advantage. Our objectives include achieving operational efficiency, improving customer experience, and ensuring robust value propositions of our core products (Credit, Debit, Prepaid) and services (recommendation engine, anti-money laundering, fraud risk management, cybersecurity) Role Gather relevant information to define the business problem Creative thinker capable of linking AI methodologies to identified business challenges Develop AI/ML applications leveraging the latest industry and academic advancements Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda All About You : Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Concentration in Computer Science Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Manager Data Scientist AI Garage is responsible for establishing Mastercard as an AI powerhouse. AI will be leveraged and implemented at scale within Mastercard providing a foundational, competitive advantage for the future. All internal processes, all products and services will be enabled by AI continuously advancing our value proposition, consumer experience, and efficiency. Opportunity Join Mastercard's AI Garage @ Gurgaon, a newly created strategic business unit executing on identified use cases for product optimization and operational efficiency securing Mastercard's competitive advantage through all things AI. The AI professional will be responsible for the creative application and execution of AI use cases, working collaboratively with other AI professionals and business stakeholders to effectively drive the AI mandate. Role Ensure all AI solution development is in line with industry standards for data management and privacy compliance including the collection, use, storage, access, retention, output, reporting, and quality of data at Mastercard Adopt a pragmatic approach to AI, capable of articulating complex technical requirements in a manner this is simple and relevant to stakeholder use cases Gather relevant information to define the business problem interfacing with global stakeholders Creative thinker capable of linking AI methodologies to identified business challenges Identify commonalities amongst use cases enabling a microservice approach to scaling AI at Mastercard, building reusable, multi-purpose models Develop AI/ML solutions/applications leveraging the latest industry and academic advancements Leverage open and closed source technologies to solve business problems Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda Partner with technical teams to implement developed solutions/applications in production environment Support a learning culture continuously advancing AI capabilities Experience All About You Experience in the Data Sciences field with a focus on AI strategy and execution and developing solutions from scratch Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Exposure or experience using collaboration tools such as: Confluence (Documentation) Bitbucket/Stash (Code Sharing) Shared Folders (File Sharing) ALM (Project Management) Knowledge of payments industry a plus Experience with SAFe (Scaled Agile Framework) process is a plus Effectiveness Effective at managing and validating assumptions with key stakeholders in compressed timeframes, without hampering development momentum Capable of navigating a complex organization in a relentless pursuit of answers and clarity Enthusiasm for Data Sciences embracing the creative application of AI techniques to improve an organization's effectiveness Ability to understand technical system architecture and overarching function along with interdependency elements, as well as anticipate challenges for immediate remediation Ability to unpack complex problems into addressable segments and evaluate AI methods most applicable to addressing the segment Incredible attention to detail and focus instilling confidence without qualification in developed solutions Core Capabilities Strong written and oral communication skills Strong project management skills Concentration in Computer Science Some international travel required #AI1 Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Senior Data Scientist We are the global technology company behind the world’s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. The Mastercard Launch program is aimed at early career talent, to help you develop skills and gain cross-functional work experience. Over a period of 18 months, Launch participants will be assigned to a business unit, learn and develop skills, and gain valuable on the job experience. Mastercard has over 2 billion payment cards issued by 25,000+ banks across 190+ countries and territories, amassing over 10 petabytes of data. Millions of transactions are flowing to Mastercard in real-time providing an ideal environment to apply and leverage AI at scale. The AI team is responsible for building and deploying innovative AI solutions for all divisions within Mastercard securing a competitive advantage. Our objectives include achieving operational efficiency, improving customer experience, and ensuring robust value propositions of our core products (Credit, Debit, Prepaid) and services (recommendation engine, anti-money laundering, fraud risk management, cybersecurity) Role Gather relevant information to define the business problem Creative thinker capable of linking AI methodologies to identified business challenges Develop AI/ML applications leveraging the latest industry and academic advancements Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda All About You : Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Concentration in Computer