142 Lstm Jobs

Role: Senior Data Scientist Responsibilities: Partner with Internal and External stakeholders and contribute to building Formal Models with Pipelines Have the eagle Eye View of the whole system and provide innovative solutions Work with UI/UX Teams to provide an end-to-end solution Qualification: BE, Tech, MCA, MSc, MTech, MBA AI or ML certificate from institutes like IISC, IIT etc is a plus Technical Skills: Languages - Python Database - MSSQL, Oracle Cloud - Azure Version control - Github Experience Required: 5+ years in the industry Experience in building AI predictive and Prescriptive Analysis Experience in transformer models like BERT, ROBERTA, LSTM, RNN is mandatory Familiarity with various generative AI models, such as generative adversarial networks (GANs) and LLAMA is preferred is a plus Experience in Integrating models to .NET or Java application is a plus

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY- Assurance – Senior - Digital Position Details As part of EY GDS Assurance Digital, you will be responsible for implementing innovative ideas through AI research to develop high growth & impactful products. You will be helping EY’s sector and service line professionals by developing analytics enabled solutions, integrating data science activities with business relevant aspects to gain insight from data. You will work with multi-disciplinary teams across the entire region to support global clients. This is a core full-time AI developer role, responsible for creating innovative solutions by applying AI based techniques for business problems. As our in-house senior AI engineer, your expertise and skills will be vital in our ability to steer one of our Innovation agenda. Responsibilities Convert business problem into analytical problem and devise a solution approach. Clean, aggregate, analyze and interpret the data to derive business insights from it. Own the AI/ML implementation process: Model Design, Feature Planning, Testing, Production Setup, Monitoring, and release management. Work closely with the Solution Architects in deployment of the AI POC’s and scaling up to production level applications. Should have solid background in Python and has deployed on open-source models- Work on data extraction techniques from complex PDF/Word Doc/Forms- entities extraction, table extraction, information comparison. Key Requirements/Skills & Qualification: Excellent academic background, including at a minimum a bachelor or a master’s degree in data science, Business Analytics, Statistics, Engineering, Operational Research, or other related field with strong focus on modern data architectures, processes, and environments. Solid background in Python with excellent coding skills. 4+ years of core data science experience in one or more below areas: Machine Learning (Regression, Classification, Decision Trees, Random Forests, Timeseries Forecasting and Clustering) Understanding and usage of Large Language Models like Open AI models like ChatGPT, GPT4, frameworks like LangChain and Llama Index. Good understanding of open source LLM framework like Mistral, Llama, etc. and fine tuning on custom datasets. Deep Learning (DNN, RNN, LSTM, Encoder-Decoder Models) Natural Language Processing- Text Summarization, Aspect Mining, Question Answering, Text Classification, NER, Language Translation, NLG, Sentiment Analysis, Sentence Computer Vision- Image Classification, Object Detection, Tracking etc. SQL/NoSQL Databases and its manipulation components Working knowledge of API Deployment (Flask/FastAPI/Azure Function Apps) and webapps creation, Docker, Kubernetes. Additional skills requirements: Excellent written, oral, presentation and facilitation skills Ability to coordinate multiple projects and initiatives simultaneously through effective prioritization, organization, flexibility, and self-discipline. Must have demonstrated project management experience. Knowledge of firm’s reporting tools and processes. Proactive, organized, and self-sufficient with ability to priorities and multitask. Analyses complex or unusual problems and can deliver insightful and pragmatic solutions. Ability to quickly and easily create/ gather/ analyze data from a variety of sources. A robust and resilient disposition able to encourage discipline in team behaviors What We Look For A Team of people with commercial acumen, technical experience, and enthusiasm to learn new things in this fast-moving environment An opportunity to be a part of market-leading, multi-disciplinary team of 7200 + professionals, in the only integrated global assurance business worldwide. Opportunities to work with EY GDS Assurance practices globally with leading businesses across a range of industries What Working At EY Offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY- Assurance – Senior - Digital Position Details As part of EY GDS Assurance Digital, you will be responsible for implementing innovative ideas through AI research to develop high growth & impactful products. You will be helping EY’s sector and service line professionals by developing analytics enabled solutions, integrating data science activities with business relevant aspects to gain insight from data. You will work with multi-disciplinary teams across the entire region to support global clients. This is a core full-time AI developer role, responsible for creating innovative solutions by applying AI based techniques for business problems. As our in-house senior AI engineer, your expertise and skills will be vital in our ability to steer one of our Innovation agenda. Responsibilities Convert business problem into analytical problem and devise a solution approach. Clean, aggregate, analyze and interpret the data to derive business insights from it. Own the AI/ML implementation process: Model Design, Feature Planning, Testing, Production Setup, Monitoring, and release management. Work closely with the Solution Architects in deployment of the AI POC’s and scaling up to production level applications. Should have solid background in Python and has deployed on open-source models- Work on data extraction techniques from complex PDF/Word Doc/Forms- entities extraction, table extraction, information comparison. Key Requirements/Skills & Qualification: Excellent academic background, including at a minimum a bachelor or a master’s degree in data science, Business Analytics, Statistics, Engineering, Operational Research, or other related field with strong focus on modern data architectures, processes, and environments. Solid background in Python with excellent coding skills. 4+ years of core data science experience in one or more below areas: Machine Learning (Regression, Classification, Decision Trees, Random Forests, Timeseries Forecasting and Clustering) Understanding and usage of Large Language Models like Open AI models like ChatGPT, GPT4, frameworks like LangChain and Llama Index. Good understanding of open source LLM framework like Mistral, Llama, etc. and fine tuning on custom datasets. Deep Learning (DNN, RNN, LSTM, Encoder-Decoder Models) Natural Language Processing- Text Summarization, Aspect Mining, Question Answering, Text Classification, NER, Language Translation, NLG, Sentiment Analysis, Sentence Computer Vision- Image Classification, Object Detection, Tracking etc. SQL/NoSQL Databases and its manipulation components Working knowledge of API Deployment (Flask/FastAPI/Azure Function Apps) and webapps creation, Docker, Kubernetes. Additional skills requirements: Excellent written, oral, presentation and facilitation skills Ability to coordinate multiple projects and initiatives simultaneously through effective prioritization, organization, flexibility, and self-discipline. Must have demonstrated project management experience. Knowledge of firm’s reporting tools and processes. Proactive, organized, and self-sufficient with ability to priorities and multitask. Analyses complex or unusual problems and can deliver insightful and pragmatic solutions. Ability to quickly and easily create/ gather/ analyze data from a variety of sources. A robust and resilient disposition able to encourage discipline in team behaviors What We Look For A Team of people with commercial acumen, technical experience, and enthusiasm to learn new things in this fast-moving environment An opportunity to be a part of market-leading, multi-disciplinary team of 7200 + professionals, in the only integrated global assurance business worldwide. Opportunities to work with EY GDS Assurance practices globally with leading businesses across a range of industries What Working At EY Offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

