85 Nlp Techniques Jobs - Page 3

You should have a Master of Science in a relevant field such as Computer Science, Statistics, Mathematics, Engineering, or Data Science. Additionally, you should possess 1-3 years of experience applying machine learning techniques to solve complex data problems. It is important to have a strong knowledge of machine learning algorithms and statistical models, including supervised and unsupervised learning methods. Experience with data preprocessing, feature engineering, and data visualization techniques is required. Proficiency in Python programming and experience working with big data tools such as Spark are essential for this role. Your role will require excellent communication skills, with the ability to explain complex concepts to non-technical stakeholders. Strong problem-solving skills and attention to detail are also crucial. You should have experience with agile development methodologies and version control tools such as Git. Preferred qualifications for this position include experience working with natural language processing (NLP) techniques, familiarity with deep learning frameworks such as TensorFlow or PyTorch, and knowledge of cloud computing platforms such as AWS, GCP, or Azure. If you meet these requirements and possess the desired qualifications, we encourage you to apply for this position.,

Who We Are Wayfair is moving the world so that anyone can live in a home they love a journey enabled by more than 3,000 Wayfair engineers and a data-centric culture. Wayfairs Advertising business is rapidly expanding, adding hundreds of millions of dollars in profits to Wayfair. We are building Sponsored Products, Display & Video Ad offerings that cater to a variety of Advertiser goals while showing highly relevant and engaging Ads to millions of customers. We are evolving our Ads Platform to empower advertisers across all sophistication levels to grow their business on Wayfair at a strong, positive ROI and are leveraging state of the art Machine Learning techniques. The Advertising Optimization & Automation Science team is central to this effort. We leverage machine learning and generative AI to streamline campaign workflows, delivering impactful recommendations on budget allocation, target Return on Ad Spend (tROAS), and SKU selection. Additionally, we are developing intelligent systems for creative optimization and exploring agentic frameworks to further simplify and enhance advertiser interactions. We are looking for an experienced Senior Machine Learning Scientist to join the Advertising Optimization & Automation Science team. In this role, you will be responsible for building intelligent, ML-powered systems that drive personalized recommendations and campaign automation within Wayfairs advertising platform. You will work closely with other scientists, as well as members of our internal Product and Engineering teams, to apply your ML expertise to define and deliver 0-to-1 capabilities that unlock substantial commercial value and directly enhance advertiser outcomes. What Youll do Design and build intelligent budget, tROAS, and SKU recommendations, and simulation-driven decisioning that extends beyond the current advertising platform capabilities. Lead the next phase of GenAI-powered creative optimization and automation to drive significant incremental ad revenue and improve supplier outcomes. Raise technical standards across the team by promoting best practices in ML system design and development. Partner cross-functionally with Product, Engineering, and Sales to deliver scalable ML solutions that improve supplier campaign performance. Ensure systems are designed for reuse, extensibility, and long-term impact across multiple advertising workflows. Research and apply best practices in advertising science, GenAI applications in creative personalization, and auction modeling. Keep Wayfair at the forefront of innovation in supplier marketing optimization. Collaborate with Engineering teams (AdTech, ML Platform, Campaign Management) to build and scale the infrastructure needed for automated, intelligent advertising decisioning. We Are a Match Because You Have : Bachelor&aposs or Masters degree in Computer Science, Mathematics, Statistics, or related field. 9+ years of experience in building large scale machine learning algorithms. 4+ years of experience working in an architect or technical leadership position. Strong theoretical understanding of statistical models such as regression, clustering and ML algorithms such as decision trees, neural networks, transformers and NLP techniques. Proficiency in programming languages such as Python and relevant ML libraries (e.g., TensorFlow, PyTorch) to develop production-grade products. Strategic thinker with a customer-centric mindset and a desire for creative problem solving, looking to make a big impact in a growing organization. Demonstrated success influencing senior level stakeholders on strategic direction based on recommendations backed by in-depth analysis; Excellent written and verbal communication. Ability to partner cross-functionally to own and shape technical roadmaps Intellectual curiosity and a desire to always be learning! Nice to have Experience with GCP, Airflow, and containerization (Docker). Experience building scalable data processing pipelines with big data tools such as Hadoop, Hive, SQL, Spark, etc. Familiarity with Generative AI and agentic workflows. Experience in Bayesian Learning, Multi-armed Bandits, or Reinforcement Learning. About Wayfair Inc. Wayfair is one of the worlds largest online destinations for the home. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If youre looking for rapid growth, constant learning, and dynamic challenges, then youll find that amazing career opportunities are knocking. No matter who you are, Wayfair is a place you can call home. Were a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair and world for all. Every voice, every perspective matters. Thats why were proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, genetic information, or any other legally protected characteristic. We are interested in retaining your data for a period of 12 months to consider you for suitable positions within Wayfair. Your personal data is processed in accordance with our Candidate Privacy Notice (which can found here: https://www.wayfair.com/careers/privacy). If you have any questions regarding our processing of your personal data, please contact us at [HIDDEN TEXT]. If you would rather not have us retain your data please contact us anytime at [HIDDEN TEXT]. Show more Show less

