349 Nlp Jobs - Page 7

Management Level :06 Senior Manager Location :Bangalore/ Gurgaon/ Chennai/ Pune/ Hyderabad/ Mumbai Must have skills: Contact Center Transformation, Customer Service Strategy, Technology and Innovation Good to have skills: Industry Trends and Disruptions, Claims Management Expertise, General Regulatory and Compliance Expertise, Digital Literacy, Value architect, Product Owner, Business Analyst, Digital transformation, Business case creations for Contact center transformation. Job Summary : We are seeking a highly motivated and experienced Senior Manager with deep expertise in customer service transformation, with a specific focus on leveraging technology, AI, and innovation within the insurance sector. Critically, this role requires demonstrable experience working within an insurance firm in a customer service transformation capacity. This role will be pivotal in leading and driving initiatives to revolutionize customer experience, optimize service delivery, and implement cutting-edge solutions. The ideal candidate will be a thought leader with a proven track record of success in customer service transformation, particularly in the application of technology and AI within an insurance company environment. If this role resonates with you, we invite you to discover many exciting global opportunities available within Accenture Strategy & Consultings Customer, Sales & Service practice. Roles & Responsibilities: Subject Matter Expertise: Serve as subject matter expert (SME) on insurance customer service trends, best practices, technologies (including AI, automation, and analytics), and general regulatory guidelines. This includes staying abreast of evolving customer expectations, digital transformation trends, emerging technologies, and the competitive landscape within the insurance industry. Customer Experience Vision & Strategy: Develop and champion a forward-thinking customer experience vision and strategy, tailored to the insurance industry, with a focus on leveraging technology and AI. This includes defining customer journeys, identifying pain points, and designing innovative service models informed by firsthand experience within an insurance organization. Customer Service KPI Mastery: Possess a strong understanding of key customer service performance indicators (KPIs) in the Insurance sector, including customer satisfaction (CSAT), Net Promoter Score (NPS), first call resolution (FCR), average handle time (AHT), and cost per contact, Digital and Omni channel KPIs, Claims Specific KPIs, Employee Satisfaction, etc. Be able to analyze and interpret these KPIs to identify areas for improvement. AI & Automation Implementation: Lead the exploration, evaluation, and implementation of AI-powered solutions to enhance customer service, such as AI-driven chatbots, virtual assistants, personalized recommendations, and automated claims processing. This requires an understanding of how these technologies integrate within existing insurance systems and workflows. Digital Transformation Leadership: Drive the digital transformation of customer service, including the implementation of self-service portals, mobile apps, CRM systems, and other relevant technologies. Focus on creating seamless omnichannel experiences. Experience integrating these technologies into an insurance firm's ecosystem is essential. Innovation & Emerging Tech: Identify and evaluate emerging technologies and innovative solutions that can enhance customer service in insurance, such as natural language processing (NLP), machine learning (ML), etc. The ideal candidate will have a network within the insurance technology space. Process Optimization & Automation: Analyze and optimize existing customer service processes to improve efficiency, reduce costs, and enhance customer satisfaction, with a focus on automation and technology enablement. This requires a deep understanding of insurance operations and workflows. Technology Evaluation & Vendor Management: Evaluate and recommend customer service technologies and platforms, including AI-powered solutions. Oversee the implementation and integration of these systems, ensuring seamless functionality and user adoption. Manage relationships with third-party vendors. Data Analytics & Reporting: Utilize data analytics to measure customer service performance, identify areas for improvement, track the effectiveness of transformation initiatives, and demonstrate the ROI of technology investments. Develop and present reports on key metrics and trends. Experience using insurance-specific data sources Experience with insurance-specific KPIs is essential. Client Engagement: Consult with clients on their customer service strategies and provide expert guidance on transformation initiatives, with a focus on technology and AI adoption. This may involve leveraging knowledge of specific insurance regulations and compliance requirements. Pre-sales activities: Lead and contribute to pre-sales activities including response to RFPs, creating proofs of concept, creating effective presentations, demonstrating solutions during client orals, effort and cost estimation process, etc. Thought Leadership :Lead practice-specific initiatives including creating points of view, creating reusable assets on contact center space, performing analysis on industry research and market trends and bringing in innovative solutions, etc. Continuous Learning :Ability to take new challenges and to be an enthusiastic learner. Professional & Technical Skills: MBA from a tier 1 or tier 2 institute. 10+ years of digital experience and solid knowledge of industry tools and understanding of designing intuitive and responsive user experiences. Experience in working for an Insurance company in Service Transformation role. Solid experience developing interactive models using conversational platforms and deep understanding of customer-centered design processes with consulting experience (optional). Experience of working with business stakeholders across multiple geographic areas, with different priorities and requirements. Ability to work in high-paced and complex projects and understand industry-specific customer service processes, operations, and functional needs. Strong stakeholder management skills and a proactive approach to issue and risk resolution. Bachelors degree in related field or equivalent experience and Post-Graduation in Business management would be an added value. Experience leading the design and implementation of contact center applications, from concept to deployment, is highly desirable. Additional Information: An opportunity to work on with key G2000 clients Potential to with leaders in strategy, industry experts, enterprise function practitioners and, business intelligence professionals to shape and recommend innovative solutions that leverage emerging technologies. Ability to embed into everythingfrom how you service your clients to how you operate as a responsible professional. Personalized training modules to develop your to grow your skills, industry knowledge and capabilities Opportunity to thrive in a that is committed to accelerate equality for all. Engage in boundaryless collaboration across the entire organization. Qualification Educational Qualification :Post Graduation in Business Management