Science Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Senior Data Scientist AI Garage is responsible for establishing Mastercard as an AI powerhouse. AI will be leveraged and implemented at scale within Mastercard providing a foundational, competitive advantage for the future. All internal processes, all products and services will be enabled by AI continuously advancing our value proposition, consumer experience, and efficiency. Opportunity Join Mastercard's AI Garage @ Gurgaon, a newly created strategic business unit executing on identified use cases for product optimization and operational efficiency securing Mastercard's competitive advantage through all things AI. The AI professional will be responsible for the creative application and execution of AI use cases, working collaboratively with other AI professionals and business stakeholders to effectively drive the AI mandate. Role Ensure all AI solution development is in line with industry standards for data management and privacy compliance including the collection, use, storage, access, retention, output, reporting, and quality of data at Mastercard Adopt a pragmatic approach to AI, capable of articulating complex technical requirements in a manner this is simple and relevant to stakeholder use cases Gather relevant information to define the business problem interfacing with global stakeholders Creative thinker capable of linking AI methodologies to identified business challenges Identify commonalities amongst use cases enabling a microservice approach to scaling AI at Mastercard, building reusable, multi-purpose models Develop AI/ML solutions/applications leveraging the latest industry and academic advancements Leverage open and closed source technologies to solve business problems Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda Partner with technical teams to implement developed solutions/applications in production environment Support a learning culture continuously advancing AI capabilities Experience All About You Experience in the Data Sciences field with a focus on AI strategy and execution and developing solutions from scratch Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Exposure or experience using collaboration tools such as: Confluence (Documentation) Bitbucket/Stash (Code Sharing) Shared Folders (File Sharing) ALM (Project Management) Knowledge of payments industry a plus Experience with SAFe (Scaled Agile Framework) process is a plus Effectiveness Effective at managing and validating assumptions with key stakeholders in compressed timeframes, without hampering development momentum Capable of navigating a complex organization in a relentless pursuit of answers and clarity Enthusiasm for Data Sciences embracing the creative application of AI techniques to improve an organization's effectiveness Ability to understand technical system architecture and overarching function along with interdependency elements, as well as anticipate challenges for immediate remediation Ability to unpack complex problems into addressable segments and evaluate AI methods most applicable to addressing the segment Incredible attention to detail and focus instilling confidence without qualification in developed solutions Core Capabilities Strong written and oral communication skills Strong project management skills Concentration in Computer Science Some international travel required Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

As a Manager, Behavioral Modeler (Development/Validation) & Researcher Specialist at Genpact, you will be responsible for developing or validating Behavioral Models for banking and financial institutions, focusing on areas such as Financial Crime (Fraud or AML), Marketing Campaigns, and Adjudication models. Your role will involve working closely with the centralized advanced analytics team of banking or financial firms, interacting with various business units, auditors, and model development/validation teams to ensure compliance with Enterprise Modeling Governance standards. Your key responsibilities will include providing analytical support to mitigate risk, assessing data quality for model development, developing machine learning-based models, proposing recommendations to improve monitoring systems, conducting in-depth research on behavioral modeling policies, and contributing to the creation of whitepapers and artifacts. You will be expected to have hands-on experience in developing and validating models, risk management, and applying AI, ML, and Deep Learning techniques using tools such as SAS, Python, and R. The qualifications we seek in you include a Master's degree in a quantitative discipline, experience in statistical modeling, detailed knowledge of data analysis techniques, expertise in SQL, ETL, and strong scripting and automation skills. Additionally, you should possess strong client management, communication, and presentation skills, be self-driven, proactive, and have the ability to work under ambiguity and with minimal supervision. You should also have strong project management experience, the ability to lead projects and teams, and demonstrate expertise in communicating and coordinating across multiple business units. Preferred qualifications/skills include strong networking, negotiation, and influencing skills, as well as prior experience in financial crime and machine learning models. If you are a forward-thinking individual with a hunger for learning and a passion for turning innovative ideas into reality, we invite you to apply for this challenging and rewarding role at Genpact. Please note that this is a full-time position based in India-Kolkata, and the job posting was on Oct 7, 2024.,

