557 Nltk Jobs - Page 9

Dear Candidate, We are hiring a Flask Developer to create lightweight and high-performance web services using Python. Key Responsibilities: Develop web APIs using Flask and deploy them on cloud or containers Use SQLAlchemy or MongoEngine for data access Write modular blueprints and configure middleware Perform request validation and error handling Work on REST/GraphQL integration with frontend teams Required Skills & Qualifications: Expertise in Flask , Python , and Jinja2 Familiar with Gunicorn , Docker , and PostgreSQL Understanding of JWT , OAuth , and API security Bonus: Experience in FastAPI or Flask-SocketIO 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

About KYFEX: KYFEX is a leading AI consulting firm, dedicated to harnessing the power of artificial intelligence to revolutionize business operations across the globe. Our expertise in Large Language Models (LLMs) positions us at the cutting edge of AI technology, enabling us to offer unparalleled solutions to our clients. As we continue to grow, we're seeking a skilled Remote LLM Engineer to join our dynamic team and contribute to our mission of driving innovation and excellence in AI. Job Responsibilities: Design, develop, and deploy advanced LLMs to meet the specific needs of our diverse client base. Collaborate with clients to understand their business challenges and tailor LLM solutions that provide strategic advantages. Stay abreast of developments in the field of LLMs and apply the latest research and techniques to our projects. Work closely with data scientists and engineers to integrate LLMs into broader AI solutions. Conduct thorough testing and validation to ensure the accuracy and reliability of LLM implementations. Optimize LLM performance for various computational environments, including cloud and edge computing platforms. Document all aspects of LLM development processes, including model architecture, training procedures, and deployment strategies. Provide technical guidance and support for LLM-related queries from clients and team members. Minimum Requirements: Bachelor's degree in Computer Science, AI, Linguistics, or a related technical field. 3+ years of hands-on experience in developing and deploying Large Language Models. Proficiency in Python, including experience with NLP libraries (e.g., Hugging Face Transformers, NLTK, spaCy). Strong understanding of neural network architectures, particularly those relevant to LLMs (e.g., Transformers). Demonstrated ability to work independently in a remote setting, managing projects from conception to completion. Excellent problem-solving skills and a detail-oriented mindset. Preferred Skills: Master's or Ph.D. in a relevant field. Experience with cloud services (AWS, Google Cloud, Azure) and ML deployment tools (Docker, Kubernetes). Familiarity with model fine-tuning and optimization techniques for LLMs. Proven track record of innovative solutions in the field of LLMs, evidenced by publications, patents, or software contributions. Strong communication skills, with the ability to explain complex AI concepts to non-expert audiences. Why Join KYFEX? Work at the forefront of AI technology with a team of experts passionate about innovation. Enjoy the flexibility and benefits of a fully remote position. Engage in challenging and meaningful projects that have a real-world impact. Benefit from a culture of continuous learning, professional development, and collaborative achievement. To Apply: Interested candidates are invited to submit their resume, a cover letter detailing their experience with LLMs, and any relevant project samples or GitHub links to careers@kyfex.com with "Remote LLM Engineer Application" as the subject line. KYFEX is committed to diversity and inclusion and encourages applications from all qualified individuals, including those from diverse backgrounds and underrepresented groups.

• Develop strategies/solutions to solve problems in logical yet creative ways, leveraging state-of-the-art machine learning, deep learning and GEN AI techniques. • Technically lead a team of data scientists to produce project deliverables on time and with high quality. • Identify and address client needs in different domains, by analyzing large and complex data sets, processing, cleansing, and verifying the integrity of data, and performing exploratory data analysis (EDA) using state-of-the-art methods. • Select features, build and optimize classifiers/regressors, etc. using machine learning and deep learning techniques. • Enhance data collection procedures to include information that is relevant for building analytical systems, and ensure data quality and accuracy. • Perform ad-hoc analysis and present results in a clear manner to both technical and non-technical stakeholders. • Create custom reports and presentations with strong data visualization and storytelling skills to effectively communicate analytical conclusions to senior officials in a company and other stakeholders. • Expertise in data mining, EDA, feature selection, model building, and optimization using machine learning and deep learning techniques. • Strong programming skills in Python. • Excellent communication and interpersonal skills, with the ability to present complex analytical concepts to both technical and non-technical stakeholders. Primary Skills : - Excellent understanding and hand-on experience of data-science and machine learning techniques & algorithms for supervised & unsupervised problems, NLP and computer vision and GEN AI. Good applied statistics skills, such as distributions, statistical inference & testing, etc. - Excellent understanding and hand-on experience on building Deep-learning models for text & image analytics (such as ANNs, CNNs, LSTM, Transfer Learning, Encoder and decoder, etc). - Proficient in coding in common data science language & tools such as R, Python. - Experience with common data science toolkits, such as NumPy, Pandas, Matplotlib, StatsModel, Scikitlearn, SciPy, NLTK, Spacy, OpenCV etc. - Experience with common data science frameworks such as Tensorflow, Keras, PyTorch, XGBoost,etc. - Exposure or knowledge in cloud (Azure/AWS). - Experience on deployment of model in production.

Job Title : Data Research Engineer Location: Remote (Hybrid for Chennai& Mumbai) Experience: 4 Years Responsibilities: ● Develop methods to leverage the potential of LLM and AI within the team. ● Proactive at finding new solutions to engage the team with AI/LLM, and streamline processes in the team. ● Be a visionary with AI/LLM tools and predict how the use of future technologies could be harnessed early on so that when these technologies come out, the team is ahead of the game regarding how it could be used. ● Assist in acquiring and integrating data from various sources, including web crawling and API integration. ● Stay updated with emerging technologies and industry trends. ● Explore third-party technologies as alternatives to legacy approaches for efficient data pipelines. ● Contribute to cross-functional teams in understanding data requirements. ● Assume accountability for achieving development milestones. ● Prioritize tasks to ensure timely delivery, in a fast-paced environment with rapidly changing priorities. ● Collaborate with and assist fellow members of the Data Research Engineering Team as required. ● Leverage online resources effectively like Stack Overflow, ChatGPT, Bard, etc., while considering their capabilities and limitations. Skills and Experience ● Bachelor's degree in Computer Science, Data Science, or a related field. Higher qualifications is a plus. ● Think proactively and creatively regarding the next AI/LLM technologies and how to use them to the team’s and company’s benefits. ● “Think outside the box” mentality. ● Experience prompting LLMs in a streamlined way, taking into account how the LLM can potentially “hallucinate” and return wrong information. ● Experience building agentic AI platforms with modular capabilities and autonomous task execution. (crewai, lagchain, etc.) ● Proficient in implementing Retrieval-Augmented Generation (RAG) pipelines for dynamic knowledge integration. (chromadb, pinecone, etc) ● Experience managing a team of AI/LLM experts is a plus: this includes setting up goals and objectives for the team and fine-tuning complex models. ● Strong proficiency in Python programming ● Proficiency in SQL and data querying is a plus. ● Familiarity with web crawling techniques and API integration is a plus but not a must. ● Experience in AI/ML engineering and data extraction ● Experience with LLMs, NLP frameworks (spaCy, NLTK, Hugging Face, etc.) ● Strong understanding of machine learning frameworks (Tensor Flow, PyTorch) ● Design and build AI models using LLMs ● Integrate LLM solutions with existing systems via APIs ● Collaborate with the team to implement and optimize AI solutions ● Monitor and improve model performance and accuracy ● Familiarity with Agile development methodologies is a plus. ● Strong problem-solving and analytical skills with attention to detail. ● Creative and critical thinking. ● Ability to work collaboratively in a team environment. ● Good and effective communication skills. ● Experience with version control systems, such as Git, for collaborative development. ● Ability to thrive in a fast-paced environment with rapidly changing priorities. ● Comfortable with autonomy and ability to work independently.