What You'll Do We are looking for experienced Machine Learning Engineers with a background in software development and a deep enthusiasm for solving complex problems. You will lead a dynamic team dedicated to designing and implementing a large language model framework to power diverse applications across Avalara. Your responsibilities will span the entire development lifecycle, including conceptualization, prototyping and delivery of the LLM platform features. You will have a blend of technical skills in the fields of AI & Machine Learning especially with LLMs and a deep-seated understanding of software development practices where you'll work with a team to ensure our systems are scalable, performant and accurate. You will be reporting to Senior Manager, AI/ML. What Your Responsibilities Will Be We are looking for engineers who can think quick and have a background in implementation. Your responsibilities will include: Build on top of the foundational framework for supporting Large Language Model Applications at Avalara Experience with LLMs - like GPT, Claude, LLama and other Bedrock models Leverage best practices in software development, including Continuous Integration/Continuous Deployment (CI/CD) along with appropriate functional and unit testing in place. Inspire creativity by researching and applying the latest technologies and methodologies in machine learning and software development. Write, review, and maintain high-quality code that meets industry standards. Lead code review sessions, ensuring good code quality and documentation. Mentor junior engineers, encouraging a culture of collaboration. Proficiency in developing and debugging software with a preference for Python, though familiarity with additional programming languages is valued and encouraged. What You'll Need to be Successful Bachelor's/Master's degree in computer science with 5+ years of industry experience in software development, along with experience building Machine Learning models and deploying them in production environments. Proficiency working in cloud computing environments (AWS, Azure, GCP), Machine Learning frameworks, and software development best practices. Work with technological innovations in AI & ML(esp. GenAI) Experience with design patterns and data structures. Good analytical, design and debugging skills. Technologies you will work with: Python, LLMs, MLFlow, Docker, Kubernetes, Terraform, AWS, GitLab, Postgres, Prometheus, Grafana

What you will do In this vital role We are looking for a creative and technically skilled Senior Software Engineer/AI Engineer Search to help design and build cutting-edge AI-powered search solutions for the pharmaceutical industry. In this role, you'll develop intelligent systems that surface the most relevant insights from clinical trials, scientific literature, regulatory documents, and internal knowledge assets. Your work will empower researchers, clinicians, and decision-makers with faster, smarter access to the right information. . Design and implement search algorithms using NLP, machine learning, semantic understanding, and deep learning models Build and fine-tune models for information retrieval, query expansion, document ranking, summarization, and Q&A systems Support integration of LLMs (e.g., GPT, BERT, Bio BERT) for semantic and generative search Train and evaluate custom models for biomedical named entity recognition, relevance ranking, and similarity search. Build and deploy vector-based search systems using embeddings and vector databases Work closely with platform engineers to integrate AI models into scalable cloud-based infrastructures (AWS, Azure, GCP) Package and deploy search services using containerization (Docker, Kubernetes) and modern MLOps pipelines. Preprocess and structure unstructured content such as clinical trial reports, research articles, and regulatory documents Apply knowledge graphs, taxonomies, and ontologies (e.g., MeSH, UMLS, SNOMED) to enhance search results Build and deploy recommendation systems models, utilize AIML infrastructure, and contribute to model optimization and data processing Experience in Generative AI on Search Engines Experience in integrating Generative AI capabilities and Vision Models to enrich content quality and user engagement Experience Generative AI tasks such as content summarization. deduping and metadata quality. Researching and developing advanced AI algorithms, including Vision Models for visual content analysis. Implementing KPI measurement frameworks to evaluate the quality and performance of delivered models, including those utilizing Generative AI. Developing and maintaining Deep Learning models for data quality checks, visual similarity scoring, and content tagging. Continually researching current and emerging technologies and proposing changes where needed. Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements. Basic Qualifications: Degree in computer science & engineering preferred with 6-8 years of software development experience 2-4 years of experience building AI/ML models, ideally in search, NLP, or biomedical domains. Proficiency in Python and frameworks such as PyTorch, TensorFlow, Hugging Face Transformers Experience with search technologies like Elasticsearch, OpenSearch, or vector search tools Solid understanding of NLP techniques: embeddings, transformers, entity recognition, text classification Hands-on experience with various AI models, GCP Search Engines, GCP Cloud services Proficient in programming language AI/ML, Python, Java Crawlers, Java Script, SQL/NoSQL, Databricks/RDS, Data engineering, S3 Buckets, dynamo DB Strong problem solving, analytical skills; Ability to learn quickly; Excellent communication and interpersonal skills Preferred Qualifications: Experience in AI/ML, Java, Python Experienced with Fast Pythons API, GraphQL Experience with design patterns, data structures, data modelling, data algorithms Experienced with AWS /Azure Platform, building and deploying the code Experience in Postgres SQL /Mongo DB SQL database, vector database for large language models, Databricks or RDS, S3 Buckets Knowledge of LLMs, generative AI, and their use in enterprise search Experience in Google cloud Search and Google cloud Storage Experience with popular large language models Experience with LangChain or LlamaIndex framework for language models Experience with prompt engineering, model fine tuning Knowledge of NLP techniques for text analysis and sentiment analysis Experience in Agile software development methodologies Experience in End-to-End testing as part of Test-Driven Development Good to Have Skills Willingness to work on Full stack Applications Exposure to MLOps tools like MLflow, Airflow, or SageMaker Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills. Ability to work effectively with global, remote teams. High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Strong presentation and public speaking skills.

Notice Period : Immediate - 15 Days About the Role : We are seeking a highly skilled Senior Data Scientist to join our team and contribute to cutting-edge projects. As a key member of our data science team, you will leverage your expertise in machine learning, natural language processing, and data engineering to develop innovative solutions that drive business value. Responsibilities : - Machine Learning Model Development : Design, develop, and deploy advanced machine learning models, focusing on natural language processing tasks such as text classification, sentiment analysis, and language generation. - Data Engineering : Extract, transform, and load (ETL) data from various sources, ensuring data quality and consistency. - NLP Techniques : Apply state-of-the-art NLP techniques, including language models and text processing, to solve complex problems. - Python and ML Frameworks : Utilize Python programming language and popular ML frameworks like PyTorch or TensorFlow to build efficient and scalable models. - Cloud and Containerization : Leverage cloud platforms (GCP, AWS) and containerization technologies (Docker) for efficient deployment and management of ML models. - Database Management : Work with relational databases (Postgres, MySQL) to store, manage, and query large datasets. - Knowledge Graphs and ML Publications : Contribute to the development of knowledge graphs and stay updated with the latest advancements in the field through research and publications. Qualifications : Experience : 4-7 years of hands-on experience in data science, with a strong focus on machine learning and natural language processing. Technical Skills : - Proficiency in Python programming language. - Deep understanding of machine learning algorithms and techniques. - Expertise in NLP, including language models and text processing. - Familiarity with ML frameworks like PyTorch or TensorFlow. - Experience with cloud platforms (GCP, AWS) and containerization (Docker). - Knowledge of relational databases (Postgres, MySQL). Soft Skills : - Strong problem-solving and analytical skills. - Excellent communication and collaboration abilities. - Ability to work independently and as part of a team.