When you join Verizon You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife. What You’ll Be Doing... As a DMTS (AI Science) you will own and drive end to end solutions for Cognitive and Gen AI driven use cases. Working on designing and building scalable cognitive and generative AI solutions to meet the needs of given Business engagement. Providing technical thought leadership on model architecture, delivery, monitoring, measurement and model lifecycle best practices. Working in collaborative environment with global teams to drive solutioning of business problems. Developing end to end analytical solutions, and articulating insights to leadership. Provide data-driven recommendations to business by clearly articulating complex modeling concepts through generation and delivery of presentations. Analyzing and model both structured and unstructured data from a number of distributed client and publicly available sources. Assisting with the mentorship and development of Junior members. Drive team towards solutions. Assisting in growing data science practice in Verizon, by meeting business goals through client prospecting, responding to model POC, identifying and closing opportunities within identified Insights, writing white papers, exploring new tools and defining best practices. What We’re Looking For... You have strong ML/NLP/GenAI skills and are eager to work in a collaborative environment with global teams to drive NLP/GenAI application in business problems. You work independently and are always willing to learn new technologies. You thrive in a dynamic environment and are able to interact with various stakeholders and cross functional teams to implement data science driven business solutions. You take pride in your role as a data scientist and evangelist and enjoy adding to the systems, concepts and models that enrich the practice. You enjoy mentoring and empowering the team to expand their technical capabilities. You’ll Need To Have Bachelor’s degree or four or more years of work experience. Six or more years of work experience. Data Scientist and thought leader with experience in implementing production use cases in Gen AI and Cognitive. Ten or more years of hands-on experience on implementation of large-scale NLP Projects and Fine tuning & Evaluation of LLMs for downstream tasks such as text generation, Classification, summarization, question answering, entity extraction etc. Working knowledge of Agentic AI frameworks like LangChain, LangGraph, CrewAI etc. Ability to guide the team to correctly analyze cognitive insights and leverage unstructured conversational data to create transformative, intelligent, context aware and adaptive AI systems. Experience in Machine Learning, Deep Learning model development & deployment from scratch in Python. Working knowledge of NLP frameworks and libraries like NLTK, Spacy, Transformers, Pytorch, Tensorflow, hugging face API's. Working knowledge of various supervised and unsupervised ML algorithms. Should know the various data preprocessing techniques and its impact on algorithm's accuracy, precision and recall. Knowledge & Implementation Experience of Deep Learning i.e Convolutional Neural Nets (CNN), Recursive Neural Nets (RNN) & Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Deep Reinforcement Learning. Experience with RESTful, JSON API services. Working knowledge on Word embeddings, TF-IDF, Tokenization, N-Grams, Stemmers, lemmatization, Part of speech tagging, entity resolution, ontology, lexicology, phonetics, intents, entities, and context. Experience in analyzing Live Chat/call conversation with agents. Expertise in Python, Sql, PySpark, Scala and/or other languages and tools. Understanding of validation framework for generative model output and perspective on future ready systems to scale validation. Familiarity with GPU/CPU architecture and distributed computing and general infra needs to scale Gen AI models Ability to provide technical thought leadership on model architecture, delivery, monitoring, measurement and model lifecycle best practices. Even better if you have one or more of the following: Phd or an advanced degree or specialization in Artificial Intelligence If Verizon and this role sound like a fit for you, we encourage you to apply even if you don’t meet every “even better” qualification listed above. Where you’ll be working In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager. Scheduled Weekly Hours 40 Equal Employment Opportunity Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics.

Primary Skills Time Series Forecasting : Applying models like ARIMA, Prophet, or LSTM for month-on-month estimations Machine Learning : Building and deploying ML models for forecasting and cost optimization Python Programming : For data manipulation, modeling, and automation (Pandas, NumPy, scikit-learn) CDN Domain Knowledge : Understanding content delivery networks, traffic patterns, and cost structures Power BI : Designing dashboards for CDN usage reporting (regional, brand-level, etc.) Data Analysis & Modeling : Statistical analysis, feature engineering, and model evaluation Cost Optimization Techniques : Using ML to model and optimize CDN allocation and expenses SQL : Querying structured data for reporting and model input Secondary Skills These enhance effectiveness and collaboration but are not strictly mandatory: Cloud Platforms : Familiarity with Azure, AWS, or GCP for data storage and compute ETL & Data Wrangling : Preparing and transforming data from multiple sources Version Control : Using Git for code collaboration and tracking Agile Methodologies : Working in sprints, using tools like JIRA or Confluence Communication Skills : Explaining technical insights to non-technical stakeholders Collaboration Tools : Experience with Teams, Slack, or similar platforms This job is provided by Shine.com