You will be joining our Data & AI practice as an Individual Contributor and Functional AI Decision Science Consultant at Level 9, with the opportunity to work in Gurgaon, Bangalore, Mumbai, or Hyderabad. As part of a global team of skilled professionals, you will utilize cutting-edge statistical tools and methodologies to deliver data-driven insights and solutions for our clients. Your primary responsibilities will include defining data requirements for Data Driven Growth Analytics, analyzing and interpreting data, and ensuring data quality. You will work on market sizing, lift ratio estimation, non-linear optimization techniques, statistical timeseries models, store clustering algorithms, and descriptive analytics to support merchandising AI capabilities. Additionally, you will develop AI/ML models using Azure ML tech stack, manage data pipelines, and leverage cloud platforms for deploying and scaling machine learning models. In this role, you will also be expected to manage client relationships, effectively communicate insights and recommendations, and contribute to capability building and thought leadership within the team. Your logical thinking and task management skills will be crucial to analyze data systematically and prioritize tasks efficiently. To be successful in this position, you should have a minimum of 4+ years of experience in Marketing analytics and 3+ years of experience in Data Driven Merchandizing. Proficiency in econometric/statistical modeling, Azure ML, SQL, R, Python, and PySpark is essential, along with a strong understanding of marketing data and business processes in the Retail and CPG industries. A Bachelor's or Master's degree in Statistics, Economics, Mathematics, Computer Science, or related fields is required, along with excellent academic credentials. Additionally, knowledge of tools like Excel, Word, and PowerPoint for communication and documentation will be beneficial in this role. If you are seeking a challenging opportunity to work with a dynamic team of professionals and make a significant impact in the field of Data & AI, we invite you to apply and join our team at Accenture.,

You have over 5 years of experience in building production-grade Neural Network models using Computer Vision or Natural Language Processing techniques. You possess a strong understanding of various machine learning techniques and algorithms, including k-NN, Naive Bayes, SVM, Decision Forests, and Neural Networks. Experience with Deep Learning frameworks like TensorFlow, PyTorch, and MxNet is part of your skillset. Proficiency in common data science toolkits such as R, Sklearn, NumPy, MatLab, and MLib is highly desirable. Additionally, you have solid applied statistics skills encompassing distributions, statistical testing, and regression. Your expertise extends to using query languages like SQL, Hive, Pig, and NoSQL databases. In this role, you will collaborate with Product Managers, Architects, and Engineering Leadership to conceptualize, strategize, and develop new products focused on AI/ML initiatives. You will be responsible for developing, driving, and executing the long-term vision and strategy for the Data Science team by engaging with multiple teams and stakeholders across the organization. Your tasks will involve architecting, designing, and implementing large-scale machine learning systems. Specifically, you will develop Neural Network models for information extraction from mortgage documents using Computer Vision and NLP techniques. Ad-hoc analysis and clear presentation of results to various audiences and key stakeholders will be part of your routine. You will also design experiments, test hypotheses, and build models while conducting advanced data analysis and highly complex algorithm designs. Applying advanced statistical, predictive, and machine learning modeling techniques to enhance multiple real-time decision systems will be a key aspect of your role. You will collaborate with development teams to deploy models in the production environment to support ML-driven product features. Furthermore, you will define business-specific performance metrics to assess model effectiveness and continuously monitor and enhance these metrics over time for models in a production environment. To qualify for this position, you should hold an M.S. in mathematics, statistics, computer science, or a related field, with a Ph.D. degree being preferred. You must have over 5 years of relevant quantitative and qualitative research and analytics experience. Excellent communication skills and the ability to effectively convey complex topics to a diverse audience are essential attributes for this role.,

You are a Gen AI Senior Software Engineer with over 5 years of experience, specializing in Generative AI and Large Language Models (LLMs). Your main responsibility is to design, develop, and implement GenAI solutions tailored to address business challenges, utilizing your expertise in Python for AI/ML solutions. Your key technical skills include proficiency in Python programming, hands-on experience in Retrieval-Augmented Generation (RAG) and familiarity with Vector Databases. It would be beneficial if you have experience in React.js and are open to learning new skills and technologies. In this role, you will be responsible for designing and implementing scalable GenAI solutions using Python, leading the architecture of AI-driven solutions, and developing customized solutions using Large Language Models (LLMs) for various applications. You will also create AI models for text and speech data, optimize AI model performance using similarity search algorithms, and build conversational chatbots using advanced NLP techniques. Furthermore, you will utilize vector databases to store and manage data for AI applications, implement Retrieval-Augmented Generation (RAG) pipelines, develop and maintain ETL pipelines for efficient data flow, and conduct experiments to evaluate AI model performance. You will also ensure that AI solutions comply with data privacy, security, and ethical standards while contributing to front-end development using React.js to create user-friendly interfaces for AI applications. Soft skills required for this role include adaptability to work in an agile environment, excellent presentation skills to engage with business users, and the ability to provide expert advice to resolve project issues and ensure client satisfaction.,

The ideal candidate for this position should have previous experience in building data science/algorithms based products, which would be a significant advantage. Experience in handling healthcare data is also desired. An educational qualification of Bachelors/Masters in computer science/Data Science or related subjects from a reputable institution is required. With a typical experience of 7-9 years in the industry, the candidate should have a strong background in developing data science models and solutions. The ability to quickly adapt to new programming languages, technologies, and frameworks is essential. A deep understanding of data structures and algorithms is necessary. The candidate should also have a proven track record of implementing end-to-end data science modeling projects and providing guidance and thought leadership to the team. Experience in a consulting environment with a hands-on attitude is preferred. As a Data Science Lead, the primary responsibility will be to lead a team of analysts, data scientists, and engineers to deliver end-to-end solutions for pharmaceutical clients. The candidate is expected to participate in client proposal discussions with senior stakeholders and provide technical thought leadership. Expertise in all phases of model development, including exploratory data analysis, hypothesis testing, feature creation, dimension reduction, model training, selection, validation, and deployment, is required. A deep understanding of statistical and machine learning methods such as logistic regression, SVM, decision tree, random forest, neural network, and regression is essential. Mathematical knowledge of correlation/causation, classification, recommenders, probability, stochastic processes, NLP, and their practical implementation to solve business problems is necessary. The candidate should also be able to implement ML models in an optimized and sustainable framework and gain business understanding in the healthcare domain to develop relevant analytics use cases. In terms of technical skills, the candidate should have expert-level proficiency in programming languages like Python/SQL, along with working knowledge of relational SQL and NoSQL databases such as Postgres and Redshift. Extensive knowledge of predictive and machine learning models, NLP techniques, deep learning, and unsupervised learning is required. Familiarity with data structures, pre-processing, feature engineering, sampling techniques, and statistical analysis is important. Exposure to open-source tools, cloud platforms like AWS and Azure, and AI tools like LLM models and visualization tools like Tableau and PowerBI is preferred. If you do not meet every job requirement, the company encourages candidates to apply anyway, as they are dedicated to building a diverse, inclusive, and authentic workplace. Your excitement for the role and potential fit may make you the right candidate for this position or others within the company.,