Job Description: We're seeking a skilled and motivated ML/AI Engineer to join our team and drive end-to-end AI development for cutting-edge healthcare prediction models. As part of our AI delivery team you will be working on designing, developing, and deploying ML models to solve complex business challenges. Key Responsibilities: Design, develop, and deploy scalable machine learning models and AI solutions. Collaborate with engineers and product managers to understand business requirements and translate them into technical solutions. Analyse and preprocess large datasets for training and testing ML models. Experiment with different ML algorithms and techniques to improve model performance. Skills & Qualifications: Experience: B.Tech with 2-5 years of relevant experience in Machine Learning, AI, or Data Science roles. OR M.Tech, M. Statistics with 2-4 years of relevant experiencein Machine Learning, AI, or Data Science roles. Education: Bachelor's/master's degree in computer science or Statistics or any other relevant engineering / AI course from a Tier 1 or Tier 2 college. Technical Skills: Proficiency in programming languages such asPython & R Strong knowledge of classicalmachine learning algorithms with hands on experience in the following: Supervised (Classification model, regressions models) Unsupervised, (Clustering Algorithms, Autoencoders) Ensemble Models (Stacking, Bagging, Boosting techniques, Random Forest, XGBoost) Experience in data preprocessing, feature engineering, and handling large-scale datasets. Model evaluation techniques like accuracy, precision, recall, F1 score, AUC-ROC for classification, and MAE, MSE, RMSE, R-squared for regression. Explainable AI (XAI) techniques include methods like SHAP values, LIME, feature importance from decision trees, and partial dependence plots. Experience withML frameworkslikeTensorFlow, PyTorch, Scikit-learn,orKeras. Building & deploying Model APIs using framework like Flask, Fast API, Django, TensorFlow Serving etc. Knowledge ofcloud platformslike Azure (preferred), AWS, GCP and experience deploying models in such environments -> changed the wording, added points. Nice to Have: Object Oriented Programming. Familiarity withNLP, ortime seriesanalysis. -> Moving this into Nice to have, not bare min Exposure todeep learningmodels (RNN, LSTM) and working with GPUs.

You will be responsible for building, improving, and extending NLP capabilities to deliver theoretically elegant algorithms and practically efficient solutions to complex problems. As an NLP Engineer, you will research and evaluate different approaches to NLP problems, write well-designed code that produces deliverable results, and ensure that the code scales and can be deployed to production. Additionally, you will design and execute A/B tests through a framework, apply machine learning to language-related problems, and have knowledge of association mining, named entity recognition, and vector representations of textual data. You should have a strong understanding of neural networks such as RNN and LSTM, as well as expertise in Python, data structures, algorithms, and general software development skills. With at least 3 years of work experience in data, you are expected to possess good communication skills, analytical abilities, and problem-solving skills. Being a good team player is essential, and you should have experience leading a technical team, handling POCs, designing solutions, and providing estimates as per requirements.,

Responsibilities: Lead and manage end-to-end data science projects, including project planning, scoping, budgeting, resource allocation, and timeline management. Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders, to define project requirements, deliverables, and milestones. Conduct project kick-off meetings, define project objectives, and establish clear project scopes and deliverables. Develop and maintain project plans, track progress, and provide regular updates to stakeholders, ensuring project milestones are met within the defined timeline. Identify and manage project risks, issues, and dependencies, implementing mitigation strategies and contingency plans as necessary. Coordinate and communicate project activities, ensuring alignment with organizational goals and objectives. Monitor project budget, resource utilization, and expenses, making necessary adjustments to optimize project performance and efficiency. Foster a collaborative and innovative work environment, promoting knowledge sharing and best practices within the data science team. Stay updated with industry trends, emerging technologies, and advancements in data science methodologies, and propose relevant process improvements or tool adoption. Provide leadership and mentorship to the data science team, facilitating their professional growth and development. Requirements: Bachelor's degree in computer science, Data Science, Statistics, or a related field. A master's degree is preferred. Proven experience (5+ years) in managing data science projects, preferably in a fast-paced and dynamic environment. Strong understanding of data science concepts, machine learning algorithms, and statistical modeling techniques. Proficient in project management methodologies, tools, and techniques. Excellent organizational and time management skills, with the ability to prioritize tasks and meet deadlines. Exceptional problem-solving and analytical abilities, with keen attention to detail. Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and present complex concepts to non-technical stakeholders. Strong leadership skills, with the ability to motivate and inspire team members. Experience with data visualization tools, programming languages (e. g., Python, R), and big data technologies is a plus. Whatspp - 9886683329