Role: Senior Data Scientist Responsibilities: Partner with Internal and External stakeholders and contribute to building Formal Models with Pipelines Have the eagle Eye View of the whole system and provide innovative solutions Work with UI/UX Teams to provide an end-to-end solution Qualification: BE, Tech, MCA, MSc, MTech, MBA AI or ML certificate from institutes like IISC, IIT etc is a plus Technical Skills: Languages – Python Database – MSSQL, Oracle Cloud – Azure Version control - Github Experience Required: 5+ years in the industry Experience in building AI predictive and Prescriptive Analysis Experience in transformer models like BERT, ROBERTA, LSTM, RNN is mandatory Familiarity with various generative AI models, such as generative adversarial networks (GANs) and LLAMA is preferred is a plus Experience in Integrating models to .NET or Java application is a plus

What will your role look like Design AI solutions using both traditional ML and GenAI approaches based on problem needs Lead end-to-end implementation of ML projects including data preparation, model development, deployment, and monitoring Build GenAI-based applications using LLMs, embeddings, and multi-step reasoning frameworks (e.g., LangChain, LangGraph) Conduct research and proof-of-concepts to evaluate emerging GenAI models and techniques Guide and mentor junior engineers; review designs, architecture, and code quality Develop fine-tuned and instruction-tuned LLMs using platforms like Hugging Face, OpenAI, Cohere, etc. Build agentic AI systems involving tool use, memory, and reasoning frameworks Ensure AI models are robust, explainable, and cost-efficient in production Collaborate with stakeholders to understand business goals and translate them into technical solutions Communicate complex AI concepts to both technical and non-technical audiences. This is a strategic role where you will play a key part in shaping our AI offerings, guiding teams, and solving complex problems using both modern and established AI techniques. Why you will love this role Besides a competitive package, an open workspace full of smart and pragmatic team members, with ever-growing opportunities for professional and personal growth Be a part of a learning culture where teamwork and collaboration are encouraged, diversity is valued and excellence, compassion, openness and ownership is rewarded. We would like you to bring along Experienced AI/ML Engineer with a strong background in both traditional Machine Learning and Generative AI. Experience in classical AI/ML and 23 years in GenAI, total 10 years of experience with the ability to design, research, and build scalable AI solutions across domains. 67 years in traditional ML/DL, including regression, classification, clustering, NLP, time series forecasting, and deep learning techniques such as feedforward networks, CNNs, RNNs, LSTMs, GRUs, and attention-based models for structured, unstructured, and sequential data 23 years in Generative AI (LLMs, embeddings, RAG, fine-tuning, prompt engineering) Experience with Python, scikit-learn, TensorFlow, PyTorch, and Hugging Face Transformers Understanding of ML lifecycle: data wrangling, feature engineering, model training, evaluation, and deployment Deep experience with LLMs such as GPT, LLaMA, Mistral, Claude, or Gemini and tools like LangChain, LangGraph, and LLamaIndex Experience building agentic AI solutions (e.g., AutoGPT, ReAct, CrewAI, BabyAGI) Proficiency with vector databases (FAISS, Pinecone, Weaviate, Chroma) and embedding models (OpenAI, Cohere, BGE, etc.) Excellent communication and presentation skills Strong research mindset with the ability to quickly learn and adapt to new GenAI technologies Ability to assess trade-offs between classic and generative AI techniques and recommend the best-fit approach

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager Job Description & Summary At PwC, our people in business application consulting specialise in consulting services for a variety of business applications, helping clients optimise operational efficiency. These individuals analyse client needs, implement software solutions, and provide training and support for seamless integration and utilisation of business applications, enabling clients to achieve their strategic objectives. As a business application consulting generalist at PwC, you will provide consulting services for a wide range of business applications. You will leverage a broad understanding of various software solutions to assist clients in optimising operational efficiency through analysis, implementation, training, and support. *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: 3-10 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: Master of Business Administration, Bachelor of Engineering Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills Data Science Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Analytical Reasoning, Analytical Thinking, Application Software, Business Data Analytics, Business Management, Business Technology, Business Transformation, Coaching and Feedback, Communication, Creativity, Documentation Development, Embracing Change, Emotional Regulation, Empathy, Implementation Research, Implementation Support, Implementing Technology, Inclusion, Intellectual Curiosity, Learning Agility, Optimism, Performance Assessment {+ 21 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

Dear Candidate, We are hiring a Computer Vision Engineer to develop AI-driven solutions for image recognition, object detection, and video analysis. The role requires expertise in deep learning, computer vision algorithms, and real-time processing techniques. Key Responsibilities: Develop and optimize computer vision models using OpenCV, TensorFlow, and PyTorch. Implement object detection, segmentation, and facial recognition algorithms. Process and analyze large-scale image and video datasets. Optimize deep learning models for real-time inference on edge devices. Collaborate with AI and software teams to integrate vision solutions into applications. Required Skills & Qualifications: Computer Vision Frameworks: OpenCV, DLIB, MediaPipe Deep Learning: TensorFlow, PyTorch, Keras Algorithms: CNNs, YOLO, Faster R-CNN, Mask R-CNN Programming: Python, C++, CUDA Edge AI: TensorRT, OpenVINO, NVIDIA Jetson Experience with autonomous systems, OCR, and SLAM is a plus. Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Reddy Delivery Manager Integra Technologies

Greetings from Colan Infotech!! Role - Data Scientist Experience - 3-10 Years Job Location - Chennai/Bangalore Notice Period - Immediate to 30 Days Primary Skills Needed : AI/ML, Tensorflow, Django, Pytorch, NLP, Image processing,Gen AI,LLM Secondary Skills Needed : Keras, OpenCV, Azure or AWS Job Description:- Practical knowledge and working experience on Statistics and Operation Research methods. Practical knowledge and working experience in tools and frameworks like Flask, PySpark, Pytorch, tensorflow, keras, Databricks, OpenCV, Pillow/PIL, streamlit, d3js, dashplotly, neo4j. Good understanding of how to apply predictive and machine learning techniques like regression models, XGBoost, random forest, GBM, Neural Nets, SVM etc. Proficient with NLP techniques like RNN, LSTM and Attention based models and effectively handle readily available stanford, IBM, Azure, Open AI NLP models. Good understanding of SQL from a perspective of how to write efficient queries for pulling the data from database. Hands on experience on any version control tool (github, bitbucket). Experience of deploying ML models into production environment experience (MLOps) in any one of the cloud platforms like Azure and AWS Comprehend business issues and propose valuable business solutions. Design Factual or AI/profound learning models to address business issues. Design Statistical Models/ML/DL models and deploy them for production. Formulate what information is accessible from where and how to augment it. Develop innovative graphs for data comprehension using d3js, dashplotly and neo4j Interested candidates send updated resume to kumudha.r@colanonline.com