Job Summary XtraNet Technologies is seeking a highly experienced and results-oriented AI/ML Ops Professional to join our dynamic team in Gandhinagar. In this critical role, you will be instrumental in bridging the gap between our AI/ML development efforts and their seamless deployment and operationalization. You will leverage your deep expertise in developing, deploying, and managing machine learning models and algorithms to solve complex business challenges across diverse domains. As a sector expert, you will provide invaluable guidance on R&D initiatives and the strategic application of AI/ML technologies, including Natural Language Processing (NLP) and Generative AI, to enhance our service offerings and drive innovation for our clients. What You'll Do Lead and participate in the end-to-end lifecycle of machine learning models, from ideation and experimentation to deployment and monitoring in production environments. Design, develop, and implement scalable and efficient machine learning models and algorithms using relevant programming languages (e.g., Python), frameworks (e.g., TensorFlow, PyTorch, scikit-learn), and tools. Develop robust deployment pipelines using MLOps best practices and tools to ensure reliable and automated deployment of AI/ML models. Implement model versioning, rollback strategies, and continuous integration/continuous deployment (CI/CD) for AI/ML workflows. Establish and maintain robust monitoring systems to track the performance, health, and drift of deployed AI/ML models. Implement alerting mechanisms and proactive measures to identify and address potential issues in production AI/ML systems. Optimize the performance and scalability of deployed AI/ML models and infrastructure. Troubleshoot and resolve issues related to deployed AI/ML models and their underlying infrastructure. Serve as a subject matter expert in Artificial Intelligence and Machine Learning, providing guidance and insights to internal teams and clients on the application of AI/ML technologies. Conduct research and development (R&D) activities to explore and evaluate new AI/ML techniques, tools, and platforms, particularly in areas like Natural Language Processing (NLP) and Generative AI. Provide strategic guidance on the usage and implementation of NLP technologies (e.g., text classification, sentiment analysis, information extraction, language modeling) and Generative AI models for various business applications. Stay abreast of the latest advancements in AI/ML, MLOps, and related fields, and proactively share knowledge and best practices within the organization. Leverage your proven track record in solving complex business problems using AI/ML in diverse domains such as natural language processing, computer vision, or reinforcement learning Collaborate with business analysts and domain experts to understand business challenges and identify opportunities for AI/ML-driven solutions. Lead the exploration and prototyping of innovative AI/ML solutions to address client needs and enhance our service offerings. Work closely with data scientists, software engineers, infrastructure teams, and business stakeholders throughout the AI/ML lifecycle. Effectively communicate technical concepts and findings to both technical and non-technical audiences. Participate in technical design discussions and contribute to the overall AI/ML strategy and architecture. Document AI/ML workflows, deployment processes, and monitoring : Educational Background MCA (Master of Computer Applications) OR BE / B.Tech with specialization in Computers / Electronics & Communication (or equivalent) OR M.Sc. in Computer Science / IT Professional Experience Minimum of 7+ years of hands-on experience in developing, deploying, and managing machine learning models and algorithms in production environments. Technical Skills Strong proficiency in programming languages relevant to AI/ML (e.g., Python). Extensive experience with popular AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, Transformers). Solid understanding of machine learning algorithms and techniques across various domains (e.g., supervised learning, unsupervised learning, deep learning, reinforcement learning). Proven experience in developing and deploying NLP models (e.g., using libraries like NLTK, SpaCy, Hugging Face Transformers) and understanding of NLP concepts (e.g., text preprocessing, embeddings, sequence modeling). Familiarity with Generative AI models (e.g., GANs, VAEs, Large Language Models) and their potential applications. Strong understanding of MLOps principles and best practices, including model deployment, monitoring, and lifecycle management. (ref:hirist.tech)

Navaera Worldwide is a global, full-service firm that specializes in advanced knowledge management products and services designed to help Financial organizations improve operational efficiency, Manage Risk, Detect Fraud and gain competitive advantage. The privately held company has diverse clients around the world including major corporations in the financial services industry. As a brand, Navaera Worldwide provides complex business products and solutions to small and large organizations through Navaera Global Services. Navaera Worldwide has offices located in three continents with global headquarter based in New York. Other offices are in Toronto, Canada & Baroda, India. Designation: AI/ML (Associate Role) Experience Range: 2 Year to 4 Years Roles and Responsibilities: · Should be able to work in the areas of Data Analytics, Computer vision, NLP, OCR related task. · Data collection, Dataset preparation, Architecture modeling, model training/testing and deployment · Should have experience in handling digital data extraction and processing · Should be able to create training as well testing pipeline with different aspects of data · Must have experience in creating model architecture from scratch as well strong enough to transform pre-trained models · Should be very well equipped with the latest AI trend to keep the process up to date · Identify opportunities for process improvements, recommend system modifications. · Working with minimum of technical supervision and supplemental engineering support, while responding efficiently to multiple program priorities · Working well in a team environment and being able to effectively drive cross-team solutions that have complex dependencies and requirements · Experience with some of these methods: Regression, Decision Trees, CART, Random Forest, Boosting, Evolutionary Programming, Neural Networks, Fuzzy Systems, Bayesian Belief Networks, Support Vector Machines, Ensemble Methods, Association Rules, Singular Value Decomposition, Principal Component Analysis, Clustering, Artificial Intelligence, Deep learning etc Requisites: · B.E./B.Tech in Computer Science/Statistics/IT/ECE stream - M.S. or Ph.D. in Applied Mathematics, Statistics, Computer Science, Operations Research, Economics, or equivalent · Ex5perience in C/C++/Java/Python for developing machine learning/deep learning solutions · 2-4 years of experience in data science, machine learning/Deep learning · 2-4 years of experience in building and deploying Machine Learning solutions using various supervised/unsupervised ML algorithms · 2-4 years of hands-on experience with Python and any framework such as TensorFlow, PyTorch or MXnet along with ML libraries such as scikit-learn, NumPy, pandas, Keras etc, and/or natural language processing using NLTK, spaCy, Gensim, etc. · Good communication and interpersonal skills. · Experience in decision science tools and techniques will be added advantage · Strong problem solving and conceptual thinking, with ability to communicate even complex ideas in a succinct manner · Ability to work in a fast-paced and deadline driven environment · Strong work ethics like sense of collaboration and ownership. Job Type: Full-time Pay: ₹40,000.00 - ₹80,000.00 per month Benefits: Health insurance Provident Fund Schedule: Day shift Monday to Friday Application Question(s): Total how many years of experience do you have in AI/ML? Are you ready to work from office and relocate to Vadodara Gujarat? What is your notice period in days? What is your current annual CTC? What is your expected annual CTC? Work Location: In person