Tezo is a new generation Digital & AI solutions provider, with a history of creating remarkable outcomes for our customers. We bring exceptional experiences using cutting-edge analytics, data proficiency, technology, and digital excellence. Tezo is seeking passionate AI Engineers who are excited about harnessing the power of Generative AI to transform our company and provide cutting-edge solutions for our clients. Join us in revolutionizing enterprises by building intelligent, generative solutions that leverage AI/ML. If you've ever dreamed of contributing to impactful projects on a large scale, this is the opportunity for you! In this role, you will be an integral part of the Machine Learning Platforms/Data Science team, focusing on developing, testing, and deploying generative AI models. What Makes Our AI/ML Practice Unique: Purpose-driven: We actively respond to our customers' evolving needs with innovative solutions. Collaborative: We foster a positive and engaging work environment where collective ideas thrive. Accountable: We take ownership of our performance, both individually and as a team. Service Excellence: We maximize our potential through continuous learning and improvement. Trusted: We empower individuals to make informed decisions and take calculated risks. Job Summary: We are looking for a dedicated Lead Data Scientist with a strong background in Generative AI to join our team. You will support product, leadership, and client teams by providing insights derived from advanced data analysis and generative modeling. In this role, you will collaborate closely with the development team, architects, and product owners to build efficient generative models and manage their lifecycle using the appropriate technology stack. Core Requirements: At least 6 years of experience working with geographically distributed teams 2+ years of experience working in a client-facing role on AI/ML . Demonstrable experience in leading a substantive area of work, or line management of a team. Proven experience in building production grade Retrieval-Augmented Generation (RAG) solutions with hands on experience with advanced RAG techniques for retrieval, re-ranking etc. Build GenAI applications using LangChain, LlamaIndex and familiarity with Vector Stores and Large Language Models. Experience in fine-tuning Large Language Models (LLMs) for business use cases will be preferred. Minimum of 4 years of experience in developing end-to-end classical machine learning and NLP projects. Demonstrated experience in deploying ML solutions in production using cloud services like Azure,AWS. Business Understanding, Stakeholder management and Team leading skills. Strong practical expertise in Python and SQL needed for data science projects. Join us at Tezo to be part of a dynamic team committed to driving innovation through Generative AI solutions!

Mandatory Skills : Python, Machine Learning Models, Flask, Data Visualization Tools. Good to have : Gen AI, NLP, Cloud (AWS) etc Notice Period : Immediate - 30 days Relevant Experience : 5+ Years in Machine Learning Responsibilities : - Design, develop, and deploy machine learning models and algorithms. - Perform data analysis to extract insights and identify patterns. - Develop and implement feature engineering processes to enhance model performance. - Collaborate with data scientists and cross-functional teams to understand business requirements and translate them into technical solutions. - Build and maintain scalable data pipelines and infrastructure. - Develop and deploy machine learning applications using Flask, FastAPI, or Django. - Conduct experiments, model tuning, and evaluate model performance using appropriate metrics. Must-Have Skills : - Python and its libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). - Experience with web frameworks such as Flask, FastAPI, or Django. - Strong understanding of machine learning algorithms and techniques. - Experience with data visualization tools (e.g., Matplotlib, Seaborn). - Strong problem-solving skills and ability to work independently as well as in a team. - Excellent communication skills to effectively convey technical concepts to non-technical stakeholders. Good-to-Have Skills : - Experience with cloud platforms, particularly AWS. - Knowledge of MLOps practices and tools. - Experience with Natural Language Processing (NLP) techniques. - Exposure to Generative AI (GenAI) technologies.

Architect scalable, high-performance Python applications and solutions. Ensure adherence to design principles, patterns, and coding standards in Python development.Proficiency in Python libraries (NumPy, Pandas, scikit-learn, TensorFlow, PyTorch).

Experience: 7-12years Location and Work Mode: Pune Job Description: About this Role We are seeking a highly skilled and motivated Data Scientist to join our team. This role is ideal for individuals who are passionate about leveraging data to drive innovation and create intelligent, scalable solutions. The successful candidate will work across a variety of data science domains, including diagnostic, predictive, and prescriptive analytics, and will contribute to the development of autonomous cognitive systems. This is an exciting opportunity to be part of a forward-thinking team that values continuous learning and collaboration. Who are you A data enthusiast with a strong foundation in machine learning, deep learning, and statistical modelling. A collaborative problem-solver who thrives in cross-functional teams and is comfortable engaging with stakeholders. A continuous learner with a passion for exploring new tools, technologies, and methodologies. An effective communicator who can translate complex data insights into actionable business strategies. A self-starter with a proactive mindset and the ability to work independently in a dynamic environment. What you will do Manage and process large-scale data on both on-premise and cloud platforms (preferably AWS). Design and implement diagnostic models using decision theory and causal inference techniques (e.g., DAG, ADMG, Deterministic SME). Build and productise diagnostic systems for scalable reuse across the organisation. Develop robust predictive and prescriptive analytics models using AI techniques such as ML, DL, NLP, ES, and RL. Create intelligent systems that determine the Next Best Action based on prescriptive analytics. Drive the development of autonomous cognitive systems that proactively recommend actions with minimal human intervention. Apply advanced deep learning techniques including CNNs, RNNs, and MLPs to solve complex business problems. Utilise machine learning and deep learning libraries such as TensorFlow, PyTorch, Scikit-learn, NumPy, Pandas, Statsmodels, Theano, and XGBoost. Collaborate with stakeholders to understand business needs and deliver data-driven solutions. Present insights and findings using visualisation tools like Tableau and Power BI. What skills you need Proficiency in programming languages: Python, R, SQL Experience with frameworks: TensorFlow, Keras, Scikit-learn Strong understanding of statistical modelling: regression, classification, clustering, time series Hands-on experience with cloud platforms: AWS (preferred), Azure Familiarity with big data technologies and environments Excellent communication and stakeholder management skills Strong analytical and problem-solving abilities At least one certification in AWS is preferred What skills you will learn Advanced applications of causal inference and decision theory in real-world scenarios Building and deploying scalable AI systems in cloud environments Designing autonomous systems that integrate feedback loops for continuous learning Enhancing stakeholder engagement through data storytelling and visualisation Exposure to cutting-edge tools and frameworks in the AI and ML ecosystem