#GenerativeAI Experts ready for AI race, this is for you! Announcing Hexaware conducting Walkin Drive for AI Engineer and Lead Data Scientist (GenAI)-Pune Location-12th July 2025(Saturday) 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- Pune Date of drive- 12th July 2025(Saturday) 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

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager Job Description & Summary At PwC, our people in business application consulting specialise in consulting services for a variety of business applications, helping clients optimise operational efficiency. These individuals analyse client needs, implement software solutions, and provide training and support for seamless integration and utilisation of business applications, enabling clients to achieve their strategic objectives. As a business application consulting generalist at PwC, you will provide consulting services for a wide range of business applications. You will leverage a broad understanding of various software solutions to assist clients in optimising operational efficiency through analysis, implementation, training, and support. *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: 3-10 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: Master of Business Administration, Bachelor of Engineering Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills Data Science Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Analytical Reasoning, Analytical Thinking, Application Software, Business Data Analytics, Business Management, Business Technology, Business Transformation, Coaching and Feedback, Communication, Creativity, Documentation Development, Embracing Change, Emotional Regulation, Empathy, Implementation Research, Implementation Support, Implementing Technology, Inclusion, Intellectual Curiosity, Learning Agility, Optimism, Performance Assessment {+ 21 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 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. In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions. 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. Job Description & Summary: -Stakeholder facing role across different functions of the organizations (e.g., Marketing, Finance, Logistics, Procurement, Customer, Supply Chain, HR) to develop analyses that lead to actionable insights that accelerate profitable growth. -Working with bigdata, SAP, Oracle, Workday or several other large and complex databases. Responsibilities: -Designing and building analytical / 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 Mandatory skill sets: -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 Deep Learning and Neural Network Architectures like CNN, RNN, LSTM, Transformers etc. -Strong knowledge of SQL and R/Python and experience with distribute data/computing tools. -Experience in advanced Text Analytics (NLP, NLU, NLG). -Strong hands-on experience of end-to-end statistical model development and implementation -Basic understanding of MLOps for scalable ML development. -Expert level proficiency algorithm building languages like SQL, R and Python and data visualization tools like Shiny, Qlik, Power BI etc. -Exposure to Cloud technologies (Azure or AWS Preferred skill sets: -Experience in video/ image analytics -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 Years of experience required: -3 to 10 years' experience in Analytics modeling -Experience in algorithm development -Open for domestic and international travels Education qualification: - M.Sc. / M.Stat/ MS (Statistics / Mathematics/ Economics/ Computer Science or ML/DL focus) -B.Tech / M.Tech (Computer Science, Mathematics & Scientific Computing etc.) -MBA with ML/DL Focus. Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Master of Science, Master of Business Administration, Bachelor of Technology Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills Data Mining, Statistics Optional Skills Amazon Web Services (AWS), Microsoft Azure 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

Kovai.co is a catalyst, sparking a revolution in the world of enterprise software and B2B SaaS, we are a technology powerhouse delivering best-in-class enterprise software and game-changing SaaS solutions across industries. At Kovai.co , we're rewriting the B2B landscape by empowering over 2,500 businesses worldwide with our award-winning SaaS solutions. Our Products Biztalk360 Turbo360 Document360 “UK headquarters. Indian innovation. Global impact.” Our journey has been nothing short of remarkable, having witnessed exponential growth and profitability right from our inception. We are on track towards $30 million in annual revenue – and we're just getting started. Kovai.co is fueled by a tribe of thoughtful helpers, obsessed with empowering customers, uplifting colleagues, and igniting our own journeys. Redefining tech is our game. Are you in? Join Kovai.co – where passion meets purpose. What's the job: Data Scientist What You’ll Do On The Job Understand business problems and formulate hypothesis Collecting and interpreting data, analyzing results, identifying patterns and trends in large data sets Research and develop advanced statistical and machine learning models for analysis of large-scale, high-dimensional data Build custom machine learning models for various use-cases such as recommendation, insight generation, forecasting, anomaly detection, and so on Performing data quality checks for quality assurance Build data pipelines to supply quality data to machine learning model in production environment Supports innovative analytical thinking & solutions that results into improved business performance Writing reports based on insights gained from exploratory data analysis and able to articulate it to product owner Practice industry well-known Machine Learning Framework and best practices Who’ll be a good fit: Proven working experience of 2+ years as a Data Scientist Strong in mathematics - statistics, probability, linear algebra, time series Proficiency in working with large datasets and data wrangling using SQL (Structured Query Language) Familiar with tools such as JuPyteR, Tensorflow ,Python , Azure ML, Prophet (Open source software), MS SQL Server Working knowledge of applied machine learning techniques such as regression, clustering, forecasting of time-series data and Classification models Proficiency in LSTM, hypothesis testing and supervised learning / unsupervised learning. Familiarity with all aspects of the analytical cycle such as data wrangling and visualisation, feature engineering, and model building Write scalable scripts to fetch or modify data from API endpoints Exposure to cloud technology is preferred (Azure) Excellent critical thinking, verbal, and written communication skills Equal Opportunities Kovai.co is committed to building a workforce that reflects the richness of our society. We believe in fostering a culture of belonging and respect for all. Kovai.co stands firmly against discrimination, ensuring equal opportunity for everyone to build a successful career. Submit Your Application You have successfully applied You have errors in applying Apply With Resume * First Name* Middle Name Last Name* Email* Mobile Phone Social Network and Web Links Provide us with links to see some of your work (Git/ Dribble/ Behance/ Pinterest/ Blog/ Medium) Employer Education