Minimum of (3+) years of experience in AI-based application development. Fine-tune pre-existing models to improve performance and accuracy. Experience with TensorFlow or PyTorch, Scikit-learn, or similar ML frameworks and familiarity with APIs like OpenAI or vertex AI Experience with NLP tools and libraries (e.g., NLTK, SpaCy, GPT, BERT). Implement frameworks like LangChain, Anthropics Constitutional AI, OpenAIs, Hugging Face, and Prompt Engineering techniques to build robust and scalable AI applications. Evaluate and analyze RAG solution and Utilise the best-in-class LLM to define customer experience solutions (Fine tune Large Language models (LLM)). Architect and develop advanced generative AI solutions leveraging state-of-the-art language models (LLMs) such as GPT, LLaMA, PaLM, BLOOM, and others. Strong understanding and experience with open-source multimodal LLM models to customize and create solutions. Explore and implement cutting-edge techniques like Few-Shot Learning, Reinforcement Learning, Multi-Task Learning, and Transfer Learning for AI model training and fine-tuning. Proficiency in data preprocessing, feature engineering, and data visualization using tools like Pandas, NumPy, and Matplotlib. Optimize model performance through experimentation, hyperparameter tuning, and advanced optimization techniques. Proficiency in Python with the ability to get hands-on with coding at a deep level. Develop and maintain APIs using Python's FastAPI, Flask, or Django for integrating AI capabilities into various systems. Ability to write optimized and high-performing scripts on relational databases (e.g., MySQL, PostgreSQL) or non-relational database (e.g., MongoDB or Cassandra) Enthusiasm for continuous learning and professional developement in AI and leated technologies. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Knowledge of cloud services like AWS, Google Cloud, or Azure. Proficiency with version control systems, especially Git. Familiarity with data pre-processing techniques and pipeline development for Al model training. Experience with deploying models using Docker, Kubernetes Experience with AWS Bedrock, and Sagemaker is a plus Strong problem-solving skills with the ability to translate complex business problems into Al solutions.

Navaera Worldwide is a global, full-service firm that specializes in advanced knowledge management products and services designed to help Financial organizations improve operational efficiency, Manage Risk, Detect Fraud and gain competitive advantage. The privately held company has diverse clients around the world including major corporations in the financial services industry. As a brand, Navaera Worldwide provides complex business products and solutions to small and large organizations through Navaera Global Services. Navaera Worldwide has offices located in three continents with global headquarter based in New York. Other offices are in Toronto, Canada & Baroda, India. Designation: AI/ML (Associate Role) Experience Range: 2 Year to 4 Years Roles and Responsibilities: · Should be able to work in the areas of Data Analytics, Computer vision, NLP, OCR related task. · Data collection, Dataset preparation, Architecture modeling, model training/testing and deployment · Should have experience in handling digital data extraction and processing · Should be able to create training as well testing pipeline with different aspects of data · Must have experience in creating model architecture from scratch as well strong enough to transform pre-trained models · Should be very well equipped with the latest AI trend to keep the process up to date · Identify opportunities for process improvements, recommend system modifications. · Working with minimum of technical supervision and supplemental engineering support, while responding efficiently to multiple program priorities · Working well in a team environment and being able to effectively drive cross-team solutions that have complex dependencies and requirements · Experience with some of these methods: Regression, Decision Trees, CART, Random Forest, Boosting, Evolutionary Programming, Neural Networks, Fuzzy Systems, Bayesian Belief Networks, Support Vector Machines, Ensemble Methods, Association Rules, Singular Value Decomposition, Principal Component Analysis, Clustering, Artificial Intelligence, Deep learning etc Requisites: · B.E./B.Tech in Computer Science/Statistics/IT/ECE stream - M.S. or Ph.D. in Applied Mathematics, Statistics, Computer Science, Operations Research, Economics, or equivalent · Ex5perience in C/C++/Java/Python for developing machine learning/deep learning solutions · 2-4 years of experience in data science, machine learning/Deep learning · 2-4 years of experience in building and deploying Machine Learning solutions using various supervised/unsupervised ML algorithms · 2-4 years of hands-on experience with Python and any framework such as TensorFlow, PyTorch or MXnet along with ML libraries such as scikit-learn, NumPy, pandas, Keras etc, and/or natural language processing using NLTK, spaCy, Gensim, etc. · Good communication and interpersonal skills. · Experience in decision science tools and techniques will be added advantage · Strong problem solving and conceptual thinking, with ability to communicate even complex ideas in a succinct manner · Ability to work in a fast-paced and deadline driven environment · Strong work ethics like sense of collaboration and ownership. Job Type: Full-time Pay: ₹40,000.00 - ₹80,000.00 per month Benefits: Health insurance Provident Fund Schedule: Day shift Monday to Friday Application Question(s): Total how many years of experience do you have in AI/ML? Are you ready to work from office and relocate to Vadodara Gujarat? What is your notice period in days? What is your current annual CTC? What is your expected annual CTC? Work Location: In person

About Gartner IT Step into a world where your creativity fuels innovation and your ideas drive transformation. At Gartner IT, we empower our team to build groundbreaking digital solutions that make a real difference for our colleagues and clients. Here, every voice matters, and every idea has the potential to shape the future. Are you ready to make an impact? About The Role As a Software Development – ML Specialist, you'll be at the forefront of designing, implementing, and supporting Python-based applications that align with our Research & Consulting Delivery strategy. Your expertise in NLP will be crucial in crafting solutions that propel Gartner's mission forward. What You’ll Do Pioneer new methodologies to rapidly deploy data-driven products and services, leveraging the power of ML and NLP. Transform unstructured data into actionable insights, setting the stage for advanced modelling. Lead architectural and technical design discussions, ensuring our NLP solutions hit strategic targets. Drive continuous improvement of NLP models through cutting-edge experimentation and optimization. Stay ahead of the curve by integrating the latest advancements in NLP and machine learning. Dive into generative AI technologies like OpenAI and LLaMA3 to supercharge our NLP capabilities. Craft detailed design specifications and rigorously review code to uphold our high standards. What You’ll Need Bring your 2-4 years of expertise in algorithms, statistics, and data processing to the table, along with hands-on experience in machine learning, deep learning, and NLP. Must Have Over 2 years of hands-on experience in Machine Learning and NLP. Mastery of Python programming. Expertise in data cleaning and exploratory data analysis. Deep understanding of algorithms, statistics, data mining, and NLP. Proficiency in NLP, including transformers. Skilled in Python libraries like Pandas and NumPy. Familiarity with deep learning libraries such as SpaCy, NLTK, TensorFlow, and Scikit-Learn. Experience with relational databases like Oracle, PostgreSQL, and MySQL. Strong analytical, problem-solving, and debugging skills. Good To Have Experience with generative AI technologies such as OpenAI, LLaMA3, etc. Knowledge of graph databases. Experience in deploying model serving APIs. Who You Are A master of time management, meeting deadlines with ease. A communicator who can bridge the gap between technical and business audiences. An organizational wizard with multitasking and prioritization prowess. A tech enthusiast eager to embrace and master new technologies and ideas. Driven by intellectual curiosity and a passion for staying ahead of tech trends. Committed to delivering high-quality projects on time and within budget. Think you might not meet every requirement? We encourage you to apply anyway. You could be the perfect fit for this role or others. Join us and be part of something extraordinary! Who are we? At Gartner, Inc. (NYSE:IT), we guide the leaders who shape the world. Our mission relies on expert analysis and bold ideas to deliver actionable, objective insight, helping enterprise leaders and their teams succeed with their mission-critical priorities. Since our founding in 1979, we’ve grown to more than 21,000 associates globally who support ~14,000 client enterprises in ~90 countries and territories. We do important, interesting and substantive work that matters. That’s why we hire associates with the intellectual curiosity, energy and drive to want to make a difference. The bar is unapologetically high. So is the impact you can have here. What makes Gartner a great place to work? Our sustained success creates limitless opportunities for you to grow professionally and flourish personally. We have a vast, virtually untapped market potential ahead of us, providing you with an exciting trajectory long into the future. How far you go is driven by your passion and performance. We hire remarkable people who collaborate and win as a team. Together, our singular, unifying goal is to deliver results for our clients. Our teams are inclusive and composed of individuals from different geographies, cultures, religions, ethnicities, races, genders, sexual orientations, abilities and generations. We invest in great leaders who bring out the best in you and the company, enabling us to multiply our impact and results. This is why, year after year, we are recognized worldwide as a great place to work . What do we offer? Gartner offers world-class benefits, highly competitive compensation and disproportionate rewards for top performers. In our hybrid work environment, we provide the flexibility and support for you to thrive — working virtually when it's productive to do so and getting together with colleagues in a vibrant community that is purposeful, engaging and inspiring. Ready to grow your career with Gartner? Join us. The policy of Gartner is to provide equal employment opportunities to all applicants and employees without regard to race, color, creed, religion, sex, sexual orientation, gender identity, marital status, citizenship status, age, national origin, ancestry, disability, veteran status, or any other legally protected status and to seek to advance the principles of equal employment opportunity. Gartner is committed to being an Equal Opportunity Employer and offers opportunities to all job seekers, including job seekers with disabilities. If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access the Company’s career webpage as a result of your disability. You may request reasonable accommodations by calling Human Resources at +1 (203) 964-0096 or by sending an email to ApplicantAccommodations@gartner.com . Job Requisition ID:98080 By submitting your information and application, you confirm that you have read and agree to the country or regional recruitment notice linked below applicable to your place of residence. Gartner Applicant Privacy Link: https://jobs.gartner.com/applicant-privacy-policy For efficient navigation through the application, please only use the back button within the application, not the back arrow within your browser.