Job Description - Jr. Data Scientist Experience: 0-1 year | Employment Type: Full-time Overview We are looking for a motivated Data Scientist with foundational data science expertise. This position is ideal for recent graduates or early-career professionals eager to work with real-world data, applying both standard and advanced preprocessing and modeling techniques in a collaborative environment. PLEASE NOTE: Mandatory: Email your CV to careers@solvusai.com with the subject line: “Job ID 202507-DS01: ” This is a full-time role with a hybrid work model Students currently pursuing a degree should not apply A strong foundation and clear understanding of data science concepts is essential Key Responsibilities 1. Data Ingestion & Preparation Extract and manipulate data using SQL and Python (pandas) Import and clean both structured & unstructured datasets 2. Data Preprocessing & Feature Engineering Handle missing values, outliers, and duplicates using statistical and ML techniques Apply noise reduction, data integration, and transformation (e.g., scaling, encoding) Perform dimensionality reduction (e.g., PCA) and ensure quality through data validation 3. Model Building & Evaluation Develop machine learning models (e.g., Linear Regression, Random Forest, XGBoost, ARIMA, LSTM) for varied problem types Tune hyperparameters using cross-validation and assess models using standard metrics (accuracy, RMSE, F1-score, etc.) 4. Visualization & Insight Generation Build dashboards and visualizations using tools like Matplotlib, Seaborn, Plotly, or Tableau Conduct statistical analysis to derive actionable business insights and present findings clearly 5. Team Collaboration Work closely with cross-functional teams (data engineers, analysts, business units) to align deliverables with organizational goals Participate in agile discussions and contribute to iterative development Required Skills Bachelors or Masters in Data Science, Computer Science, Statistics, or related field Proficiency in Python or R Strong SQL skills for data extraction/manipulation from relational databases Experience handling CSV/Excel data ingestion; advanced data cleaning techniques Understanding and implementation of various machine learning models (e.g., Linear Regression, Decision Tree, Random Forest, XGBoost, ARIMA, LSTM, SVM, K-Means) and their practical applications Ability to evaluate model performance using appropriate metrics: accuracy, precision, recall, F1-score, RMSE, MAE, ROC-AUC, etc Experience with feature scaling and categorical variable encoding Data visualization using Matplotlib, Seaborn, Plotly, or Tableau Analytical thinking, problem-solving, teamwork, and clear communication Ready to make an impact by transforming data into meaningful insights? Apply now!

As a Senior Specialist in Software Development (Artificial Intelligence) at Accelya, you will lead the design, development, and implementation of AI and machine learning solutions to tackle complex business challenges. Your expertise in AI algorithms, model development, and software engineering best practices will be crucial in working with cross-functional teams to deliver intelligent systems that optimize business operations and decision-making. Your responsibilities will include designing and developing AI-driven applications and platforms using machine learning, deep learning, and NLP techniques. You will lead the implementation of advanced algorithms for supervised and unsupervised learning, reinforcement learning, and computer vision. Additionally, you will develop scalable AI models, integrate them into software applications, and build APIs and microservices for deployment in cloud environments or on-premise systems. Collaboration with data scientists and data engineers will be essential in gathering, preprocessing, and analyzing large datasets. You will also implement feature engineering techniques to enhance the accuracy and performance of machine learning models. Regular evaluation of AI models using performance metrics and fine-tuning them for optimal accuracy will be part of your role. Furthermore, you will collaborate with business stakeholders to identify AI adoption opportunities, provide technical leadership and mentorship to junior team members, and stay updated with the latest AI trends and research to introduce innovative techniques to the team. Ensuring ethical compliance, security, and continuous improvement of AI systems will also be key aspects of your role. You should hold a Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or a related field, along with at least 5 years of experience in software development focusing on AI and machine learning. Proficiency in AI frameworks and libraries, programming languages such as Python, R, or Java, and cloud platforms for deploying AI models is required. Familiarity with Agile methodologies, data structures, and databases is essential. Preferred qualifications include a Master's or PhD in Artificial Intelligence or Machine Learning, experience with NLP techniques and computer vision technologies, and certifications in AI/ML or cloud platforms. Accelya is looking for individuals who are passionate about shaping the future of the air transport industry through innovative AI solutions. If you are ready to contribute your expertise and drive continuous improvement in AI systems, this role offers you the opportunity to make a significant impact in the industry.,