Senior Data Scientist (Deep Learning and Artificial Intelligence) Job Description We aim to bring about a new paradigm in medical image diagnostics; providing intelligent, holistic, ethical, explainable and patient centric care. We are looking for innovative problem solvers who love solving problems. We want people who can empathize with the consumer, understand business problems, and design and deliver intelligent products. People who are looking to extend artificial intelligence into unexplored areas. Your primary focus will be in applying deep learning and artificial intelligence techniques to the domain of medical image analysis. Responsibilities Selecting features, building and optimizing classifier engines using deep learning techniques. Understanding the problem and applying the suitable image processing techniques Use techniques from artificial intelligence/deep learning to solve supervised and unsupervised learning problems. Understanding and designing solutions for complex problems related to medical image analysis by using Deep Learning/Object Detection/Image Segmentation. Recommend and implement best practices around the application of statistical modeling. Create, train, test, and deploy various neural networks to solve complex problems. Develop and implement solutions to fit business problems which may include applying algorithms from a standard statistical tool, deep learning or custom algorithm development. Understanding the requirements and designing solutions and architecture in accordance with them is important. Participate in code reviews, sprint planning, and Agile ceremonies to drive high-quality deliverables. Design and implement scalable data science architectures for training, inference, and deployment pipelines. Ensure code quality, readability, and maintainability by enforcing software engineering best practices within the data science team. Optimize models for production, including quantization, pruning, and latency reduction for real-time inference. Drive the adoption of versioing strategies for models, datasets, and experiments (e.g., using MLFlow, DVC). Contribute to the architectural design of data platforms to support large-scale experimentation and production workloads. Skills and Qualifications Strong software engineering skills in Python (or other languages used in data science) with emphasis on clean code, modularity, and testability. Excellent understanding and hands-on of Deep Learning techniques such as ANN, CNN, RNN, LSTM, Transformers, VAEs etc. Must have experience with Tensorflow or PyTorch framework in building, training, testing, and deploying neural networks. Experience in solving problems in the domain of Computer Vision. Knowledge of data, data augmentation, data curation, and synthetic data generation. Ability to understand the complete problem and design the solutions that best fit all the constraints. Knowledge of the common data science and deep learning libraries and toolkits such as Keras, Pandas, Scikit-learn, Numpy, Scipy, OpenCV etc. Good applied statistical skills, such as distributions, statistical testing, regression, etc. Exposure to Agile/Scrum methodologies and collaborative development practices. Experience with the development of RESTful APIs. The knowledge of libraries like FastAPI and the ability to apply it to deep learning architectures is essential. Excellent analytical and problem-solving skills with a good attitude and keen to adapt to evolving technologies. Experience with medical image analysis will be an advantage. Experience designing and building ML architecture components (e.g., feature stores, model registries, inference servers). Solid understanding of software design patterns, microservices, and cloud-native architectures. Expertise in model optimization techniques (e.g., ONNX conversion, TensorRT, model distillation) Education : BE/B Tech MS/M Tech (will be a bonus) Experience : 3+ Years Job Type: Full-time Ability to commute/relocate: Gurugram, Haryana: Reliably commute or planning to relocate before starting work (Required) Application Question(s): Do you have experience leading teams in AI Development? Do you have experience creating software architecture for production environment in AI applications? Experience: Deep learning: 3 years (Required) Computer vision: 3 years (Required) PyTorch: 3 years (Required) Work Location: In person

Senior Data Scientist (Deep Learning and Artificial Intelligence) Job Description We aim to bring about a new paradigm in medical image diagnostics; providing intelligent, holistic, ethical, explainable and patient centric care. We are looking for innovative problem solvers who love solving problems. We want people who can empathize with the consumer, understand business problems, and design and deliver intelligent products. People who are looking to extend artificial intelligence into unexplored areas. Your primary focus will be in applying deep learning and artificial intelligence techniques to the domain of medical image analysis. Responsibilities Selecting features, building and optimizing classifier engines using deep learning techniques. Understanding the problem and applying the suitable image processing techniques Use techniques from artificial intelligence/deep learning to solve supervised and unsupervised learning problems. Understanding and designing solutions for complex problems related to medical image analysis by using Deep Learning/Object Detection/Image Segmentation. Recommend and implement best practices around the application of statistical modeling. Create, train, test, and deploy various neural networks to solve complex problems. Develop and implement solutions to fit business problems which may include applying algorithms from a standard statistical tool, deep learning or custom algorithm development. Understanding the requirements and designing solutions and architecture in accordance with them is important. Participate in code reviews, sprint planning, and Agile ceremonies to drive high-quality deliverables. Design and implement scalable data science architectures for training, inference, and deployment pipelines. Ensure code quality, readability, and maintainability by enforcing software engineering best practices within the data science team. Optimize models for production, including quantization, pruning, and latency reduction for real-time inference. Drive the adoption of versioing strategies for models, datasets, and experiments (e.g., using MLFlow, DVC). Contribute to the architectural design of data platforms to support large-scale experimentation and production workloads. Skills and Qualifications Strong software engineering skills in Python (or other languages used in data science) with emphasis on clean code, modularity, and testability. Excellent understanding and hands-on of Deep Learning techniques such as ANN, CNN, RNN, LSTM, Transformers, VAEs etc. Must have experience with Tensorflow or PyTorch framework in building, training, testing, and deploying neural networks. Experience in solving problems in the domain of Computer Vision. Knowledge of data, data augmentation, data curation, and synthetic data generation. Ability to understand the complete problem and design the solutions that best fit all the constraints. Knowledge of the common data science and deep learning libraries and toolkits such as Keras, Pandas, Scikit-learn, Numpy, Scipy, OpenCV etc. Good applied statistical skills, such as distributions, statistical testing, regression, etc. Exposure to Agile/Scrum methodologies and collaborative development practices. Experience with the development of RESTful APIs. The knowledge of libraries like FastAPI and the ability to apply it to deep learning architectures is essential. Excellent analytical and problem-solving skills with a good attitude and keen to adapt to evolving technologies. Experience with medical image analysis will be an advantage. Experience designing and building ML architecture components (e.g., feature stores, model registries, inference servers). Solid understanding of software design patterns, microservices, and cloud-native architectures. Expertise in model optimization techniques (e.g., ONNX conversion, TensorRT, model distillation) Education : BE/B Tech MS/M Tech (will be a bonus) Experience : 3+ Years Job Type: Full-time Ability to commute/relocate: Gurugram, Haryana: Reliably commute or planning to relocate before starting work (Required) Application Question(s): Do you have experience leading teams in AI Development? Do you have experience creating software architecture for production environment in AI applications? Experience: Deep learning: 3 years (Required) Computer vision: 3 years (Required) PyTorch: 3 years (Required) Work Location: In person