What do you need for this opportunity? Must have skills required: TensorFlow, PyTorch, rag, LangChain Forbes Advisor is Looking for: Location - Remote (For candidate's from Chennai or Mumbai it's hybrid The Data Extraction Team is a brand-new team who plays a crucial role in our organization by designing, implementing, and overseeing advanced web scraping frameworks. Their core function involves creating and refining tools and methodologies to efficiently gather precise and meaningful data from a diverse range of digital platforms. Additionally, this team is tasked with constructing robust data pipelines and implementing Extract, Transform, Load (ETL) processes. These processes are essential for seamlessly transferring the harvested data into our data storage systems, ensuring its ready availability for analysis and utilization. A typical day in the life of a Data Research Engineer will involve coming up with ideas regarding how the company/team can best harness the power of AI/LLM, and use it not only simplify operations within the team, but also to streamline the work of the research team in gathering/retrieving large sets of data. The role is that of a leader who sets a vision for the future of AI/LLMs use within the team and the company. They think outside the box and are proactive in engaging with new technologies and developing new ideas for the team to move forward in the AI/LLM field. The candidate should also at least be willing to acquire some basic skills in scraping and data pipelining. Responsibilities: Develop methods to leverage the potential of LLM and AI within the team. Proactive at finding new solutions to engage the team with AI/LLM, and streamline processes in the team. Be a visionary with AI/LLM tools and predict how the use of future technologies could be harnessed early on so that when these technologies come out, the team is ahead of the game regarding how it could be used. Assist in acquiring and integrating data from various sources, including web crawling and API integration. Stay updated with emerging technologies and industry trends. Explore third-party technologies as alternatives to legacy approaches for efficient data pipelines. Contribute to cross-functional teams in understanding data requirements. Assume accountability for achieving development milestones. Prioritize tasks to ensure timely delivery, in a fast-paced environment with rapidly changing priorities. Collaborate with and assist fellow members of the Data Research Engineering Team as required. Leverage online resources effectively like StackOverflow, ChatGPT, Bard, etc., while considering their capabilities and limitations. Skills and Experience Bachelor's degree in Computer Science, Data Science, or a related field. Higher qualifications is a plus. Think proactively and creatively regarding the next AI/LLM technologies and how to use them to the teams and companys benefits. Think outside the box mentality. Experience prompting LLMs in a streamlined way, taking into account how the LLM can potentially hallucinate and return wrong information. Experience building agentic AI platforms with modular capabilities and autonomous task execution. (crewai, lagchain, etc.) Proficient in implementing Retrieval-Augmented Generation (RAG) pipelines for dynamic knowledge integration. (chromadb, pinecone, etc) Experience managing a team of AI/LLM experts is a plus: this includes setting up goals and objectives for the team and fine-tuning complex models. Strong proficiency in Python programming Proficiency in SQL and data querying is a plus. Familiarity with web crawling techniques and API integration is a plus but not a must. Experience in AI/ML engineering and data extraction Experience with LLMs, NLP frameworks (spaCy, NLTK, Hugging Face, etc.) Strong understanding of machine learning frameworks (TensorFlow, PyTorch) Design and build AI models using LLMs Integrate LLM solutions with existing systems via APIs Collaborate with the team to implement and optimize AI solutions Monitor and improve model performance and accuracy Familiarity with Agile development methodologies is a plus. Strong problem-solving and analytical skills with attention to detail. Creative and critical thinking. Ability to work collaboratively in a team environment. Good and effective communication skills. Experience with version control systems, such as Git, for collaborative development. Ability to thrive in a fast-paced environment with rapidly changing priorities. Comfortable with autonomy and ability to work independently.

We are looking for qualified people who can develop scalable solutions to complex real-world problems using AI/ML, Big Data, Statistics, Econometrics, and Optimization. Potential candidates should have excellent depth and breadth of knowledge in machine learning, data mining, and statistical modeling. They should possess the ability to translate a business problem into an analytical problem, identify the relevant data sets needed for addressing the analytical problem, recommend, implement, and validate the best suited analytical algorithm(s), and generate/deliver insights to stakeholders. Candidates are expected to regularly refer to research papers and be at the cutting-edge with respect to algorithms, tools, and techniques. The role is that of an individual contributor; however, the candidate is expected to work in project teams of 2 to 3 people and interact with Business partners on regular basis. Minimum Qualifications Bachelor’s degree in Analytics, Computer science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. 2+ years of hands-on experience in Python programming for data analysis, machine learning, and with libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, NLTK, spaCy, and Gensim. 2+ years of experience with both supervised and unsupervised machine learning techniques. 2+ years of experience with data analysis and visualization using Python packages such as Pandas, NumPy, Matplotlib, Seaborn, or data visualization tools like Dash or PowerBI. 1+ years' experience in SQL programming language and relational databases. Preferred Qualifications An MS/PhD in Analytics, Computer Science, Operational research, Statistics, Applied mathematics or in any other engineering discipline. PhD strongly preferred. Experience working with Google Cloud Platform (GCP) services, leveraging its capabilities for ML model development and deployment. Experience with Git and GitHub for version control and collaboration. Besides Python, familiarity with one more additional programming language (e.g., C/C++/Java) Strong background and understanding of mathematical concepts relating to probabilistic models, conditional probability, numerical methods, linear algebra, neural network under the hood detail. Experience working with large language models such GPT-4, Gemini, Palm, Llama-2, etc. Excellent problem solving, communication, and data presentation skills Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making Design and implement data analysis and AI/ML models, hypotheses, algorithms and experiments to support data-driven decision-making Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness

Job Description We are looking for qualified people who can develop scalable solutions to complex real-world problems using AI/ML, Big Data, Statistics, Econometrics, and Optimization. Potential candidates should have excellent depth and breadth of knowledge in machine learning, data mining, and statistical modeling. They should possess the ability to translate a business problem into an analytical problem, identify the relevant data sets needed for addressing the analytical problem, recommend, implement, and validate the best suited analytical algorithm(s), and generate/deliver insights to stakeholders. Candidates are expected to regularly refer to research papers and be at the cutting-edge with respect to algorithms, tools, and techniques. The role is that of an individual contributor; however, the candidate is expected to work in project teams of 2 to 3 people and interact with Business partners on regular basis. Responsibilities Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making Design and implement data analysis and AI/ML models, hypotheses, algorithms and experiments to support data-driven decision-making Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness Qualifications Minimum Qualifications Bachelor’s degree in Analytics, Computer science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. 2+ years of hands-on experience in Python programming for data analysis, machine learning, and with libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, NLTK, spaCy, and Gensim. 2+ years of experience with both supervised and unsupervised machine learning techniques. 2+ years of experience with data analysis and visualization using Python packages such as Pandas, NumPy, Matplotlib, Seaborn, or data visualization tools like Dash or PowerBI. 1+ years' experience in SQL programming language and relational databases. Preferred Qualifications An MS/PhD in Analytics, Computer Science, Operational research, Statistics, Applied mathematics or in any other engineering discipline. PhD strongly preferred. Experience working with Google Cloud Platform (GCP) services, leveraging its capabilities for ML model development and deployment. Experience with Git and GitHub for version control and collaboration. Besides Python, familiarity with one more additional programming language (e.g., C/C++/Java) Strong background and understanding of mathematical concepts relating to probabilistic models, conditional probability, numerical methods, linear algebra, neural network under the hood detail. Experience working with large language models such GPT-4, Gemini, Palm, Llama-2, etc. Excellent problem solving, communication, and data presentation skills

Minimum of (3+) years of experience in AI-based application development. Fine-tune pre-existing models to improve performance and accuracy. Experience with TensorFlow or PyTorch, Scikit-learn, or similar ML frameworks and familiarity with APIs like OpenAI or vertex AI Experience with NLP tools and libraries (e.g., NLTK, SpaCy, GPT, BERT). Implement frameworks like LangChain, Anthropics Constitutional AI, OpenAIs, Hugging Face, and Prompt Engineering techniques to build robust and scalable AI applications. Evaluate and analyze RAG solution and Utilise the best-in-class LLM to define customer experience solutions (Fine tune Large Language models (LLM)). Architect and develop advanced generative AI solutions leveraging state-of-the-art language models (LLMs) such as GPT, LLaMA, PaLM, BLOOM, and others. Strong understanding and experience with open-source multimodal LLM models to customize and create solutions. Explore and implement cutting-edge techniques like Few-Shot Learning, Reinforcement Learning, Multi-Task Learning, and Transfer Learning for AI model training and fine-tuning. Proficiency in data preprocessing, feature engineering, and data visualization using tools like Pandas, NumPy, and Matplotlib. Optimize model performance through experimentation, hyperparameter tuning, and advanced optimization techniques. Proficiency in Python with the ability to get hands-on with coding at a deep level. Develop and maintain APIs using Python's FastAPI, Flask, or Django for integrating AI capabilities into various systems. Ability to write optimized and high-performing scripts on relational databases (e.g., MySQL, PostgreSQL) or non-relational database (e.g., MongoDB or Cassandra) Enthusiasm for continuous learning and professional developement in AI and leated technologies. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Knowledge of cloud services like AWS, Google Cloud, or Azure. Proficiency with version control systems, especially Git. Familiarity with data pre-processing techniques and pipeline development for Al model training. Experience with deploying models using Docker, Kubernetes Experience with AWS Bedrock, and Sagemaker is a plus Strong problem-solving skills with the ability to translate complex business problems into Al solutions.

Min 1-3 yrs of exp in data science,NLP&Python Exp in PyTorch,Scikit-learn,and NLP libraries(NLTK,SpaCy,Hugging Face) Help deploy AI/ML solutions on AWS,GCP/Azure Exp in SQL for data manipulation & analysis Exp in Big Data processing Spark,Pandas,Dask

Roles & Responsibilities:  Understand and design solutions to Business problems leveraging Data science and AI  Should be able to understand and gather the requirement from Stakeholders.  Propose and execute the solution and present the deliverables to Stakeholders.  Manage and optimize the deliverables.  Mentor and Train new team members.  Develop POCs to enhance teams’ capability. Skillsets 1: Strong understanding of Math, Statistics and the theoretical foundations of Statistical & Machine Learning, Parametric and Non-parametric models.  Experience training and evaluating ML models. Perform statistical analysis of results and refine models.  Strong understanding of advanced data mining techniques, curating, processing and transforming data to produce sound datasets.  Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop.  Understanding of NLP techniques for text representation, semantic extraction techniques, data structures, and modelling.  Use various statistical techniques and ML methods to perform predictive modelling/classification for problems around client, distribution, sales, client profiles, segmentation and provide relevant & actionable recommendations/insights for the business.  Stronghold on Visualization tool (or libraries) like SAS Visual Analytics, Tableau, Python, etc.  Expert in working on Statistical tools (Python/R/SAS).  Experience with cloud computing infrastructure like AWS/Azure/GCP.  Able to develop, test and deploy models on Cloud/Web. Skillsets 2: 1.BERT and Transformer Models: Proficiency in working with BERT and other transformer-based models for various NLP tasks, such as text classification, named entity recognition, question answering, and text generation. Familiarity with fine-tuning BERT on specific downstream tasks using techniques like transfer learning and domain adaptation. 2.Natural Language Processing (NLP): Strong understanding of NLP techniques, including text preprocessing, information extraction, text representation, sentiment analysis, named entity recognition, topic modeling, and information retrieval. 3.Machine Learning and Deep Learning: Proficiency in machine learning and deep learning algorithms and frameworks, such as TensorFlow, PyTorch, scikit-learn, or Keras. Ability to train and evaluate NLP models using supervised and unsupervised learning techniques. 4.Programming Languages: Proficiency in programming languages commonly used in NLP, such as Python, Java, or C++. Ability to write efficient and clean code for data manipulation, model development, and deployment. 5.NLP Libraries and Tools: Familiarity with popular NLP libraries and tools, such as NLTK, SpaCy, Gensim, Stanford NLP, or CoreNLP. Ability to leverage existing librariesfor various NLP tasks and adaptthem to specific use cases. 8.Continuous Learning: Proactive approach to staying updated with the latest advancements in NLP research, technologies, and best practices. Active participation in conferences, workshops, and online forums. Qualifications  MCA/BE/B. Tech. /MBA/M.Stat./M.sc. or equivalent degree in Quant. from reputed institute.  3+ years of relevant experience. Soft Skills:  Excellent organizational skills and ability to prioritize wide range of tasks  Demonstrated initiative and creativity - ability to influence (add value)  Strong interpersonal, communication, organizational and planning skills.