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.,

As an AI Development and Integration specialist, you will be responsible for developing and optimizing AI solutions using tools like Claude.ai, Perplexity.ai, and other Anthropics-powered systems. Your primary focus will be on building and integrating AI-driven features into EdTech platforms to enhance adaptive learning, content personalization, and intelligent tutoring capabilities. In the realm of EdTech solutions development, you will design AI applications specifically tailored to the education sector. This includes creating virtual tutors, automated assessments, and recommendation systems. It will be crucial for you to collaborate closely with educators and curriculum designers to ensure that the AI functionalities align with educational goals effectively. Your role will also involve model training and fine-tuning, where you will be required to train and optimize LLMs for specific EdTech use cases. This process aims to guarantee the delivery of accurate and meaningful interactions. Additionally, you will apply transfer learning techniques to customize general AI models for education-specific tasks. Utilizing tools like Claude.ai and Perplexity.ai will be essential in your work to create innovative solutions for interactive learning and derive data-driven insights. You will have the opportunity to experiment with features from emerging Anthropics technologies to enhance the capabilities of the EdTech platform continually. Staying updated on the latest developments in AI and EdTech will be a crucial aspect of your role to implement cutting-edge solutions effectively. Engaging in exploratory research to explore how advanced AI tools can address key challenges in the education sector will also be part of your responsibilities. Collaboration and stakeholder engagement will play a significant role in your work, requiring you to work closely with product managers, UX designers, and other developers to deliver AI-powered EdTech features successfully. You will need to effectively communicate AI concepts and capabilities to technical and non-technical stakeholders, ensuring a clear understanding across the board. To excel in this role, you should hold a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. would be advantageous. Demonstrated expertise in working with Claude.ai, Perplexity.ai, and other Anthropics systems is essential. Proficiency in Python and familiarity with AI frameworks like TensorFlow, PyTorch, and Hugging Face are required. A deep understanding of NLP techniques, LLM architectures, and transformer-based models is crucial. Experience with API integrations and deploying AI/ML models in production environments is necessary. Previous experience in developing AI solutions for educational platforms and knowledge of challenges in EdTech, including accessibility, data privacy (e.g., FERPA, GDPR), and scalability, will be beneficial for this role.,

As an AI Software Engineer Leader at Hyperforce Developer Experience, you will be part of a team dedicated to enhancing developer productivity and experience through generative AI. Our goal is to revolutionize software development by providing cutting-edge AI-powered tools and solutions that exceed customer expectations and establish a strong reputation for excellence. Your role will involve working on a cutting-edge AI platform to enhance developer productivity, offering features like advanced code generation, intelligent code completion, automated testing, and throughout SDLC. You will lead a team of AI engineers in developing and implementing AI solutions across the software development life cycle. Your responsibilities will include continuously innovating and exploring advanced AI techniques to improve SDLC processes, reducing development time and effort through automated code generation and intelligent suggestions, enhancing code accuracy, readability, and maintainability with AI-powered tools, empowering developers to explore new ideas and experiment with cutting-edge technologies, automating repetitive tasks and streamlining the development process, optimizing AI models through data analysis, designing user-friendly interfaces for AI-powered tools, and building a scalable infrastructure to support a growing user base. In this role, you will drive the vision of transforming engineers" productivity by infusing AI technologies/tools into SDLC in collaboration with teams across geographies. You will build and lead a team of engineers to deliver various AI engineering initiatives, have solid experience in building large-scale AI systems in public cloud environments, identify and resolve reliability and data quality issues, mentor and coach engineers for continuous development, recruit top talent, collaborate with cross-functional teams for execution and delivery, manage multiple engineering teams, design and implement algorithms for code suggestions, evaluate AI model performance, maintain data retrieval systems, ensure code generation meets standards and user preferences, develop AI-powered features in IDEs, and more. Core qualifications for this role include a degree in computer science or a related field, 14+ years of relevant software development experience with 5+ years of team management experience, at least 3+ years of AI/ML engineering experience, proficiency in programming languages such as Python, Java, Typescript, or Golang, knowledge of NLP techniques and code generation techniques, expertise in cloud native services, strong analytical and communication skills, and the ability to work in a fast-paced environment with a focus on delivering high-quality results under tight deadlines.,