#GenerativeAI Experts ready for AI race, this is for you! Announcing Hexaware conducting Walkin Drive for AI Engineer and Lead Data Scientist (GenAI)-Noida Location-3rd Aug 2025(Sunday) Interested candidates share your CV at umaparvathyc@hexaware.com Open Positions: AI Engineer/Lead Data Scientist (GenAI) AI Engineer Experience- 3+years Lead Data Scientist (GenAI) Experience- 7+years Notice Period- 15 days/30days Max (who serving Notice Period) Walkin Drive Location- Noida Date of drive- 3rd Aug 2025(Sunday) Must have Experience: LLM, Advance RAG, NLP, transformer model, LangChain Technical Skill: 1. Strong Experience in Data Scientist (GENAI) 2. Proficiency with Generative AI models like GANs, VAEs, and transformers 3. Expertise with cloud platforms (AWS, Azure, Google Cloud) for deploying AI models 4. Strong Python Fast API experience, SDA based implementations for all the APIs 5. Knowledge of Agentic AI concepts and applications

As an experienced professional in the field, you will be expected to demonstrate proficiency in a range of key areas. Your expertise should include statistical modeling, traditional machine learning, and Gen AI. Moreover, you should possess knowledge of various deep learning models such as LSTM, N-BEATS, CNN, and RNN. In addition, you are required to be well-versed in optimization techniques including linear programming and mix integer programming, along with familiarity with optimization tools like Opensolver and Gurobi. Your role will involve working with Data Bricks and Snowflake, engaging with ML/DL models, and interacting directly with business stakeholders and customer FTEs. Therefore, strong technological skills and effective communication are essential for success in this position. The must-have skills for this role include Time Series Modelling (LSTN, CNN, N-BEATS, RNN), proficiency in Data Bricks, statistical knowledge, Python programming, optimization expertise, as well as experience with Opensolver and Gurobi. Additionally, it would be beneficial to have experience with GenAI and Snowflake. The ideal candidate should have a minimum of 8-10 years of experience in the field, showcasing a deep understanding of the mandatory skills required for this role. Your ability to leverage your expertise in time series modeling, data manipulation, statistical analysis, and optimization tools will be instrumental in driving successful outcomes for the organization.,

As a Senior Generative AI Engineer, your primary role will involve conducting original research on generative AI models. You will focus on exploring model architecture, training methodologies, fine-tuning techniques, and evaluation strategies. It is essential to maintain a strong publication record in esteemed conferences and journals, demonstrating your valuable contributions to the fields of Natural Language Processing (NLP), Deep Learning (DL), and Machine Learning (ML). In addition, you will be responsible for designing and experimenting with multimodal generative models that incorporate various data types such as text, images, and other modalities to enhance AI capabilities. Your expertise will be crucial in developing autonomous AI systems that exhibit agentic behavior, enabling them to make independent decisions and adapt to dynamic environments. Leading the design, development, and implementation of generative AI models and systems will be a key aspect of your role. This involves selecting suitable models, training them on extensive datasets, fine-tuning hyperparameters, and optimizing overall performance. It is imperative to have a deep understanding of the problem domain to ensure effective model development and implementation. Furthermore, you will be tasked with optimizing generative AI algorithms to enhance their efficiency, scalability, and computational performance. Techniques such as parallelization, distributed computing, and hardware acceleration will be utilized to maximize the capabilities of modern computing architectures. Managing large datasets through data preprocessing and feature engineering to extract critical information for generative AI models will also be a crucial aspect of your responsibilities. Your role will also involve evaluating the performance of generative AI models using relevant metrics and validation techniques. By conducting experiments, analyzing results, and iteratively refining models, you will work towards achieving desired performance benchmarks. Providing technical leadership and mentorship to junior team members, guiding their development in generative AI, will also be part of your responsibilities. Documenting research findings, model architectures, methodologies, and experimental results thoroughly is essential. You will prepare technical reports, presentations, and whitepapers to effectively communicate insights and findings to stakeholders. Additionally, staying updated on the latest advancements in generative AI by reading research papers, attending conferences, and engaging with relevant communities is crucial to foster a culture of learning and innovation within the team. Mandatory technical skills for this role include strong programming abilities in Python and familiarity with frameworks like PyTorch or TensorFlow. In-depth knowledge of Deep Learning concepts such as CNN, RNN, LSTM, Transformers LLMs (BERT, GEPT, etc.), and NLP algorithms is required. Experience with frameworks like Langgraph, CrewAI, or Autogen for developing, deploying, and evaluating AI agents is also essential. Preferred technical skills include expertise in cloud computing, particularly with Google/AWS/Azure Cloud Platform, and understanding Data Analytics Services offered by these platforms. Hands-on experience with ML platforms like GCP: Vertex AI, Azure: AI Foundry, or AWS SageMaker is desirable. Strong communication skills, the ability to work independently with minimal supervision, and a proactive approach to escalate when necessary are also key attributes for this role. If you have a Master's or PhD degree in Computer Science and 6 to 8 years of experience with a strong record of publications in top-tier conferences and journals, this role could be a great fit for you. Preference will be given to research scholars from esteemed institutions like IITs, NITs, and IIITs.,