Job Responsibilities: Design, develop and implement solutions for a wide range of NLP use cases involving classification, extraction and search on unstructured text data Create and maintain state of the art scalable NLP solutions in Python/ Java/ Scala for multiple business problems. This involves: Choosing most appropriate NLP technique(s) based on business needs and available data Performing data exploration and innovative feature engineering Training and tuning a variety of NLP models / solutions which include regular expressions, traditional NLP models as well as SOTA transformer based models Augmenting models by integrating domain specific ontologies and/or external databases Reporting and Monitoring the solution outcome Work experience with document-oriented databases such as MongoDB Collaborate with ML engineering team to deploy NLP solutions in production - both on premise as well as cloud deployment Interact with clients and internal business teams to perform solution feasibility as well as design and develop solutions Open to working across different domains – Insurance, Healthcare and Financial Services etc. Required Skills: Experience (including graduate school) on training machine learning models, applying and developing text mining and NLP techniques Exposure to OCR and computer vision Experience in extracting content from documents is preferred Experience (including graduate school) with Natural Language Processing techniques is required Hands on experience with Natural Language Processing tools such as Stanford CORE-NLP, NLTK, spaCy, Gensim, Textblob etc. Experience/ Familiarity with document clustering in supervised un un-supervised scenarios Expertise in at least two of the state of the art techniques in NLP like BERT, GPT, XL Net etc. Applied experience of machine learning algorithms using Python Organized, self-motivated, disciplined and detail oriented Production level coding experience in Python is required Ability to read recent ML research papers and adapt those models to solve real-world problems Experience with any deep learning framework, including Tensorflow, Caffe, MxNet, Torch, Theano Experience with optimization on GPUs (a plus) Hands on experience with using cloud technologies on AWS/ Microsoft Azure is preferred

About The Role This is a unique opportunity to join our fast-growing Global Product Management Data Science team. You will be working with the team managing ‘The Client Experience Digital Platform’ which is the go-to place for all clients to interact with Gartner to get value. Our clients are IT and business leaders around the world. They expect to get help from Gartner on their most critical priorities. The Digital Platform is embedded in their workflows to help them on every step of their journey. Our mission is to deliver tremendous client value by building scalable, intelligent digital products and solutions. We are constantly looking for product management, UX and data science leaders to help us accelerate innovation to disrupt the marketplace and disrupt ourselves. What You Will Do Work on Data science projects in close collaboration with the Data Engineering team, Application development team, Product owners and business leaders to deliver high value business capabilities Solve ‘Search’ value stream problems and help improve Gartner’s client experience in finding the most meaningful and valuable insights Build user query understanding and intent refinement models to refine query to content similarity Build and incorporate LLMs in addition to vector search capabilities Be responsible for high quality data science solutions with respect to accuracy and coverage. Be accountable for solutions’ scalability, stability, and business adoption Responsible for maintaining proper documentation and further code-reusability principles Responsible for ownership of algorithms and its enhancements/optimizations as per business requirement Collaborate with Director, Data Science in long term vision, strategy, and solution roadmap to align with bigger business objectives and mission critical priorities of the organization Responsible to pitch ideas, present solutions and influence senior leaders with strong business value propositions Stay on top of fast-moving AI/ML models and technologies. Understand and follow disruptive data science solutions Collaborate with engineering and product teams to launch MVPs and iterate quickly Independently plan and drive data science projects that deliver clear business value What You Will Need 6-8 years hands-on experience building predictive models, search systems, or other machine learning/artificial intelligence applications to drive business impact Bachelor’s degree required while a master’s degree in a quantitative field (math, computer science, engineering, etc.) is strongly preferred Demonstrated ability to translate quantitative analysis into actionable business strategies. Strong communication skills in technical and business domains Working experience in some of the following data science areas: Machine Learning and Predictive modeling Text mining and Natural Language Processing Search or Recommendation systems Data analytics with multi-dimensional data Generative models Strong working knowledge of Lean product principles, software development lifecycle, and machine learning life cycle Practical, intuitive problem solver with a demonstrated ability to translate business objectives into actionable data science tasks and translate quantitative analysis into actionable business strategies Ability to implement latest ML research to improve our current algorithms Experience and proficiency with Python, machine learning tools (e.g., scikit-learn, spacy, nltk), deep learning (e.g., pytorch, tensorflow), statistical packages (e.g., Scipy), SQL/relational databases (e.g., Oracle) and NoSQL databases (e.g., MongoDB, graph database), distributed machine learning (spark), Linux and shell scripting Experience with cloud computing services such as AWS or Azure ML Ability to work collaboratively across product, data science and technical stakeholders Ability to work in a culture that thrives on feedback and seeks opportunities to stretch outside comfort zone Bias for action and client outcome oriented Who are we? At Gartner, Inc. (NYSE:IT), we guide the leaders who shape the world. Our mission relies on expert analysis and bold ideas to deliver actionable, objective insight, helping enterprise leaders and their teams succeed with their mission-critical priorities. Since our founding in 1979, we’ve grown to more than 21,000 associates globally who support ~14,000 client enterprises in ~90 countries and territories. We do important, interesting and substantive work that matters. That’s why we hire associates with the intellectual curiosity, energy and drive to want to make a difference. The bar is unapologetically high. So is the impact you can have here. What makes Gartner a great place to work? Our sustained success creates limitless opportunities for you to grow professionally and flourish personally. We have a vast, virtually untapped market potential ahead of us, providing you with an exciting trajectory long into the future. How far you go is driven by your passion and performance. We hire remarkable people who collaborate and win as a team. Together, our singular, unifying goal is to deliver results for our clients. Our teams are inclusive and composed of individuals from different geographies, cultures, religions, ethnicities, races, genders, sexual orientations, abilities and generations. We invest in great leaders who bring out the best in you and the company, enabling us to multiply our impact and results. This is why, year after year, we are recognized worldwide as a great place to work . What do we offer? Gartner offers world-class benefits, highly competitive compensation and disproportionate rewards for top performers. In our hybrid work environment, we provide the flexibility and support for you to thrive — working virtually when it's productive to do so and getting together with colleagues in a vibrant community that is purposeful, engaging and inspiring. Ready to grow your career with Gartner? Join us. The policy of Gartner is to provide equal employment opportunities to all applicants and employees without regard to race, color, creed, religion, sex, sexual orientation, gender identity, marital status, citizenship status, age, national origin, ancestry, disability, veteran status, or any other legally protected status and to seek to advance the principles of equal employment opportunity. Gartner is committed to being an Equal Opportunity Employer and offers opportunities to all job seekers, including job seekers with disabilities. If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access the Company’s career webpage as a result of your disability. You may request reasonable accommodations by calling Human Resources at +1 (203) 964-0096 or by sending an email to ApplicantAccommodations@gartner.com . 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Job Summary: We’re looking for a passionate and driven Machine Learning Engineer with 1 year of hands-on experience working with Large Language Models (LLMs), Natural Language Processing (NLP), Python, and web scraping. The ideal candidate should have practical exposure to real-world NLP tasks and be comfortable fine-tuning models and building end-to-end pipelines. ✅ Key Responsibilities: Work on fine-tuning and integrating LLMs for various use cases. Build and maintain NLP pipelines for text classification, summarization, or Q&A systems. Perform web scraping to gather structured and unstructured data using Python libraries like BeautifulSoup, Scrapy, or Selenium. Collaborate with the team to deploy and test ML models in production environments. Continuously evaluate model performance and optimize based on feedback. 🧰 Requirements: 1 year of hands-on experience in Machine Learning, specifically in NLP and LLMs. Strong programming skills in Python. Experience with web scraping tools and libraries. Familiarity with ML libraries such as Hugging Face Transformers, spaCy, NLTK, or Scikit-learn. Basic understanding of model evaluation and tuning techniques. Good problem-solving skills and ability to work independently. 💡 Good to Have: Experience with prompt engineering or RAG-based architectures. Knowledge of API integration for AI/LLM services (e.g., OpenAI, Cohere, etc.).