As an experienced AI Architect with 4+ years of experience, your core responsibilities will involve designing and architecting AI pipelines that encompass ingestion, extraction, deduplication, quality checks, reasoning, and visualization using LLM-based technologies. You will be tasked with creating agentic workflows that efficiently coordinate various tools, functions, and data sources through orchestration frameworks. Additionally, your role will require building user-facing agents that can interpret queries, retrieve data, and deliver tailored outputs utilizing RAG technology. Collaborating with product, engineering, and domain experts, you will integrate AI applications into production environments and develop generative interfaces for tasks like report generation, insight synthesis, and stakeholder communications. Furthermore, you will be responsible for defining LLM customization strategies, including fine-tuning, prompt engineering, and retrieval optimization. Your expertise in Prompt Engineering will be crucial, as you will be crafting and refining prompts to guide task-specific LLM behavior. Practical experience with LLM APIs from providers like OpenAI, Anthropic, or similar platforms is essential. Familiarity with RAG, embeddings, and retrieval-augmented generation patterns will be required for creating user-friendly agents. Proficiency in software development using Python, Git, testing, and modern development practices is necessary. Working knowledge of NLP techniques such as entity recognition, text classification, and model adaptation will also be beneficial. Additionally, you should be able to define and track metrics for accuracy, latency, and hallucination in LLM agents and have experience in generative visualization using tools like Vega-Lite, Observable, or custom pipelines. Ideally, you should hold a Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related field, or possess equivalent hands-on experience. You must have at least two years of experience developing production software, with a minimum of one year dedicated to building LLM-driven applications or AI agents. A portfolio, GitHub repository, or case study showcasing AI-enabled solutions in real or simulated environments would be advantageous. Bonus skills that would set you apart include an understanding of LLM fine-tuning, agent orchestration frameworks like CrewAI or LangChain, knowledge of open-source LLMs such as LLaMA, familiarity with AWS and Docker, and hands-on experience with transformer libraries like Hugging Face. This is a full-time position that requires working in person.,

Tata Electronics Pvt. Ltd. is a key global player in the electronics manufacturing industry, specializing in Electronics Manufacturing Services, Semiconductor Assembly & Test, Semiconductor Foundry, and Design Services. Established in 2020 by the Tata Group, the company's primary objective is to provide integrated solutions to global customers across the electronics and semiconductor value chain. We are looking for an AI Core Developer to join our R&D team in Bangalore. This role is centered around fundamental AI research, algorithm development, and model pre-training, focusing on innovation rather than application engineering. As an AI Core Developer, you will be involved in cutting-edge AI research, creating novel algorithms, and constructing foundation models from scratch. This position is ideal for individuals with a strong background in pre-training methodologies and algorithm development who aspire to contribute to core AI advancements. Your responsibilities will include developing and implementing innovative machine learning algorithms for various AI systems, designing pre-training pipelines for large models, prototyping new AI architectures, collaborating with research scientists and engineers, and contributing to technical publications. The ideal candidate should hold a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field, with 2-4 years of hands-on experience in AI/ML development. Proficiency in Python, C/C++, knowledge of deep learning frameworks such as PyTorch and TensorFlow, and experience with model pre-training are essential requirements. Strong mathematical skills, familiarity with transformer architectures and attention mechanisms, and understanding of distributed computing are also key competencies. Preferred qualifications include advanced experience in multimodal AI systems, research contributions to top-tier AI conferences, and expertise in specific AI domains like healthcare or finance. The position is based in Bangalore, India, with a hybrid work arrangement and occasional travel for conferences and collaborations.,

The Sales Ex COE - Client Success Data Science Specialist role based in Bangalore, Gurgaon, Hyderabad, or Mumbai requires expertise in data science, machine learning, and generative AI skills. As part of the Center of Excellence (COE), you will support salespeople by analyzing data, creating models, and delivering insights to enhance sales and pricing methods. Your primary responsibility will be to enable Sales Excellence in providing top-notch service offerings to Accenture's leaders, practitioners, and sales teams. Working within the COE Analytics Modeling Analysis team, you will develop models and scorecards to improve processes, drive sales, and maximize profitability. Collaborating with operations teams, you will translate data-driven insights into actionable solutions, manage tool access, and monitor usage. Key responsibilities include: - Extracting and transforming raw data from various sources for analysis and modeling - Applying statistical, machine learning, and NLP techniques to identify patterns and extract insights - Developing machine learning or deep learning models to address complex business challenges - Presenting findings to technical and non-technical audiences in a clear manner - Exploring Gen AI use cases and collaborating with cross-functional teams to develop solutions - Ensuring data compliance with privacy regulations and implementing security measures - Staying updated on advancements in data science and Gen AI To qualify for this role, you should have a Bachelor's degree with at least 4 years of experience in AI/ML, including expertise in machine learning algorithms, NLP techniques, generative AI skills, data visualization tools, and coding in Python, SQL, or R. Strong communication, time management, organizational, and project management skills are essential. A Master's or doctoral degree in Data Science or related field, along with experience in developing Gen AI solutions using Azure OpenAI or Google PaLM2, is preferred. Join Accenture, a leading company with a wealth of experience, and contribute your 6-9 years of expertise to drive innovation and success in the field of data science and AI.,

As an AI Developer specializing in Large Language Models (LLMs) with a focus on EdTech, you will play a crucial role in developing cutting-edge AI solutions to revolutionize learning experiences and educational outcomes. You will work with tools like Claude.ai, Perplexity.ai, and Anthropics" AI systems to create innovative features that enhance adaptive learning, content personalization, and intelligent tutoring within EdTech platforms. Your responsibilities will include developing and integrating AI solutions, designing AI applications tailored to the education sector, training and fine-tuning LLMs for specific EdTech use cases, and leveraging AI tools to create interactive learning experiences. You will also stay updated on the latest advancements in AI and EdTech, conduct research on implementing state-of-the-art solutions, and collaborate with cross-functional teams to deliver AI-powered features. To excel in this role, you should have a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. will be advantageous. Your technical skills should encompass expertise in Claude.ai, Perplexity.ai, and Anthropics systems, proficiency in Python and AI frameworks like TensorFlow and PyTorch, and a deep understanding of NLP techniques and transformer-based models. Experience with API integrations and deploying AI/ML models in production environments is essential. Furthermore, your EdTech experience should demonstrate your ability to address challenges such as accessibility, data privacy regulations (e.g., FERPA, GDPR), and scalability within educational platforms. Strong analytical, problem-solving, and communication skills are required to effectively explain complex AI concepts to both technical and non-technical stakeholders. A collaborative mindset and a passion for leveraging AI to enhance education will set you up for success in this role. Preferred qualifications include familiarity with adaptive learning systems, gamification in education, or chatbot implementations, as well as experience working with cloud platforms like AWS, GCP, or Azure. Prior involvement in projects involving real-time interactions through AI integration will be beneficial for this position.,