Job Summary: We are seeking a highly skilled Functional AI Engineer to join our team and lead the development of custom knowledge-based AI models and large language model (LLM) implementations. The ideal candidate will have a strong background in artificial intelligence, machine learning, and natural language processing, with a focus on building innovative AI solutions that leverage knowledge-based systems and generative AI use cases. Key Responsibilities: - Design, develop, and implement knowledge-based AI models and LLMs to solve complex business problems. - Collaborate with cross-functional teams to identify opportunities for AI-driven solutions and develop custom use cases. - Conduct research and stay updated on the latest advancements in AI, machine learning, and NLP technologies. - Optimize and fine-tune AI models for performance, accuracy, and scalability. - Develop and maintain documentation for AI models, algorithms, and processes. - Ensure the ethical and responsible use of AI technologies in all implementations. - Provide technical guidance and mentorship to junior AI engineers and data scientists. - Work closely with stakeholders to understand business requirements and translate them into technical specifications. - Evaluate and integrate third-party AI tools and platforms as needed. - Monitor and analyze the performance of AI models, making necessary adjustments to improve outcomes. Qualifications: - Bachelor's or masters degree in computer science, Artificial Intelligence, Machine Learning, or a related field. - Proven experience in developing and implementing knowledge-based AI models and LLMs. - Strong programming skills in Python, TensorFlow, PyTorch, or similar AI frameworks. - Experience with natural language processing (NLP) and understanding of language models. - Familiarity with data management, data mining, and data visualization techniques. - Excellent problem-solving skills and ability to work independently and collaboratively. - Strong communication skills to effectively convey complex technical concepts to non-technical stakeholders. - Experience in the paints industry or similar sectors is a plus. Interested candidates can send their resume dhanashree.chitre@weareams.com

Notice Period : Immediate - 15 Days About the Role : We are seeking a highly skilled Senior Data Scientist to join our team and contribute to cutting-edge projects. As a key member of our data science team, you will leverage your expertise in machine learning, natural language processing, and data engineering to develop innovative solutions that drive business value. Responsibilities : - Machine Learning Model Development : Design, develop, and deploy advanced machine learning models, focusing on natural language processing tasks such as text classification, sentiment analysis, and language generation. - Data Engineering : Extract, transform, and load (ETL) data from various sources, ensuring data quality and consistency. - NLP Techniques : Apply state-of-the-art NLP techniques, including language models and text processing, to solve complex problems. - Python and ML Frameworks : Utilize Python programming language and popular ML frameworks like PyTorch or TensorFlow to build efficient and scalable models. - Cloud and Containerization : Leverage cloud platforms (GCP, AWS) and containerization technologies (Docker) for efficient deployment and management of ML models. - Database Management : Work with relational databases (Postgres, MySQL) to store, manage, and query large datasets. - Knowledge Graphs and ML Publications : Contribute to the development of knowledge graphs and stay updated with the latest advancements in the field through research and publications. Qualifications : Experience : 4-7 years of hands-on experience in data science, with a strong focus on machine learning and natural language processing. Technical Skills : - Proficiency in Python programming language. - Deep understanding of machine learning algorithms and techniques. - Expertise in NLP, including language models and text processing. - Familiarity with ML frameworks like PyTorch or TensorFlow. - Experience with cloud platforms (GCP, AWS) and containerization (Docker). - Knowledge of relational databases (Postgres, MySQL). Soft Skills : - Strong problem-solving and analytical skills. - Excellent communication and collaboration abilities. - Ability to work independently and as part of a team.

- Data Scientist -6+ years of experience in data science, with at least 2 years focused on LLMs or Generative AI. -Proven implementation experience in Data Science, Machine Learning, Deep Learning, and NLP for multiple domains. -Strong programming skills in Python, with experience in libraries such as Transformers (Hugging Face), PyTorch, or TensorFlow. -Hands-on experience with fine-tuning, prompt engineering, RAG (Retrieval-Augmented Generation), and LLM evaluation. -Familiarity with vector databases and embedding techniques. -Experience deploying models using APIs, Docker, and cloud platforms -Strong analytical, problem-solving, and communication skills. -Experience in ML Ops, Model deployment, Model lifecycle and management

AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Senior Data Scientist Marketing & Consumer Insights Location: Bangalore Reporting to: Senior Manager – Marketing & Consumer Insights COE 1. Purpose of the role We are looking for a highly motivated and strategic Senior Data Scientist to drive the global consumer sentiment analytics platform. This role will focus on building scalable, explainable, and accurate data science models using NLP and AI, enabling insights from social media, e-commerce platforms, and online review data across global markets. The candidate will own the end-to-end development cycle, from experimentation and model development to deployment and integration into Power BI dashboards. Mentoring junior data scientists, ensuring code quality, and exploring new AI techniques will also be part of the role. 2. Key tasks & accountabilities Own and manage data science workflows: data ingestion, cleaning, modeling, tuning, and interpretation. Apply and fine-tune NLP techniques for sentiment analysis, aspect extraction, multi-lingual translation and topic modeling. Ensure proper data modeling aligned with AB InBev’s data architecture; manage different data layers, handle data archiving, and continuously optimize the model as it matures. Integrate multiple datasets and data types (structured and unstructured) to improve model robustness and drive more insightful outputs. Oversee the deployment of models into production, ensuring integration with existing ABI systems and infrastructure. Ensure that the models are accurate, scalable and aligned with project objectives. Collaborate with functional and technical teams to translate business questions into modeling approaches. Participate actively during the dashboard visualization phase to ensure seamless user experience and usability; revisit model code to improve accuracy and simplify where possible. Work closely with visualization experts to ensure insights are consumable, intuitive, and decision-ready. Operate in a high-pressure, fast-paced environment across a global project with multiple stakeholders, diverse markets, and high-volume datasets. The ability to manage expectations, adapt to evolving requirements, and deliver results across geographies is critical. Drive experimentation and optimization cycles to improve model accuracy and business relevance. Partner with stakeholders across functions and geographies to ensure models address real-world needs. Maintain documentation and reproducibility standards across all modeling efforts. Mentor and support analysts and junior data scientists on best practices and solution design. 3. Qualifications, Experience, Skills Level of educational attainment required: Bachelor’s/Master’s degree in Data Science, Computer Science, Statistics, Engineering, or equivalent. Specialization or certifications in NLP, Deep Learning, or Applied AI preferred. Previous work experience required: 8+ years in data science with a focus on NLP and consumer analytics. Experience working with unstructured data, especially from social media, forums, or customer reviews. Prior exposure to end-to-end model deployment and integration with BI tools like Power BI. Experience in Agile teams, with familiarity in Azure DevOps or similar CI/CD environments. Proven ability to mentor and guide teams across multiple regions. IT Skills required: Python (essential), SQL, R, ML/DL frameworks (TensorFlow, Scikit-learn, SpaCy, HuggingFace) Experience with APIs (Twitter, Reddit, Facebook, YouTube, etc.) Familiarity with cloud environments (Azure preferred) Knowledge of Power BI integration and data pipelines Technical skills required: NLP, Sentiment Analysis, Topic Modeling, Text Classification Python, SQL, Machine Learning, Model Explainability API integration, Power BI readiness, data engineering fundamentals Text preprocessing, tokenization, and vectorization Sentiment analysis and topic modeling fundamentals Efficient coding practices and code optimization Working with multilingual corpora and translation APIs Knowledge of social listening tools (e.g., Brandwatch, Talkwalker) Advanced Data Visualization techniques Experience with multilingual data sets And above all of this, an undying love for beer! We dream big to create future with more cheers.

Key Responsibilities : We are seeking a highly skilled and motivated AI Engineer to join our team. In this role, you will leverage your expertise in AI technologies and the Microsoft ecosystem to design, build, and deploy intelligent agents and automation solutions that enhance business processes and deliver value to our clients. Candidates must have extensive experience in the Microsoft environment. You will collaborate with cross-functional teams to create innovative solutions using Microsoft tools and platforms. Responsibilities : Agent Development : - Design, implement, and optimize AI agents using Microsoft Azure Framework and related technologies. - Develop custom AI solutions leveraging Power Automate, Azure OpenAI, and other Microsoft tools. Solution Integration : - Deploy AI solutions within client environments, ensuring scalability and seamless integration with existing systems. - Work with stakeholders to identify automation opportunities and tailor solutions to business needs. AI Algorithm and Model Implementation : - Design and implement machine learning algorithms, focusing on natural language processing (NLP) and conversational AI. - Perform data preprocessing, feature engineering, and model training to create high-performing solutions. Collaboration and Support : - Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to deliver integrated solutions. - Provide technical guidance and support to ensure the successful adoption and use of AI-driven tools. Continuous Improvement : - Stay updated on advancements in AI, machine learning, and Microsofts AI technologies. - Contribute to knowledge sharing by conducting training sessions and documenting best practices. Preferred Skills : - Strong knowledge of Azure OpenAI, Azure AI Search Index and open source libraries such as LangChain and LlamaIndex. - Proficiency in Python and its AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). - Familiarity with building and managing cloud-based solutions, preferably on Microsoft Azure. - Understanding of conversational AI technologies and chatbot frameworks. - Experience with data analysis tools and techniques to uncover insights and optimize models. Requirements : - Bachelors or Masters degree in Computer Science, Data Science, or a related field. - Proven experience in developing and deploying AI/ML models in real-world applications. - Strong programming skills, especially in Python, and familiarity with version control systems like Git. - Extensive experience in the Microsoft environment and related technologies.

Face to Face interview in Pune . Please apply only if you are available for a Face to Face interview . Job highlights Required Qualifications . 0 -2 years of relevant industry experience or fresh graduates are welcome to apply. Basic experience or understanding in applying Data Science methodologies to extract, process, and transform data from multiple sources. Preferred Qualifications . Bachelors degree in Data Science , AI, Statistics ,Computer Science, Economics, or a directly related field. Essential Duties and Responsibilities Assist in developing, fine-tuning, and deploying machine learning models. Aid in consulting with key internal and external stakeholders to understand and frame model requirements and potential applications. Participate in the development of sound analytic plans based on available data sources, business partner needs, and required timelines. Work with software engineers in integrating trained models into end-user applications. Help manage deliverables across multiple projects in a deadline-driven environment. Present results, insights, and recommendations to both technical and non-technical stakeholders. Required Qualifications 0 -2 years of relevant industry experience or fresh graduates are welcome to apply. Good knowledge of Python and Linux, familiarity with ML frameworks, and a willingness to learn. Demonstrated problem-solving abilities and creative thinking. Basic experience or understanding in applying Data Science methodologies to extract, process, and transform data from multiple sources. Excellent communication and interpersonal skills. Must be comfortable working in a team-oriented environment. Preferred Qualifications Bachelor's degree in Statistics, Computer Science, Economics, or a directly related field. Masters degree or current enrollment in a Masters program in Statistics, Computer Science, Mathematics, Economics, or directly related fields is a plus. Demonstrated passion for continued learning and innovation. As a Data Science Assistant, we expect not just skills and qualifications, but also an enthusiasm for learning and growing within our team. We value those who are adaptable, innovative, and ready to take on challenges in a fast-paced work environment. Diversity, Inclusion & Equity At Rocket we are committed to an inclusive workplace environment, where every Rocketeer can thrive by bringing their full selves to work. Being a Rocketeer means you are part of our movement to continually drive inclusivity, diversity and equity in our workforce.