Experience: 3+ years Requirements: Excellent knowledge of computer vision concepts, including but not limited to Image Classification, Object Detection, and Semantic Segmentation, developed using state-of-the-art deep learning algorithms. Hands-on experience developing efficient and real-time convolutional neural network (CNN) models for computer vision tasks. Strong proficiency in at least one of the deep learning frameworks, such as PyTorch , TensorFlow , or Caffe, with the ability to apply them to computer vision problems. Quick prototyping skills in Python and coding and debugging proficiency in C++ . Good communication and collaboration skills to work effectively in a team and communicate complex technical concepts. Qualifications: A Ph.D. degree (including candidates at various stages of their Ph.D., such as thesis submission, thesis submitted, degree awaited, synopsis seminar completed, defense completed) in Deep Learning with hands-on coding skills and a passion for an industrial career will be preferred. Master's or Bachelor's degree with thorough industrial work experience in developing computer vision applications using deep learning. Postgraduates or Undergraduates with a strong academic background in Deep Learning, Computer Vision, or related fields, and demonstrated coding skills, are also encouraged to apply. Preferred: Publications in top-tier computer vision conferences like CVPR, ICCV, ECCV , or major AI conferences like NeurIPS. Knowledge of computer vision libraries and tools, including OpenCV and DLib, and a solid understanding of image processing and computer vision fundamentals. Hands-on experience with model compression and pruning techniques in deep learning. Good exposure to various deep learning architectures, such as Artificial Neural Networks (ANN), Deep Neural Networks (DNN) , Convolutional Neural Networks (CNN) , Recurrent Neural Networks (RNN ), and Long Short-Term Memory (LSTM) networks. Familiarity with GPU programming (e.g., CUDA, OpenCL) for efficient deep-learning computations. Pay is competitive as per market standards.

Company Description Datakrew is a deep-tech startup based in Singapore, building next-generation analytics for electric vehicle (EV) fleets, batteries, and grid-connected energy assets. Our OXRED platform is deployed across OEMs and operators to extract real-time intelligence from EV battery telemetry, reduce safety risks, and extend usable battery life. We are currently looking for a Battery Intelligence Engineer to support our internal R&D and analytics module development. This role is ideal for someone with a strong interest in battery health modeling, time-series ML, and predictive maintenance. Job Description Responsibilities: Build, train, and benchmark ML models (e.g. LSTM, XGBoost) for battery State-of-Health (SOH), Remaining Useful Life (RUL), and degradation prediction. Analyze large-scale battery performance data to extract actionable insights. Develop anomaly and event detection algorithms for safety-critical battery threats. Create predictive maintenance models to forecast battery failures and degradation. Validate and benchmark model performance using real-world and simulated datasets. Work with the product team to ensure integration of developed models. Stay updated with the latest research in battery modeling and machine learning techniques. Research and collaborate with the team to incorporate electrochemical knowledge into ML models. Qualifications Preferred Skills & Tools: Python (Pandas, NumPy, Scikit-learn, PyTorch or TensorFlow) Strong grasp of time-series modeling, signal processing, and statistical evaluation Familiarity with LSTM, GRU, transformer models, or forecasting pipelines Hands-on experience with deep learning models (CNN, DNN, RNN), NLP techniques, and sequence models Exposure to modern LLM ecosystems (ChatGPT, Gemini, Ollama) and tools like LangChain, AI agents, and prompt engineering Good understanding of battery systems: SOC, SOH, DOD, thermal behaviour, lifecycle stressors Experience working with EV, IoT, or BMS datasets (even in academic projects) SQL basics for querying historical telemetry Nice to Have: Familiarity with Kalman filters, physics-informed models, or hybrid ML-physics methods GitHub portfolio or academic project code repos Knowledge of EV architectures or energy storage standards Additional Information If you’re interested in the EV or battery analytics domain, we welcome your application. Engagement Model: Flexible remote work Duration: 2–4 months (extendable) This is a part-time or freelance position.

Dear Candidate, We are seeking a Machine Learning Engineer to develop predictive models and deploy them into production. Ideal for professionals passionate about AI and data science. Key Responsibilities: Develop and train machine learning models Preprocess and analyze large datasets Deploy models using scalable infrastructure Collaborate with product teams to integrate ML solutions Required Skills & Qualifications: Strong knowledge of Python and ML libraries (scikit-learn, TensorFlow, PyTorch) Experience with data preprocessing and feature engineering Familiarity with model deployment techniques Bonus: Experience with cloud ML services (AWS SageMaker, Google AI Platform) Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Delivery Manager Integra Technologies