As a Senior ML Scientist in the Advertising Optimization & Automation Science team at Wayfair, you will play a crucial role in leveraging machine learning and generative AI to streamline campaign workflows. Based in Bangalore, India, you will contribute to building intelligent systems that drive personalized recommendations and campaign automation within Wayfair's advertising platform. Your responsibilities will include designing and implementing intelligent budget, tROAS, and SKU recommendations, as well as simulation-driven decisioning to enhance advertiser outcomes and unlock substantial commercial value. In collaboration with cross-functional teams, you will lead the development of GenAI-powered creative optimization and automation to drive incremental ad revenue and improve supplier outcomes. Additionally, you will elevate technical standards by promoting best practices in ML system design and development across the team. The ideal candidate for this role possesses a Bachelor's or Masters degree in Computer Science, Mathematics, Statistics, or a related field, along with 9+ years of experience in building large-scale machine learning algorithms. You should have a strong theoretical understanding of statistical models and ML algorithms, proficiency in programming languages such as Python, and experience with relevant ML libraries like TensorFlow and PyTorch. Strategic thinking, customer-centric mindset, and a desire for creative problem-solving are essential qualities for success in this position. Additionally, you should be adept at influencing senior-level stakeholders, possess excellent communication skills, and demonstrate the ability to shape technical roadmaps through cross-functional partnerships. Nice-to-have qualifications include experience with GCP, Airflow, and containerization, as well as familiarity with Generative AI and agentic workflows. Knowledge of Bayesian Learning, Multi-armed Bandits, or Reinforcement Learning is also advantageous. By joining Wayfair, you will be part of a dynamic and innovative team that is dedicated to reinventing the way people shop for their homes. If you are looking for a fast-paced environment that offers continuous learning and growth opportunities, Wayfair may be the perfect place for you to advance your career.,

As a Specialist IS Business Systems Analyst with Amgen, you will play a crucial role in supporting the delivery of emerging AI/ML capabilities within the Neural Nexus program. Your primary responsibilities will include collaborating with the Commercial Technology Data & Analytics team to design, implement, and iterate on a layered ecosystem focused on Data, Insights, Action, and Learning (DIAL). Working within the Scaled Agile Framework (SAFe), you will partner with Engineering and Product Management to shape roadmaps, prioritize releases, and maintain a refined product backlog. Your role will involve contributing to backlog management by breaking down Epics into Features and Sprint-ready User Stories, ensuring clear articulation of requirements, and well-defined Acceptance Criteria and Definitions of Done. Additionally, you will prioritize non-functional requirements within the backlog to uphold performance, scalability, and compliance standards. Collaboration with UX will be essential to align technical requirements, business processes, and scenarios with user-centered design principles. You will also assist in developing engaging product demonstrations for both internal and external partners and support documentation efforts to maintain accurate records of system configurations, processes, and enhancements. Your input will be crucial in the launch and growth of Neural Nexus product teams that focus on data connectivity, predictive modeling, and fast-cycle value delivery for commercial teams. Moreover, you will provide valuable insights for governance discussions and help prepare materials to align executive decision-makers on technology strategy and investment. To excel in this role, you are expected to hold a Doctorate degree, Master's degree, or Bachelor's degree with 8 to 13 years of experience in Information Systems. You should have experience in writing user requirements and acceptance criteria, an affinity for working in a DevOps environment, and an Agile mindset. Excellent problem-solving skills, experience with Agile software development methodologies, and superb communication skills are essential. Experience in managing product features, developing product roadmaps, and user journeys will be advantageous. Demonstrated expertise in data and analytics, understanding of data and analytics software systems, and familiarity with test automation software are desirable skills. Technical skills in cloud-based data technologies, AWS, design patterns, and knowledge of NLP techniques will also be beneficial. Your soft skills, including the ability to work under minimal supervision, excellent analytical skills, strong verbal and written communication abilities, and a team-oriented approach will be key to your success. Amgen offers competitive benefits and comprehensive Total Rewards Plans, supporting your professional and personal growth while fostering an inclusive environment dedicated to improving the quality of life for people worldwide.,

As a Data Science Team Lead at our organization, you will be responsible for leading a team of data scientists, planning data projects, building analytic systems, and managing a team of data scientists and machine learning engineers. Your role will also involve participating in pre-sales activities and developing proposals. With your strong expertise in machine learning, deep learning, NLP, data mining, and information retrieval, you will design, prototype, and build the next-generation analytics engines and services. Your responsibilities will include leading data mining and collection procedures, ensuring data quality and integrity, interpreting and analyzing data problems, conceiving, planning, and prioritizing data projects, building analytic systems and predictive models, testing the performance of data-driven products, visualizing data, creating reports, aligning data projects with organizational goals, understanding business problems, and designing end-to-end analytics use cases. Additionally, you will develop complex models and algorithms to drive innovation throughout the organization, conduct advanced statistical analysis to provide actionable insights, collaborate with model developers to implement scalable solutions, and provide thought leadership by researching best practices and collaborating with industry leaders. To qualify for this role, you should have 8-15 years of experience in a statistical and/or data science role, proven experience as a Data Scientist or similar role, strong organizational and leadership skills, a degree in Computer Science, Data Science, Mathematics, or a similar field, deep knowledge and experience in Large Language Models (LLM), strong knowledge of Generative AI, deep knowledge of machine learning, statistics, optimization, or a related field, experience in Linear and non-Linear Regression models, Classification models, and Unsupervised models, rich experience in NLP techniques, experience in Deep Learning techniques like CNN, RNN, GAN, and Markov, real-time experience with at least one of the machine language software like R, Python, Matlab, good knowledge in Explainable AI, experience working with large datasets, simulation/optimization, and distributed computing tools, excellent written and verbal communication skills, a strong desire to work in cross-functional teams, an attitude to thrive in a fun, fast-paced startup-like environment, and an additional advantage of experience in semi, unstructured databases. Optional qualifications include programming skills in languages like C, C++, Java, or .Net.,