Role Responsibilities: Design and develop GenAI applications utilizing Python. Implement front-end solutions using Angular or React frameworks. Apply NLP techniques to enhance application functionalities. Optimize machine learning models for performance and scalability. Establish MLOps practices to streamline model deployment. Create and integrate APIs for seamless functionality between applications. Collaborate with cross-functional teams to define project requirements. Conduct code reviews to ensure adherence to best practices. Debug and troubleshoot applications to enhance user experience. Stay updated with industry trends and advancements in GenAI. Document project specifications and technological processes. Participate in regular team meetings to align on goals and challenges. Assist in training team members on GenAI technologies. Maintain version control for project codes and documentation. Provide technical support during product launches. Qualifications: Bachelor's or Master's degree in Computer Science or related field. Proven experience in GenAI development. Strong proficiency in Python programming language. Experience with front-end frameworks such as Angular and React. Hands-on expertise in Natural Language Processing (NLP). Familiarity with machine learning algorithms and models. Understanding of MLOps tools and practices. Experience in API development and integration. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Ability to work independently as well as in a team environment. Attention to detail with a focus on quality outcomes. Familiarity with database systems and management. Experience with version control systems like Git. Knowledge of agile methodologies is a plus.

Develop and enhance AI-driven chatbot solutions to automate customer interactions and optimize response accuracy. Design and implement NLP algorithms using frameworks like Rasa, Dialogflow, or IBM Watson. Ensure seamless chatbot integration with existing platforms and CRM systems. Work closely with data scientists to improve machine learning models. Must have strong proficiency in Python, deep learning techniques, and chatbot analytics.

Develop and enhance AI-driven chatbot solutions to automate customer interactions and optimize response accuracy. Design and implement NLP algorithms using frameworks like Rasa, Dialogflow, or IBM Watson. Ensure seamless chatbot integration with existing platforms and CRM systems. Work closely with data scientists to improve machine learning models. Must have strong proficiency in Python, deep learning techniques, and chatbot analytics.

Develop and enhance AI-driven chatbot solutions to automate customer interactions and optimize response accuracy. Design and implement NLP algorithms using frameworks like Rasa, Dialogflow, or IBM Watson. Ensure seamless chatbot integration with existing platforms and CRM systems. Work closely with data scientists to improve machine learning models. Must have strong proficiency in Python, deep learning techniques, and chatbot analytics.

Develop and enhance AI-driven chatbot solutions to automate customer interactions and optimize response accuracy. Design and implement NLP algorithms using frameworks like Rasa, Dialogflow, or IBM Watson. Ensure seamless chatbot integration with existing platforms and CRM systems. Work closely with data scientists to improve machine learning models. Must have strong proficiency in Python, deep learning techniques, and chatbot analytics.

The Opportunity: We are seeking a talented and experienced Senior AI Engineer to play a pivotal role in developing and enhancing our conversational AI capabilities across multiple modalities (text, voice/telephony) and building intelligent agents to drive workflow automation. You will work closely with our Director of AI Engineering, product managers, and other engineering teams to bring our AI vision to life, primarily focusing on fine-tuning off-the-shelf Large Language Models (LLMs) and developing agentic systems for end-users (members, CBO staff, healthcare providers). This is a unique opportunity to apply your AI expertise to solve meaningful problems in the social and healthcare space, directly impacting people's lives. What You'll Do: Conversational AI Development & Fine-Tuning (Text & Voice): Lead the fine-tuning, evaluation, and deployment of pre-trained LLMs (e.g., Gemini, GPT series, open-source models) to create natural, empathetic, and effective conversational experiences for various user interactions via text-based channels (chat, SMS) and voice-based telephonic systems (IVR chatbots). Develop and implement strategies for data collection, preparation, and augmentation to support model fine-tuning and continuous improvement for both text and voice modalities. Design and implement robust evaluation frameworks to measure conversational AI performance, including metrics for accuracy, fluency, empathy, task completion, and call handling efficiency for telephonic agents. Work on prompt engineering, context management, and dialogue flow design to optimize conversational AI interactions across channels. Integrate and manage speech-to-text (STT) and text-to-speech (TTS) services for telephonic AI solutions. Agentic System Development: Design, build, and deploy AI agents that can reason, make decisions, and take actions to automate and optimize key workflows within the platform (e.g., intelligent referral initiation, proactive follow-ups, task management assistance). Develop agents capable of interacting with internal platform APIs, external data sources, and potentially third-party tools to achieve their goals. Explore and implement techniques for agent planning, tool usage, and multi-step reasoning. Collaboration & Technical Leadership: Collaborate closely with the Director of AI Engineering to define AI strategy, architecture, and technical roadmap for conversational AI and agentic systems. Partner with Product Managers to understand user needs and translate them into technical requirements for AI features. Work with platform and application engineers to integrate AI models and agents into the broader ecosystem. Mentor junior engineers and contribute to building a strong AI engineering culture. Stay up-to-date with the latest advancements in LLMs, conversational AI (text and voice), agent-based systems, and MLOps. MLOps & Productionization: Contribute to the development and maintenance of our MLOps infrastructure for training, deploying, monitoring, and iterating on AI models and agents in production. Ensure AI systems are scalable, reliable, and maintainable. Back-end Development: Solid understanding of back-end development principles and experience building or integrating with APIs (e.g., RESTful services) to connect AI models and agents with broader application systems. Familiarity with database technologies (SQL and/or NoSQL) and practical experience in how AI systems interact with data storage and retrieval for training, inference, and logging. What You'll Bring: Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience: 5+ years of hands-on experience in AI/ML engineering, with a significant focus on Natural Language Processing (NLP) and conversational AI. Demonstrable experience developing and deploying AI-powered telephonic chatbots or Interactive Voice Response (IVR) systems, including integration with STT/TTS technologies. Proven experience fine-tuning and deploying Large Language Models (LLMs) for specific tasks and domains. Strong understanding of model architectures, training techniques, and evaluation metrics. Demonstrable experience designing and building AI agents or systems that exhibit autonomous behavior, decision-making, and/or tool usage. Proficiency in Python and common AI/ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers, LangChain, LlamaIndex). Experience with cloud platforms (GCP preferred, AWS/Azure acceptable) and their AI/ML services (e.g., Vertex AI, SageMaker, cloud telephony APIs). Solid understanding of MLOps principles and experience with tools for model deployment, monitoring, and CI/CD for ML. Skills: Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Ability to translate complex technical concepts to non-technical stakeholders. Proactive, self-starter with a passion for building impactful AI solutions. Nice to Haves: Experience working in the healthcare or social care domain. Familiarity with data privacy and security considerations in regulated environments (e.g., HIPAA). Experience with specific telephony platforms or APIs (e.g., Twilio, Vonage, Google Dialogflow CX). Contributions to open-source AI/ML projects.