Key Responsibilities Team Leadership : Lead, guide, and mentor a team of AI/ML engineers and data scientists, fostering a collaborative, innovative, and productive work environment. Clean Code & Development : Write clean, maintainable, and error-free Python code for developing robust machine learning systems. Model Engineering : Efficiently design, build, and deploy machine learning models and end-to-end solutions. Cross-Functional Collaboration : Work closely with diverse technical teams to ensure timely and efficient delivery of AI/ML projects. Data Science Lifecycle : Implement end-to-end data science processes, including data preprocessing, exploratory analysis, modeling, evaluation, and deployment. Database Management : Work proficiently with SQL and NoSQL databases to manage and retrieve data effectively. API Development : Develop and integrate RESTful APIs using Python web frameworks (e.g., Flask, Django). Debugging & Optimization : Diagnose issues and optimize existing code for performance improvements. Agile Methodologies : Follow Agile/Scrum software development lifecycle practices consistently. LLM & RAG Implementation : Design, develop, fine-tune, and deploy AI models focusing on Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). Model Validation & Evaluation : Conduct training, validation, and evaluation experiments, refining models based on statistical analysis and performance metrics. Security & Compliance : Ensure that AI/ML solutions adhere to security best practices and data privacy regulations (e.g., GDPR). Technical Qualifications Python Expertise : 35 years of hands-on experience with Python programming. ML/DL Experience : 35 years of experience building, training, and deploying Machine Learning and Deep Learning models. Deep Learning Frameworks : Proficiency with TensorFlow, PyTorch, and Keras. Web Frameworks : Solid experience with Python web frameworks (Flask, Django) for API development. Core Libraries : Strong expertise in NumPy, Pandas, Matplotlib, Scikit-learn, SpaCy, NLTK, and HuggingFace Transformers. Algorithms & Techniques : Deep understanding of ML/DL algorithms, with advanced techniques in NLP and/or Computer Vision. Production-Grade AI : Proven experience designing and deploying AI solutions leveraging LLMs and RAG. NLP & Conversational AI : Hands-on expertise in text representation, semantic extraction, sentiment analysis, and conversational AI. Concurrency : Practical knowledge of multithreading, concurrency, and asynchronous programming in Python. Database Proficiency : Advanced skills in SQL (PostgreSQL, MySQL, SQLite, MariaDB) and NoSQL (MongoDB) databases. Deployment & MLOps : Experience with containerization (Docker/Kubernetes), cloud platforms (AWS, Azure, GCP), and familiarity with MLOps principles for CI/CD, monitoring, and logging. Version Control : Proficient understanding of Git and Bitbucket for software version control. C++ : Experience with C++ development is a plus. Soft Skills Analytical Thinking : Strong analytical and structured problem-solving capabilities. Proactive Problem-Solving : Logical reasoning and a hands-on approach to debugging and optimization. Team Collaboration : Effective interpersonal skills to work seamlessly with cross-functional teams. Clear Communication : Excellent ability to articulate technical concepts to diverse audiences. F- Continuous Learning : Commitment to staying current on emerging trends in AI/ML, NLP, and Computer Vision. (ref:hirist.tech)

Role Outline We are looking for a Document Extraction and Inference Engineer with expertise in traditional machine learning algorithms and rule based NLP techniques. The ideal candidate will have a strong foundation in document processing, structured data extraction, and inference modeling using classical ML approaches. You will work on designing, implementing, and optimizing document extraction pipelines for various applications, ensuring accuracy and efficiency. Role & Responsibilities: Develop and implement document parsing and structured data extraction techniques. Utilize OCR (Optical Character Recognition) and pattern-based NLP for text extraction. Optimize rulebased and statistical models for document classification and entity recognition. Design feature engineering strategies for improving inference accuracy. Work with structured and semistructured data (PDFs, scanned documents, XML, JSON). Implement knowledgebased inference models for decisionmaking applications. Collaborate with data engineers to build scalable document processing pipelines. Conduct error analysis and improve extraction accuracy through iterative refinements. Stay updated with advancements in traditional NLP and document processing techniques. Required Qualifications: Bachelors or Masters degree in Computer Science, AI, Machine Learning, or related field. 3+ years of experience in document extraction and inference modeling. Strong proficiency in Python and ML libraries (Scikit-learn, NLTK, OpenCV, Tesseract). Expertise in OCR technologies, regular expressions, and rule-based NLP. Experience with SQL and database management for handling extracted data. Knowledge of probabilistic models, optimization techniques, and statistical inference. Familiarity with cloud-based document processing (AWS Textract, Azure Form Recognize Preferred Qualifications: Experience with graphbased document analysis and knowledge graphs. Knowledge of time series analysis for document-based forecasting. Exposure to reinforcement learning for adaptive document processing. Understanding of the credit / loan processing domain

Area(s) of responsibility About Us Birlasoft, a global leader at the forefront of Cloud, AI, and Digital technologies, seamlessly blends domain expertise with enterprise solutions. The company’s consultative and design-thinking approach empowers societies worldwide, enhancing the efficiency and productivity of businesses. As part of the multibillion-dollar diversified CKA Birla Group, Birlasoft with its 12,000+ professionals, is committed to continuing the Group’s 170-year heritage of building sustainable communities. Location: Any BSL Location Job Description Bachelor/master’s degree in computer science, Artificial Intelligence, Machine Learning, or a related field with 15+ years of experience 2+ years of experience in developing and implementing Generative AI models, with a strong understanding of techniques such as GPT, T5 and BERT Experience with LLMs OpenAI GPT and others Experience in latest GenAI application development frameworks Project management and governance experience preferred. Candidates with Technical and management skills given stronger preference. Life sciences experience preferred. Experience with handling customers at SLT and VP level. Proficiency in Python and have 8+ years of experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras Experience in developing Fast API and documentations Experience working with SQL, NoSQL, Elastic, Files etc. Strong knowledge of data structures, algorithms, and software engineering principles Familiarity with cloud-based platforms and services, such as AWS (must), GCP, or Azure 8+ years of experience with advanced natural language processing ( NLP ) techniques and tools, such as SpaCy, NLTK, or Hugging Face Familiarity with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly Significant experience architecting cutting-edge MLOps systems in enterprise environments Knowledge of software development methodologies, such as Agile or Scrum Excellent problem-solving skills , with the ability to think critically and creatively to develop innovative AI solutions. Strong communication skills , with the ability to effectively convey complex technical concepts to a diverse audience Proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Able to execute thought leadership. Responsibilities Design, develop, and implement Generative AI models and algorithms, using techniques such as GPT, T5, BERT Collaborate with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals Conduct research to stay up-to-date with the latest advancements in Generative AI , machine learning, and deep learning techniques, and identify opportunities to integrate them into customer products and services Optimize Generative AI models for improved performance, scalability, and efficiency Develop and maintain AI pipelines, including data preprocessing, feature extraction, model training, and evaluation Contribute to the establishment of best practices and standards for Generative AI development within the organization