Job Description We aim to bring about a new paradigm in medical image diagnostics; providing intelligent, holistic, ethical, explainable and patient centric care. We are looking for innovative problem solvers who love solving problems. We want people who can empathize with the consumer, understand business problems, and design and deliver intelligent products. People who are looking to extend artificial intelligence into unexplored areas. Your primary focus will be in applying deep learning and artificial intelligence techniques to the domain of medical image analysis. Responsibilities Selecting features, building and optimizing classifier engines using deep learning techniques. Understanding the problem and applying the suitable image processing techniques Use techniques from artificial intelligence/deep learning to solve supervised and unsupervised learning problems. Understanding and designing solutions for complex problems related to medical image analysis by using Deep Learning/Object Detection/Image Segmentation. Recommend and implement best practices around the application of statistical modeling. Create, train, test, and deploy various neural networks to solve complex problems. Develop and implement solutions to fit business problems which may include applying algorithms from a standard statistical tool, deep learning or custom algorithm development. Understanding the requirements and designing solutions and architecture in accordance with them. Participate in code reviews, sprint planning, and Agile ceremonies to drive high-quality deliverables. Design and implement scalable data science architectures for training, inference, and deployment pipelines. Ensure code quality, readability, and maintainability by enforcing software engineering best practices within the data science team. Optimize models for production, including quantization, pruning, and latency reduction for real-time inference. Drive the adoption of versioing strategies for models, datasets, and experiments (e.g., using MLFlow, DVC). Contribute to the architectural design of data platforms to support large-scale experimentation and production workloads. Skills and Qualifications Strong software engineering skills in Python (or other languages used in data science) with emphasis on clean code, modularity, and testability. Excellent understanding and hands-on of Deep Learning techniques such as ANN, CNN, RNN, LSTM, Transformers, VAEs etc. Must have experience with Tensorflow or PyTorch framework in building, training, testing, and deploying neural networks. Experience in solving problems in the domain of Computer Vision. Knowledge of data, data augmentation, data curation, and synthetic data generation. Ability to understand the complete problem and design the solutions that best fit all the constraints. Knowledge of the common data science and deep learning libraries and toolkits such as Keras, Pandas, Scikit-learn, Numpy, Scipy, OpenCV etc. Good applied statistical skills, such as distributions, statistical testing, regression, etc. Exposure to Agile/Scrum methodologies and collaborative development practices. Experience with the development of RESTful APIs. The knowledge of libraries like FastAPI and the ability to apply it to deep learning architectures is essential. Excellent analytical and problem-solving skills with a good attitude and keen to adapt to evolving technologies. Experience with medical image analysis will be an advantage. Experience designing and building ML architecture components (e.g., feature stores, model registries, inference servers). Solid understanding of software design patterns, microservices, and cloud-native architectures. Expertise in model optimization techniques (e.g., ONNX conversion, TensorRT, model distillation) Education: BE/B Tech MS/M Tech (will be a bonus) Experience: 3-5 Years

Company: Aiventory (A unit of Jazzoa Services OPC Private Limited) Location: Remote Stipend: ₹3,000 – ₹5,000/month Duration: 3 to 6 months Start Date: Immediate About Us: Aiventory is an AI-powered inventory management platform built specifically for India's Kirana stores and small retail businesses. We're on a mission to bring cutting-edge technology to the underserved sectors of India’s supply chain. We are currently seeking a passionate AI/ML Intern to join our product team and work closely on real-world machine learning applications like demand forecasting, anomaly detection, and computer vision for inventory intelligence. What You'll Work On: Building and training ML models (LSTM, ARIMA, Isolation Forest, etc.) Assisting in real-time prediction engine development for stock trends Image recognition using OpenCV or TensorFlow (barcode/label detection) Data preprocessing and feature engineering for retail datasets Supporting our AI roadmap across backend services You Should Know (at least some of): Python, Pandas, NumPy, Scikit-learn TensorFlow / PyTorch / OpenCV Time Series Forecasting models (ARIMA, LSTM) Basics of SQL or MongoDB Git and version control practices Bonus (Not Mandatory): Experience with retail or inventory datasets Worked on any personal ML projects or GitHub repos Familiarity with cloud (AWS, GCP) or Docker What You’ll Gain: Hands-on experience building real-world AI applications Certificate & Letter of Recommendation Potential for PPO (Pre-Placement Offer) based on performance Opportunity to work directly with the founding team and AI product manager

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 Data Scientist II-3 Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Overview Finicity, a Mastercard company, is leading the Open Banking Initiative to increase the Financial Health of consumers and businesses. The Data Science and Analytics team is looking for a Data Scientist II. The Data Science team works on Intelligent Decisioning; Financial Certainty; Attribute, Feature, and Entity Resolution; Verification Solutions and much more. Join our team to make an impact across all sectors of the economy by consistently innovating and problem-solving. The ideal candidate is passionate about leveraging data to provide high quality customer solutions. Also, the candidate is a strong technical leader who is extremely motivated, intellectually curious, analytical, and possesses an entrepreneurial mindset. Role Manipulates large data sets and applies various technical and statistical analytical techniques (e.g., OLS, multinomial logistic regression, LDA, clustering, segmentation) to draw insights from large datasets. Apply various Machine learning (i.e. SVM, Radom Forest, XGBoost, LightGBM, CATBoost etc), Deep learning techniques (i.e. LSTM, RNN, Transformer etc.) to solve analytical problem statement. Design and implement machine learning models for a number of financial applications including but not limited to: Transaction Classification, Temporal Analysis, Risk modeling from structured and unstructured data. Measure, validate, implement, monitor and improve performance of both internal and external facing machine learning models. Propose creative solutions to existing challenges that are new to the company, the financial industry and to data science. Present technical problems and findings to business leaders internally and to clients succinctly and clearly. Leverage best practices in machine learning and data engineering to develop scalable solutions. Identify areas where resources fall short of needs and provide thoughtful and sustainable solutions to benefit the team Be a strong, confident, and excellent writer and speaker, able to communicate your analysis, vision and roadmap effectively to a wide variety of stakeholders All About You: 3-5 years in data science/ machine learning model development and deployments Exposure to financial transactional structured and unstructured data, transaction classification, risk evaluation and credit risk modeling is a plus. A strong understanding of NLP, Statistical Modeling, Visualization and advanced Data Science techniques/methods. Gain insights from text, including non-language tokens and use the thought process of annotations in text analysis. Solve problems that are new to the company, the financial industry and to data science SQL / Database experience is preferred Experience with Kubernetes, Containers, Docker, REST APIs, Event Streams or other delivery mechanisms. Familiarity with relevant technologies (e.g. Tensorflow, Python, Sklearn, Pandas, etc.). Strong desire to collaborate and ability to come up with creative solutions. Additional Finance and FinTech experience preferred. Bachelor’s or Master’s Degree in Computer Science, Information Technology, Engineering, Mathematics, Statistics. Corporate Security Responsibility Every Person Working For, Or On Behalf Of, Mastercard Is Responsible For Information Security. All Activities Involving Access To Mastercard Assets, Information, And Networks Comes With An Inherent Risk To The Organization And Therefore, It Is Expected That The Successful Candidate For This Position 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. #AI 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. R-247687