Solutions Architect / Technical Lead - AI & Automation1 Key Responsibilities Solution Architecture & Development: Design end-to-end solutions using Node.JS (backend) and Vue.JS (frontend) for custom portals and administration interfaces. Integrate Azure AI services , Google OCR , and Azure OCR into client workflows. AI/ML Engineering: Develop and optimize vision-based AI models ( Layout Parsing/LP, Layout Inference/LI, Layout Transformation/LT ) using Python . Implement NLP pipelines for document extraction, classification, and data enrichment. Cloud & Database Management: Architect and optimize MongoDB databases hosted on Azure for scalability, security, and performance. Manage cloud infrastructure (Azure) for AI workloads, including containerization and serverless deployments. Technical Leadership: Lead cross-functional teams (AI engineers, DevOps, BAs) in solution delivery. Troubleshoot complex technical issues in OCR accuracy, AI model drift, or system integration. Client Enablement: Advise clients on technical best practices for scaling AI solutions. Document architectures, conduct knowledge transfers, and mentor junior engineers. Required Technical Expertise Frontend/Portal: Vue.JS (advanced components, state management), Node.JS (Express, REST/GraphQL APIs). AI/ML Stack: Python (PyTorch/TensorFlow), Azure AI (Cognitive Services, Computer Vision), NLP techniques (NER, summarization). Layout Engineering : LP/LI/LT for complex documents (invoices, contracts). OCR Technologies: Production experience with Google Vision OCR and Azure Form Recognizer . Database & Cloud: MongoDB (sharding, aggregation, indexing) hosted on Azure (Cosmos DB, Blob Storage, AKS). Infrastructure-as-Code (Terraform/Bicep), CI/CD pipelines (Azure DevOps). Experience: 10+ years in software development, including 5+ years specializing in AI/ML, OCR, or document automation . Proven track record deploying enterprise-scale solutions in cloud environments (Azure preferred). Preferred Qualifications Certifications: Azure Solutions Architect Expert , MongoDB Certified Developer , or Google Cloud AI/ML. Experience with alternative OCR tools (ABBYY, Tesseract) or AI platforms (GCP Vertex AI, AWS SageMaker). Knowledge of DocuSign CLM , Coupa , or SAP Ariba integrations. Familiarity with Kubernetes , Docker , and MLOps practices.

Company: Compunnel INC Job Location: Noida/Chandigarh Experience Required: 4+ years Mode of Work: 5 days work from the office Job Title: AI /ML Engineer We are seeking a talented and innovative Generative AI Engineer to join our team. The ideal candidate will have expertise in training and testing large language models (LLMs) for applications like speech-to-text and text-to-speech, with a focus on the Hindi language. This role requires proficiency in cutting-edge AI technologies, including transformers, GPU acceleration, and CUDA, along with strong Python programming skills. Key Responsibilities: Design, train, and fine-tune LLMs for speech-to-text and text-to-speech applications in Hindi. Develop and optimize transformer-based architectures for natural language processing (NLP) tasks. Leverage GPU acceleration and CUDA for efficient model training and deployment. Pre process and manage large datasets to ensure high-quality data for model training. Collaborate with cross-functional teams to integrate AI models into production systems. Conduct rigorous testing and evaluation of models to ensure accuracy, efficiency, and scalability. Stay updated with the latest advancements in generative AI and NLP technologies. Required Skills and Qualifications: Proficiency in Python and experience with deep learning frameworks like TensorFlow or PyTorch. Strong understanding of transformer architectures (e.g., BERT, GPT, T5). Hands-on experience with GPU acceleration and CUDA programming. Familiarity with Hindi language processing, including phonetics, grammar, and linguistic nuances. Experience in developing and deploying speech-to-text and text-to-speech systems. Knowledge of data preprocessing techniques for audio and text datasets. Strong problem-solving skills and ability to work in a collaborative environment. Preferred Qualifications: Experience with tools like Hugging Face Transformers, Kaldi, or Mozilla Deep Speech. Familiarity with cloud platforms (e.g., AWS, Azure, or Google Cloud) for AI model deployment. Understanding of end-to-end speech recognition and synthesis pipelines. A background in linguistics or computational linguistics is a plus. Please fill in all the essential details which are given below & attach your updated resume, and send it to ralish.sharma@compunnel.com 1. Total Experience: 2. Relevant Experience in Python : 3. Experience in Pytorch : 4. Experience in Tensorflow: 5. Experience in LLM : 6. Experience in RAG : 7. Experience in NLP : 8. Experience in GPT : 9. Experience in Bert: 10 . Experience in CUDA : 11. Current company : 12. Current Designation : 13. Highest Education : 14. Notice Period: 15. Current CTC: 16. Expected CTC: 17. Current Location: 18. Preferred Location: 19. Hometown: 20. Contact No: 21. If you have any offer from some other company, please mention the Offer amount and Offer Location: 22. Reason for looking for change: If the job description is suitable for you, please get in touch with me at the number below: 9910044363 .