Job Summary: The Specialist - Software Development (Artificial Intelligence) leads the design, development, and implementation of AI and machine learning solutions that address complex business challenges. This role requires expertise in AI algorithms, model development, and software engineering best practices. The individual will work closely with cross-functional teams to deliver intelligent systems that enhance business operations and decision-making. Key Responsibilities: • AI Solution Design & Development: o Lead the development of AI-driven applications and platforms using machine learning, deep learning, and NLP techniques. o Design, train, and optimize machine learning models using frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn. o Implement advanced algorithms for supervised and unsupervised learning, reinforcement learning, and computer vision. • Software Development & Integration: o Develop scalable AI models and integrate them into software applications using languages such as Python, R, or Java. o Build APIs and microservices to enable the deployment of AI models in cloud environments or on-premise systems. o Ensure that AI models are integrated with back-end systems, databases, and other business applications. • Data Management & Preprocessing: o Collaborate with data scientists and data engineers to gather, preprocess, and analyze large datasets. o Develop data pipelines to ensure the continuous availability of clean, structured data for model training and evaluation. o Implement feature engineering techniques to enhance the accuracy and performance of machine learning models. • AI Model Evaluation & Optimization: o Regularly evaluate AI models using performance metrics (e.g., precision, recall, F1 score) and fine-tune them to improve accuracy. o Perform hyperparameter tuning and cross-validation to ensure robust model performance. o Implement methods for model explainability and transparency (e.g., LIME, SHAP) to ensure trustworthiness in AI decisions. • AI Strategy & Leadership: o Collaborate with business stakeholders to identify opportunities for AI adoption and develop project roadmaps. o Provide technical leadership and mentorship to junior AI developers and data scientists, ensuring adherence to best practices in AI development. o Stay current with AI trends and research, introducing innovative techniques and tools to the team. • Security & Ethical Considerations: o Ensure AI models comply with ethical guidelines, including fairness, accountability, and transparency. o Implement security measures to protect sensitive data and AI models from vulnerabilities and attacks. o Monitor the performance of AI systems in production, ensuring they operate within ethical and legal boundaries. • Collaboration & Cross-Functional Support: o Collaborate with DevOps teams to ensure AI models are deployed efficiently in production environments. o Work closely with product managers, business analysts, and stakeholders to understand requirements and align AI solutions with business needs. o Participate in Agile ceremonies, including sprint planning and retrospectives, to ensure timely delivery of AI projects. • Continuous Improvement & Research: o Conduct research and stay updated with the latest developments in AI and machine learning technologies. o Evaluate new tools, libraries, and methodologies to improve the efficiency and accuracy of AI model development. o Drive continuous improvement initiatives to enhance the scalability and robustness of AI systems. Required Skills & Qualifications: • Bachelor’s degree in computer science, Data Science, Artificial Intelligence, or related field. • 5+ years of experience in software development with a strong focus on AI and machine learning. • Expertise in AI frameworks and libraries (e.g., TensorFlow, PyTorch, Keras, Scikit-learn). • Proficiency in programming languages such as Python, R, or Java, and familiarity with AI-related tools (e.g., Jupyter Notebooks, MLflow). • Strong knowledge of data science and machine learning algorithms, including regression, classification, clustering, and deep learning models. • Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) for deploying AI models and managing data pipelines. • Strong understanding of data structures, databases, and large-scale data processing technologies (e.g., Hadoop, Spark). • Familiarity with Agile development methodologies and version control systems (Git). Preferred Qualifications: • Master’s or PhD in Artificial Intelligence, Machine Learning, or related field. • Experience with natural language processing (NLP) techniques (e.g., BERT, GPT, LSTM, Transformer models). • Knowledge of computer vision technologies (e.g., CNNs, OpenCV). • Familiarity with edge computing and deploying AI models on IoT devices. • Certification in AI/ML or cloud platforms (e.g., AWS Certified Machine Learning, Google Professional Data Engineer).