We are seeking a Full-Stack AI Developer specializing in Generative AI and Large Language Models (LLMs) to take the lead in designing and developing AI-driven applications. This role requires comprehensive full-stack skills encompassing front-end design, backend AI model training and deployment, and scalable infrastructure management. Front-End Development: - Create intuitive and user-friendly interfaces for AI-powered applications. - Utilize modern web frameworks like React and Vue.js to develop responsive UI/UX. - Optimize front-end performance and ensure cross-browser compatibility. Back-End Development: - Develop robust and scalable backend systems for AI model deployment. - Design and maintain RESTful APIs for seamless front-end and back-end integration. - Manage cloud-based infrastructure using platforms such as AWS or Azure. AI Model Development: - Train, fine-tune, and deploy cutting-edge generative AI and LLM models. - Utilize frameworks like TensorFlow and PyTorch for deep learning model development. - Construct efficient inference pipelines for low-latency predictions. Data Engineering: - Design and maintain data pipelines for model training and evaluation. - Perform preprocessing and cleaning of large datasets to improve model performance. - Implement data versioning, monitoring, and reproducibility strategies. Preferred Qualifications: - A graduate degree in Computer Science, AI, Machine Learning, or a related field. - 5+ years of full-stack development experience. - 2+ years of hands-on experience in AI/ML, particularly with generative AI and LLMs. - Strong understanding of machine learning algorithms and NLP techniques. - Proficiency in Python and deep learning frameworks like TensorFlow and PyTorch. Skills & Competencies: - Strong problem-solving and architectural design skills. - Excellent communication and cross-functional collaboration abilities. - Self-motivated with the capacity to handle multiple projects concurrently. - Passion for continuous learning and staying abreast of the latest trends in AI/ML and LLMs.,

Games24x7 is seeking an experienced and detail-oriented Senior Data Analyst (DA-2) to join the team. The successful candidate will be responsible for analyzing and interpreting complex datasets to provide valuable insights that support strategic decision-making. The responsibilities of the Senior Data Analyst include gathering requirements from stakeholders, managing and prioritizing these requirements, and working on A/B experimentation to draw conclusions with statistical techniques. The candidate will need to convert actionable insights into well-defined projects, understand player behavior, and collaborate with Product, Marketing, and Technology teams to execute projects and measure their success. Additionally, the Senior Data Analyst will develop and maintain comprehensive dashboards and reports, debug, monitor, and troubleshoot various solutions, and ensure data quality standards are implemented to guarantee accuracy, reliability, and reusability of data and solutions. The ideal candidate should have a BE/B.Tech degree in Computer Science/IT from a top college, with a minimum of 4 years of experience in Analytics. Strong proficiency in statistical concepts and techniques such as hypothesis testing, regression analysis, and time series analysis is required. Experience in developing and implementing advanced statistical models and algorithms, such as logistic regression, decision trees, random forests, and gradient boosting, is essential. Hands-on experience with Large Language Models (LLMs) and natural language processing (NLP) techniques is a plus. The candidate must possess exceptional logical and analytical skills, excellent technical and communication abilities to convey complex technical concepts to non-technical stakeholders effectively, and attention to detail. Proficiency in data analysis tools and programming languages like Python, R, SQL, etc., as well as experience with data visualization tools (e.g., Tableau, Power BI) are necessary. Knowledge of data warehousing concepts and working with large datasets is advantageous. The Senior Data Analyst will be based in Bangalore and will play a crucial role in contributing to the organization's success by providing data-driven insights and solutions to drive business decisions.,

As a data and analytics engineering professional at PwC, your primary focus will be on leveraging advanced technologies and techniques to design and develop robust data solutions for our clients. You will play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and ultimately driving business growth. In the realm of artificial intelligence and machine learning, your responsibilities will involve developing and implementing advanced AI and ML solutions to foster innovation and enhance business processes. Your work will encompass designing and optimizing algorithms, models, and systems to facilitate intelligent decision-making and automation. Candidates with 15+ years of hands-on experience are preferred for this role. Essential requirements for this position include familiarity with the CCaaS domain, contact center operations, customer experience metrics, and industry-specific challenges. You should also possess a solid understanding of conversational data (chats, emails, and calls) to train Conversational AI systems. In-depth knowledge of CCaaS platforms such as NiceCX, Genesys, and Cisco, including their architecture, functionalities, and integration capabilities, is crucial. Proficiency in contact center metrics like average handle time (AHT), first call resolution (FCR), and customer satisfaction (CSAT) is necessary. Additionally, familiarity with sentiment analysis, topic modeling, and text classification techniques, as well as proficiency in data visualization tools like Tableau, Power BI, and Quicksight, is required. An understanding of cloud platforms (e.g., AWS, Azure, Google Cloud) and their services for scalable data storage, processing, and analytics is essential. Expertise in NLU verticals such as ASR generation, SSML modeling, Intent Analytics, conversational AI testing, Agent Assist, Proactive Outreach Orchestration, and Generative AI is highly valued. You will also be expected to apply advanced statistical and machine learning techniques to analyze large datasets and develop predictive models and algorithms to enhance contact center performance. Preferred qualifications include proficiency in programming languages such as Python, Pyspark, R, and SQL, as well as a strong understanding of data science principles, statistical analysis, and machine learning techniques. Experience in predictive modeling, along with skills in techniques like regression analysis, time series forecasting, clustering, and NLP techniques, is advantageous. Knowledge of distributed computing frameworks like Hadoop and Spark for processing large volumes of data is beneficial. An understanding of NoSQL databases (e.g., MongoDB, Cassandra) for handling unstructured and semi-structured data is also preferred. Awareness of data security best practices, encryption techniques, and compliance regulations (e.g., GDPR, CCPA), as well as an understanding of ethical considerations in data science and responsible AI practices, will be beneficial. The ideal educational background for this role includes a degree in BE, B.Tech, MCA, M.Sc, M.E, M.Tech, or MBA.,