About The Role 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. Technical Skills Proficiency in programming languages such as Python & R Strong knowledge of classical machine 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 with ML frameworks like TensorFlow, PyTorch, Scikit-learn, or Keras. Building & deploying Model APIs using framework like Flask, Fast API, Django, TensorFlow Serving etc. Knowledge of cloud platforms like Azure (preferred), AWS, GCP and experience deploying models in such environments. Nice To Have Object Oriented Programming. Familiarity with NLP, or time series analysis. Exposure to deep learning models (RNN, LSTM) and working with GPUs. (ref:hirist.tech)

Selected Intern's Day-to-day Responsibilities Include Research, identify, and understand business requirements to identify opportunities for applying predictive modeling and machine learning techniques Collaborate with cross-functional teams, including data scientists, software engineers, and domain experts, to define project objectives and requirements Design and implement predictive modeling and machine learning solutions, including data preprocessing, feature engineering, and model selection Develop and deploy predictive software applications into production, leveraging Python (or similar scripting languages) for efficient development Expertise in training and fine-tuning LLMs on diverse datasets, ensuring superior performance, and adapting models for specific applications and domains. Work with cloud-native solutions on platforms such as AWS, GCP, or Azure for scalability and flexibility Apply a range of machine learning algorithms for different tasks, including classification (SVM, decision tree, random forest, neural network), regression (linear, polynomial, logistic, etc), and graph theory (network analytics) Utilize classical optimization techniques such as gradient descent and others for model optimization and parameter tuning Utilize deep learning techniques, including LSTM, convolutional neural networks (CNN), and recurrent neural networks (RNN), for tasks such as natural language processing, image recognition, or time series analysis Experience with training ML models using Pytorch or tensorflow. About Company: We deliver business growth by providing AI-powered data enrichment. Currently working in stealth mode.

Educational Qualification: Education: Masters or PhD in Computer Science, Machine Learning, AI, Engineering, or a related technical field. Work Experience : Experience: 4-6 years of experience in machine learning based data product research and development in addition to relevant educational background in the field of Computer Science, Engineering, Machine Learning etc. Role Description : We are seeking an AI Scientist to join our analytics team. This role focuses on the development of innovative machine learning and deep learning models that unlock the full potential of Pixxels hyperspectral data. You will work on impactful, data-driven projects aimed at solving complex challenges using state-of-the-art technology and methodologies. As a key contributor to Pixxels analytics vision, you will: Leverage state-of-the-art AI techniques to address complex challenges in imaging analytics, data fusion, and large-scale data processing. Develop multimodal AI models that integrate hyperspectral data with other sensor modalities like radar, LiDAR, and weather datasets, enabling actionable insights for clients across diverse industries. Work closely with cross-functional teams, translating business and scientific objectives into AI-powered solutions that are scalable, efficient, and impactful. Responsibilities & Duties : AI Model Development: Design and implement advanced AI/ML models for classification, prediction, segmentation, and anomaly detection using Pixxels hyperspectral data and multimodal datasets. Multimodal Data Fusion: Integrate diverse data sources, such as hyperspectral, radar, LiDAR, and ancillary datasets, to enhance feature extraction, accuracy, and scalability. Algorithm Optimization: Develop computationally efficient algorithms that can handle large-scale, high-dimensional datasets and deploy them in production environments. R&D Leadership: Research and implement state-of-the-art techniques, including Transformer models, GANs, self-supervised learning, and other emerging techniques, to stay ahead in AI innovation. Cross-Functional Collaboration: Work with domain experts (e.g., hyperspectral scientists, environmental specialists) to understand the data and define project objectives, translating business problems into robust AI models. Communication & Presentation: Clearly explain complex AI concepts, model outputs, and research findings to technical and non-technical stakeholders. Skills and Experience Required: Technical Expertise: Proficiency in advanced machine learning and deep learning architectures (e.g., CNNs, RNNs, Transformers, GANs, LSTMs). Strong background in Python and frameworks such as PyTorch, TensorFlow, or PyTorch Lightning. Experience in developing AI models for complex datasets. Experience with imaging data (e.g., hyperspectral, medical, drone, or satellite imagery), is not required, but would be beneficial. Solid understanding of key principles in multimodal data fusion, computer vision, and large-scale data processing. Communication & Collaboration: Strong communication skills to present findings, teach concepts, and collaborate effectively with non-AI experts. Ability to work cross-functionally with data scientists, engineers, and domain specialists . R&D Mindset: Proven experience in implementing cutting-edge research techniques and staying up-to-date with advancements in AI. Candidate Acumen : As an AI Scientist, I bring expertise in developing advanced machine learning and deep learning models to extract insights from hyperspectral data, leveraging state-of-the-art methodologies to tackle complex, data-driven challenges. Benefits: Comprehensive insurance coverage for you and your family. Free access to mental health professionals and paid sick leave. Benefits like vaccination drives and more. Flexible working hours. Opportunity to work with top scientists and professionals in space technology.