Roles and Responsibilities: As a, Data scientist / Senior Data scientist you will solve some of the most impactful business problems for our clients using a variety of AI and ML technologies. You will collaborate with business partners and domain experts to design and develop innovative solutions on the data to achieve predefined outcomes. Engage with clients to understand current and future business goals and translate business problems into analytical frameworks Develop custom models based on in-depth understanding of underlying data, data structures, and business problems to ensure deliverables meet client needs Create repeatable, interpretable and scalable models Effectively communicate the analytics approach and insights to a larger business audience Collaborate with team members, peers and leadership at Tredence and client companies Qualification: Bachelor's or Master's degree in a quantitative field (CS, machine learning, mathematics, statistics) or equivalent experience. 3+ years of experience in data science, building hands-on ML models Experience with LMs (Llama (1/2/3), T5, Falcon, Langchain or framework similar like Langchain) Candidate must be aware of entire evolution history of NLP (Traditional Language Models to Modern Large Language Models), training data creation, training set-up and finetuning Candidate must be comfortable interpreting research papers and architecture diagrams of Language Models Candidate must be comfortable with LORA, RAG, Instruct fine-tuning, Quantization, etc. Experience leading the end-to-end design, development, and deployment of predictive modeling solutions. Excellent programming skills in Python. Strong working knowledge of Python’s numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, Jupyter, etc. Advanced SQL skills with SQL Server and Spark experience. Knowledge of predictive/prescriptive analytics including Machine Learning algorithms (Supervised and Unsupervised) and deep learning algorithms and Artificial Neural Networks Experience with Natural Language Processing (NLTK) and text analytics for information extraction, parsing and topic modeling. Excellent verbal and written communication. Strong troubleshooting and problem-solving skills. Thrive in a fast-paced, innovative environment Experience with data visualization tools — PowerBI, Tableau, R Shiny, etc. preferred Experience with cloud platforms such as Azure, AWS is preferred but not require

About The Company Axis My India is Indias foremost Consumer Data Intelligence Company, which in partnership with Google is building a single-stop People Empowerment Platform, the a app, that aims to change peoples awareness, accessibility, and utilization of a slew of services. At Axis, we are dedicated to making a tangible impact on the lives of millions. If you're passionate about creating meaningful changes and aren't afraid to get your hands dirty, we want you on our team!. Role Overview The Senior Analyst will manage, analyze, and interpret data to drive business decisions across multiple projects, including the a app and other initiatives. This position requires advanced statistical expertise, proficiency in analytics tools, and the ability to communicate insights effectively to product and research teams. Senior Analyst will be leading the team of 3 to 5 people. Key Responsibilities Conduct relevant statistical tests to validate hypotheses and ensure data-driven outcomes. Design, develop, and deploy advanced statistical and machine learning models to analyze complex datasets, including those from the a app and other projects. Perform data fusion activities by leveraging techniques to merge, reconcile, and analyze information from disparate systems and formats. Employing modern weighing and projection methods to answer key business questions and predict future trends. Design and manage interactive dashboards using Power BI for real-time data visualization. Perform Exploratory Data Analysis (EDA) to identify patterns, anomalies, and opportunities. Collaborate with product and research teams by providing feedback based on analytical findings. Analyze survey data to extract actionable insights and trends. Define and create Key Performance Indicators (KPIs) based on APP data. Serve as the gatekeeper for data maps, ensuring data integrity and accessibility for stakeholders. Develop and maintain MIS dashboards. Required Skills & Qualifications MSc in Statistics or a related quantitative field. Strong experience in statistical analysis, predictive modelling and data validation. Proficiency in Python and Power BI are necessary with experience of working in libraries used for numerical and text analysis such as Pandas, Numpy, PySpark, NLTK, SpaCy, Scikit-Learn, Genism. Experience of working with both parametric and non-parametric methods. Advanced knowledge of survey analytics and EDA techniques. Excellent communication skills for cross-functional collaboration. Experience with MIS dashboard development and KPI creation. High attention to detail and commitment to data quality. Preferred Experience Experience working with app-based data and multi-project analytics environments. Familiarity with analyzing multiple survey data. Background in creating and managing KPIs aligned with business objectives. Exposure to big data technologies and cloud-based data platforms. Ability to work collaboratively in cross-functional teams involving product, research, and engineering stakeholders. Must have led the data science team in past. Experience of developing algorithms using combination of Data Science and statistics. Requirements Technical Skills : Data Analysis & Statistical Expertise : Ability to manipulate large datasets, perform data cleaning, and run relevant statistical tests to validate findings and ensure data accuracy. Proficiency in Data Visualization Tools : Advanced skills in Power BI to design, develop, and maintain interactive, user-friendly MIS dashboards with features like advanced calculations, parameters, joins, and blending. Advanced Excel Skills : Expertise in Excel formulas, pivot tables, macros, and dashboard creation to complement BI tools and automate reporting tasks. Programming Knowledge : Familiarity with Python for data manipulation, exploratory data analysis (EDA), and predictive modelling enhances analytical capabilities. Data Validation & Quality Assurance : Skill in validating data integrity and consistency to ensure reliable dashboard outputs. Analytical & Business Skills Critical Thinking & Problem Solving : Strong analytical mindset to interpret complex data, identify trends, and provide actionable insights. Business Acumen : Understanding of the business context to translate data insights into relevant recommendations and feedback for product and research teams. Communication & Collaboration Effective Communication : Ability to present complex data insights clearly and succinctly to internal stakeholders, including senior executives, through reports, dashboards and presentations. Stakeholder Management : Experience collaborating with cross-functional teams, gathering requirements, and incorporating feedback to refine dashboards and reports. Coaching & Mentoring : Mentor and guide junior data scientists and analysts, fostering a culture of continuous learning and innovation. Benefits Competitive salary and benefits package. Opportunity to make significant contributions to a dynamic company. Evening snacks are provided by the company to keep you refreshed towards the end of the day. Walking distance from Chakala metro station, making commuting easy and convenient. At Axis My India, we value discipline and focus : Our team members wear uniforms, adhere to a no-mobile policy during work hours, and work from our office with alternate Saturdays off. If you thrive in a structured environment and are committed to excellence, we encourage you to apply. (ref:hirist.tech)

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.

Role & responsibilities Conduct relevant statistical tests to validate hypotheses and ensure data-driven outcomes. Design, develop, and deploy advanced statistical and machine learning models to analyze complex datasets, including those from the a app and other projects. Perform data fusion activities by leveraging techniques to merge, reconcile, and analyze information from disparate systems and formats. Employing modern weighing and projection methods to answer key business questions and predict future trends. Design and manage interactive dashboards using Power BI for real-time data visualization. Perform Exploratory Data Analysis (EDA) to identify patterns, anomalies, and opportunities. Collaborate with product and research teams by providing feedback based on analytical findings. Analyze survey data to extract actionable insights and trends. Define and create Key Performance Indicators (KPIs) based on APP data. Serve as the gatekeeper for data maps, ensuring data integrity and accessibility for stakeholders. Develop and maintain MIS dashboards Mentor the team and improve the overall performance of the team Preferred candidate profile Key skills / Abilities MSc in Statistics or a related quantitative field. Strong experience in statistical analysis, predictive modelling and data validation. Proficiency in Python and Power BI are necessary with experience of working in libraries used for numerical and text analysis such as Pandas, Numpy, PySpark, NLTK, SpaCy, Scikit-Learn, Genism. Experience of working with both parametric and non-parametric methods. Advanced knowledge of survey analytics and EDA techniques. Excellent communication skills for cross-functional collaboration. Experience with MIS dashboard development and KPI creation. High attention to detail and commitment to data quality. Experienced Required Experience working with app-based data and multi-project analytics environments. Familiarity with analyzing multiple survey data. Background in creating and managing KPIs aligned with business objectives. Exposure to big data technologies and cloud-based data platforms. Ability to work collaboratively in cross-functional teams involving product, research, and engineering stakeholders. Must have lead the data science team in past Experience of developing algorithm using combination of Data Science and statistics