You will be responsible for building and interpreting machine learning models on real business data from the SigView platform, such as Logistic Regression, Boosted trees (Gradient boosting), Random Forests, and Decision Trees. Your tasks will include identifying data sources, integrating multiple sources or types of data, and applying data analytics expertise within a data source to develop methods to compensate for limitations and extend the applicability of the data. Moreover, you will be expected to extract data from relevant data sources, including internal systems and third-party data sources, through manual and automated web scrapping. Your role will involve validating third-party metrics by cross-referencing various syndicated data sources and determining the numerical variables to be used in the same form as they are from the raw datasets, categorized into buckets, and used to create new calculated numerical variables. You will perform exploratory data analysis using PySpark to finalize the list of compulsory variables necessary to solve the business problem and transform formulated problems into implementation plans for experiments by applying appropriate data science methods, algorithms, and tools. Additionally, you will work with offshore teams post data preparation to identify the best statistical model/analytical solution that can be applied to the available data to solve the business problem and derive actionable insights. Your responsibilities will also include collating the results of the models, preparing detailed technical reports showcasing how the models can be used and modified for different scenarios in the future to develop predictive insights. You will develop multiple reports to facilitate the generation of various business scenarios and provide features for users to generate scenarios. Furthermore, you will be interpreting the results of tests and analyses to develop insights into formulated problems within the business/customer context and provide guidance on risks and limitations. Acquiring and using broad knowledge of innovative data analytics methods, algorithms, and tools, including Spark, Elasticsearch, Python, Databricks, Azure, Power BI, Azure Cloud services, LLMs-Gen AI, and Microsoft Suite will be crucial for success in this role. This position may involve telecommuting and requires 10% travel nationally to meet with clients. The minimum requirements for this role include a Bachelor's Degree in Electronics Engineering, Computer Engineering, Data Analytics, Computer Science, or a related field plus five (5) years of progressive experience in the job offered or related occupation. Special skill requirements for this role include applying statistical methods to validate results and support strategic decisions, building and interpreting advanced machine learning models, using various tools such as Python, Scikit-Learn, XGBoost, Databricks, Excel, and Azure Machine Learning for data preparation and model validation, integrating diverse data sources using data analytics techniques, and performing data analysis and predictive model development using AI/ML algorithms. Your mathematical knowledge in Statistics, Probability, Differentiation and Integration, Linear Algebra, and Geometry will be beneficial. Familiarity with Data Science libraries such as NumPy, SciPy, and Pandas, Azure Data Factory for data pipeline design, NLTK, Spacy, Hugging Face Transformers, Azure Text Analytics, OpenAI, Word2Vec, and BERT will also be advantageous. The base salary for this position ranges from $171,000 to $190,000 per annum for 40 hours per week, Monday to Friday. If you have any applications, comments, or questions regarding the job opportunity described, please contact Piyush Khemka, VP, Business Operations, at 111 Town Square Pl., Suite 1203, Jersey City, NJ 07310.,

Experience in ML, DL (Tensorflow, Keras, PyTorch), NLP, and NLU (NLTK, Spacy, Flair, etc.) Good understanding and relevant experience in ML techniques/ NLP/ Computer Vision tasks such as classification, clustering, deep learning, optimization methods, NER, dependency parsing, boundary detection, etc. Experience with Conversational AI frameworks like Rasa, Microsoft Bot etc Fluency in Python: Pandas, NumPy, SciPy, PySpark, PyTorch, Matplotlib Techniques: Regression analysis, Natural Language Processing (NLP) models, CNN DNN, Decision tree, Deep learning algorithms. Solid experience with one or more of the following programming languages: Scala, Java Experience with database technology such as MySQL, Postgres, Oracle and NoSQL databases Excellent working knowledge of Amazon Web Services (AWS) and ML services. Knowledge of AWS Sagemaker will be a plus AWS Certification will be a plus Good written and verbal communication skills Experience working with remote engineering teams

You should have a minimum of 5 - 8 years of experience in Data Science and Machine Learning. Your expertise should include in-depth knowledge of machine learning, Deep learning in Computer Vision (CV), and generative AI techniques. It is essential to be proficient in programming languages such as Python and frameworks like TensorFlow or PyTorch. A strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models is required. Experience with cloud platforms like Azure, AWS, or GCP and deploying AI solutions in a cloud environment is necessary. You should have expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, like fairness, transparency, and accountability in AI models and systems, is essential for this role. Collaborating with engineering teams to ensure seamless integration and deployment of AI models is crucial. Excellent problem-solving and analytical skills will be beneficial for translating business requirements into technical solutions. Strong communication and interpersonal skills are required to collaborate effectively with stakeholders at various levels. Understanding data privacy, security, and ethical considerations in AI applications is important. You should have a track record of driving innovation and staying updated with the latest trends in the field. Skills Required: - AI/ML, Machine Learning - TensorFlow, PyTorch - NLP techniques - BERT, GPT, Transformer models - Cloud Platforms: Azure, AWS, GCP - Data Engineering: data curation, cleaning, preprocessing - Trusted AI practices - Collaboration with engineering teams - Problem-solving and analytical skills - Communication and interpersonal skills - Data privacy, security, ethical considerations - Innovation and staying updated with the latest trends Mandatory Skills: - Generative AI techniques - NLP techniques - BERT, GPT, Transformer models - Azure Open AI GPT models, Hugging Face Transformers, Prompt Engineering - Python - TensorFlow, PyTorch - Deploying AI solutions in Azure, AWS, GCP - Deep learning in Computer Vision (CV), Large Language Model (LLM) Good To Have Skills: - DevOps and MLOps practices - Implementing CI/CD pipelines - Utilizing tools such as Docker, Kubernetes, and Git to build and manage AI pipelines.,