Job Summary: We are seeking a passionate and skilled AI Engineer to design, develop, and deploy cutting-edge AI solutions across domains such as large language models (LLMs), computer vision, and autonomous agent workflows. You will collaborate with data scientists, researchers, and engineering teams to build intelligent systems that solve real-world problems using deep learning, transformer-based architectures, and multi-modal AI models. Key Responsibilities: Design and implement AI/ML models, especially transformer-based LLMs (e.g., BERT, GPT, LLaMA) and vision models (e.g., ViT, YOLO, Detectron2). Develop and deploy computer vision pipelines for object detection, segmentation, OCR, and image classification tasks. Build and orchestrate intelligent agent workflows using prompt engineering, memory systems, retrieval-augmented generation (RAG), and multi-agent coordination. Fine-tune and optimize pre-trained models on domain-specific datasets using frameworks like PyTorch or TensorFlow. Collaborate with cross-functional teams to understand problem requirements and translate them into scalable AI solutions. Implement inference pipelines and APIs to serve AI models efficiently using tools such as FastAPI, ONNX, or Triton Inference Server. Conduct model evaluation, benchmarking, A/B testing, and performance tuning. Stay updated with state-of-the-art research in deep learning, generative AI, and multi-modal learning. Ensure reproducibility, versioning, and documentation of all experiments and production models. Qualifications: Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 35 years of hands-on experience in designing and deploying deep learning models. Strong knowledge of LLMs (e.g., GPT, BERT, T5), Vision Models (e.g., CNNs, Vision Transformers), and Computer Vision techniques. Experience building intelligent agents or using frameworks like LangChain, Haystack, AutoGPT, or similar. Proficiency in Python, with expertise in libraries such as PyTorch, TensorFlow, Hugging Face Transformers, OpenCV, and Scikit-learn. Familiarity with MLOps concepts and deployment tools (Docker, Kubernetes, MLflow). Strong understanding of NLP, image processing, model fine-tuning, and optimization. Experience with cloud platforms (AWS, GCP, Azure) and GPU environments. Excellent problem-solving, communication, and teamwork skills. Preferred Qualifications: Experience in building multi-modal AI systems (e.g., combining vision + language models). Exposure to real-time inference systems and low-latency model deployment. Contributions to open-source AI projects or research publications. Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and RAG pipelines. Locations : Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, India

Job Summary: We are seeking a highly skilled and hands-on AI Engineer with 3+ years of proven experience in building and deploying solutions using Generative AI and Large Language Models (LLMs). You will work on cutting-edge applications leveraging transformer-based architectures, fine-tuning, prompt engineering, and scalable AI deployments. This role is ideal for engineers passionate about AI research and real-world productization of generative AI technologies. Key Responsibilities: Design, develop, and deploy solutions using LLMs (e.g., GPT, LLaMA, Mistral, Claude, PaLM, etc.) for various NLP and content generation tasks. Work on fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) pipelines. Integrate LLMs into enterprise applications with APIs and orchestrate workflows using Python, LangChain, or similar frameworks. Optimize model performance, latency, and cost for production use. Collaborate with data scientists, MLOps engineers, and product managers to deliver scalable AI features. Conduct experiments, analyze results, and publish internal findings or contribute to whitepapers. Ensure ethical, secure, and responsible use of AI technologies in all implementations. Required Skills & Experience: 3+ years of hands-on experience working with Generative AI, LLMs, and NLP technologies. Strong programming skills in Python and experience with libraries like Transformers (Hugging Face), LangChain, PyTorch, TensorFlow, etc. Proven track record of fine-tuning LLMs, developing embeddings, and working with vector databases (e.g., FAISS, Pinecone, Weaviate). Experience deploying models on cloud platforms (AWS, Azure, GCP) and using ML pipelines or MLOps tools. Solid understanding of deep learning, NLP architectures, tokenization, and evaluation metrics for generative models. Experience in API development and integration of LLMs into user-facing applications. Preferred Qualifications: Masters or PhD in Computer Science, AI/ML, Data Science, or related field. Experience with OpenAI APIs, Anthropic, Cohere, or open-source LLMs (e.g., Mistral, Falcon, LLaMA 3). Understanding of RLHF (Reinforcement Learning from Human Feedback) and model alignment techniques. Contributions to open-source AI projects or publications in GenAI/LLM.

Job Description Develop fit for purpose AIML models/algorithms/processes to address pharma/healthcare applications and innovative products upon completion of prototypes followed by the building of production grade algorithms/automation engines for client deliverables. Test for viability in order to deliver final products to clients. Able to bring newly researched ideas to reality quickly and on a large scale. Design, build, test, and deliver products from post-prototype to client delivery. Essential Functions Assists with the ongoing development and implementation of an enterprise architecture. May devise and present business cases and program release plans to senior management with priority recommendations to maintain and evolve this architecture. Builds effective business relationships with business line managers and provides technical and system expertise as input to product concepts. May assist product development management to define IT strategic direction and assists in the mapping of projects to that strategic direction whilst ensuring product capabilities and process improvements are delivered over time within the framework of the IQVIA enterprise architecture. Participates in cross-functional product development teams, may also act as a consultant to provide system and technical advice. Keeps up to date with technology changes and identifies opportunities for implementation in future systems. Participates in R&D projects and may run those projects in compliance with standard project management practices. May mentor and assist lower level architects and business analysts Qualifications 10+ years of experience in engineering roles with team management experience 5-7 relevant years experience on NLP, Machine Learning and Deep learning 5-7 relevant years of experience on Python Extensively work on NLP applications, ability to work on Machine learning model, Deep learning development Knowledge of LLMs, fine tuning and deployment Experience annotated datasets for Supervised Learning methods and correction Experience on text to transform natural language into useful features Find and implement the right algorithms and tools for NLP tasks Perform statistical analysis of results and refine models Extend ML libraries and frameworks to apply in NLP tasks Experience on ORM, SQL Alchemy, Alembic is a must Experience on Writing on effective and scalable code Experience on Unit Testing using Pytest or equivalent framework A deep understanding and multi-process architecture and the threading limitations of Python. Familiarity with server-side templating languages including Jinja 2 and Mako is good to have Experience on REST API, Flask API, Fast API is must, Django or Pyramid framework is good to have Knowledge of NER, Knowledge graphs is good to have Education Qualification Master's Degree Masters Degree in Machine Learning, Statistics, Computer Science, Physics, Math, or related field