Job Title: Data Science Trainer Company: HERE AND NOW Artificial Intelligence Research Institute Location: HERE AND NOW AI, Salem About Us At the HERE AND NOW Artificial Intelligence Research Institute, we are at the forefront of AI innovation. Our mission is to empower the next generation of AI professionals through comprehensive education, innovative AI applications, and groundbreaking research. We are looking for a passionate and experienced Data Science Trainer to join our team and help us achieve our goals. Job Description Title: Data Science Trainer Location: Salem, Tamil Nadu Job Type: Part-Time / Contract Date of Training: 28.07.2025 Experience: Minimum 2 years in Data Science, Machine Learning, or AI domain Industry: IT Training / EdTech / Technical Education About the Role We are hiring a dedicated and skilled Data Science Trainer in Salem to deliver hands-on training in Python for Data Science, Machine Learning, Big Data Analytics, and Deep Learning. If you're passionate about teaching and mentoring aspiring data scientists, this is your chance to contribute to the AI revolution. Responsibilities Deliver interactive classroom or virtual sessions covering: Data Science: Python, Pandas, NumPy, Matplotlib, Statistics, Machine Learning (Supervised & Unsupervised), Model Evaluation, Real-world Projects. Big Data Analytics: Hadoop Ecosystem (HDFS, MapReduce, Hive, Pig, Sqoop, Flume), Apache Spark, Spark SQL, Spark MLlib, NoSQL basics (MongoDB/Cassandra). Deep Learning: Neural Networks, CNN, RNN, LSTM, GANs, using TensorFlow, Keras, and Google Colab. Design and customize curriculum for beginner to intermediate learners. Facilitate real-time mini-projects, assignments, and model-building activities. Evaluate student progress and provide mentorship. Collaborate with academic and placement teams to ensure outcomes align with industry needs. Required Skills Strong understanding of Python and ML libraries (Pandas, Scikit-learn, Matplotlib, Seaborn). Proficiency in Big Data tools: Hadoop, Spark, Hive. Familiarity with Deep Learning frameworks: TensorFlow, Keras. Understanding of statistical concepts and machine learning algorithms. Excellent communication, presentation, and mentoring skills. Willingness to conduct sessions at our Salem center. Preferred Qualifications B.E./B.Tech/MCA/M.Sc in Computer Science, Data Science, or related fields. Training experience in Data Science, Big Data, or AI. Certification in Data Science/Machine Learning/Big Data preferred. Exposure to cloud tools (AWS/GCP) and BI tools (Power BI/Tableau) is a plus. Benefits Competitive salary + performance-based incentives Opportunity to be part of a growing AI research and training community Certificate of contribution for each training batch Job Types: Part-time, Fresher, Contractual / Temporary, Freelance Benefits: Flexible schedule Food provided Paid sick time Schedule: Day shift Supplemental Pay: Commission pay Performance bonus Shift allowance Experience: total work: 2 years (Required) Work Location: In person

Responsibilities Architect and build real-time feature pipelines and model training workflows. Design, train, validate, and deploy RUL predictors, anomaly detectors, and LP-based grid solvers. Implement MLOps best practices: MLflow/Kubeflow pipelines, model registry, canary deployments. Collaborate on explainability modules (SHAP, LIME) and drift-detection alerts. Optimize GPU utilization; automate retraining schedules and performance monitoring. Skills & Experience 3+ years in ML engineering or data science roles; production-grade ML deployments. Expertise in time-series modeling: LSTM, GRU, isolation forest, ensemble methods. Strong Python skills; frameworks: TensorFlow, PyTorch, Scikit-Learn. Experience with Kubernetes-based MLOps: Kubeflow, KServe, MLflow. Proficiency tuning and deploying on NVIDIA GPUs (H100, H200). Nice-to-Have Domain experience in predictive maintenance, grid optimization, or IIoT. Familiar with feature-store design (TimescaleDB, Feast) and Spark-on-GPU. Knowledge of explainability libraries and regulatory compliance for AI.