As a Senior Data Scientist specializing in Generative AI at our organization, you will play a crucial role in driving technical innovation and delivering impactful results within a team setting. You will be responsible for working with financial data, applying NLP techniques, refining prompt engineering strategies for LLMs, collaborating with stakeholders, developing and testing Python code for GenAI solutions, integrating with vector databases, monitoring MLOps pipelines, researching emerging GenAI technologies, and troubleshooting and debugging GenAI models in production. To excel in this role, you must possess a Master's degree in Computer Science, Data Science, or a related field, with a Ph.D. being preferred. You should have 8-12 years of experience in a Data Scientist or equivalent role, with at least 4 years of specialized experience in Generative AI. Additionally, you should have demonstrable experience in the full lifecycle of real-world, production-level GenAI project implementation. You must stay up-to-date with the rapidly evolving GenAI landscape, continuously learn and explore new tools and techniques, and effectively communicate technical concepts to non-technical stakeholders. Proficiency in Python, along with expertise in key libraries for AI/ML and GenAI applications such as TensorFlow, PyTorch, and Transformers, is mandatory. Experience in designing and implementing scalable API architectures for GenAI applications, along with a deep understanding of Machine Learning concepts, is essential. Preferred qualifications for this role include experience with MLOps, cloud computing platforms, conversational AI solutions, and contributions to research and publications in the field of Generative AI. As a Senior Data Scientist, you will be expected to demonstrate strong technical leadership and mentorship skills, as well as excellent communication and collaboration abilities. This job description provides a comprehensive overview of the responsibilities and qualifications required for the Senior Data Scientist position. If you are a highly motivated individual with a strong passion for Generative AI and possess the necessary technical skills and experience, we encourage you to apply for this role.,

As a Data Scientist specializing in Generative AI & ML Engineering, your primary responsibility will be to research and develop AI algorithms and models. You will be tasked with analyzing data, constructing predictive models, and employing machine learning techniques to address intricate problems. Your proficiency should encompass a range of skills including proficiency in languages/frameworks such as Fast API and Azure UI Search API (React), as well as expertise in databases and ETL tools like Cosmos DB and Data Factory Data Bricks. In addition, you should have a strong command of Python and R, familiarity with Azure Cloud Basics and Gitlab Pipeline, and experience in deploying AI solutions end-to-end. In addition to your proficient skills, you are expected to possess expert-level knowledge in areas such as Azure Open AI, Open AI GPT Family of models, and Azure Storage Account. Your expertise should extend to machine learning algorithms, deep learning frameworks like TensorFlow and PyTorch, and a solid foundation in mathematics including linear algebra, calculus, probability, and statistics. Furthermore, your role will require proficiency in data analysis tools such as Pandas, NumPy, and SQL, as well as strong statistical and probabilistic modeling skills. Experience with data visualization tools like Matplotlib, Seaborn, and Tableau, along with knowledge of big data technologies like Spark and Hive, will be essential for success in this position. Overall, your experience in AI-driven analytics and decision-making systems, coupled with your ability to develop and deploy AI frameworks and models, will be critical in delivering effective solutions to complex challenges.,

As a Data Science Team Lead, you will be responsible for leading a team of data scientists, planning data projects, and building analytic systems and predictive models. Your role will involve managing a team of data scientists and machine learning engineers, as well as engaging in pre-sales activities and building proposals. You will need to apply your strong expertise in machine-learning, deep learning, NLP, data mining, and information retrieval to design, prototype, and build the next-generation analytics engines and services. Your responsibilities will include leading data mining and collection procedures, ensuring data quality and integrity, interpreting and analyzing data problems, conceiving, planning, and prioritizing data projects, building analytic systems and predictive models, testing the performance of data-driven products, visualizing data and creating reports, and aligning data projects with organizational goals. You will need to understand business problems and design end-to-end analytics use cases, develop complex models and algorithms to drive innovation, conduct advanced statistical analysis to provide actionable insights, identify trends, and measure performance, collaborate with model developers to implement and deploy scalable solutions, and provide thought leadership by researching best practices, conducting experiments, and collaborating with industry leaders. To qualify for this role, you should have 8-15 years of experience in a statistical and/or data science role, proven experience as a Data Scientist or similar role, strong organizational and leadership skills, a degree in Computer Science, Data Science, Mathematics, or a similar field, deep knowledge and experience in Large Language Models (LLM), strong knowledge of Generative AI, deep knowledge of machine learning, statistics, optimization, or a related field, experience in Linear and non-Linear Regression models including Multiple and Multivariate, experience in Classification models including Ensemble techniques, experience in Unsupervised models including K-Means, DBSCAN, LOF, rich experience in NLP techniques, experience in Deep Learning techniques like CNN, RNN, GAN, Markov, strong real-time experience with at least one of the machine language software like R, Python, Matlab, good knowledge in Explainable AI, experience working with large data sets, simulation/optimization, and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, etc.), excellent written and verbal communication skills along with a strong desire to work in cross-functional teams, an attitude to thrive in a fun, fast-paced start-up environment, and an additional advantage of having experience in semi-structured databases like MongoDB, Cassandra, ArangoDB, Couchbase, GraphDB, etc. Optional programming skills in C, C++, Java, or .Net would be beneficial.,