282 Spacy Jobs - Page 11

Job Title: AI/ML and Chatbot Lead Experience Level: 10+ Years (Lead/Architect level) Location: Remote Employment Type: Full-time No. of Positions: 1 Job Overview: We are seeking a visionary and hands-on AI/ML and Chatbot Lead to spearhead the design, development, and deployment of enterprise-wide Conversational and Generative AI solutions. This role will establish and scale our AI Lab function, define chatbot and multimodal AI strategies, and deliver intelligent automation solutions that enhance user engagement and operational efficiency. Key Responsibilities Define and lead the enterprise-wide strategy for Conversational AI, Multimodal AI, and Large Language Models (LLMs). Build an AI/Chatbot Lab , creating a roadmap and driving innovations across in-app, generative, and conversational AI. Architect scalable AI/ML systems including presentation, orchestration, AI, and data layers. Collaborate with business stakeholders to assess needs, conduct ROI analyses, and deliver impactful AI use cases. Identify and implement agentic AI capabilities and SaaS optimization opportunities. Deliver POCs, pilots, and MVPs owning the design, development, and deployment lifecycle. Lead, mentor, and scale a high-performing team of AI/ML engineers and chatbot developers . Build multi-turn, memory-aware conversations using frameworks like LangChain or Semantic Kernel . Integrate bots with platforms like Salesforce, NetSuite, Slack , and custom applications via APIs/webhooks. Implement and monitor chatbot KPIs using tools like Kibana , Grafana , and custom dashboards. Champion ethical AI , governance, and data privacy/security best practices. Must-Have Skills 10+ years in AI/ML; demonstrable success in chatbot, conversational AI , and generative AI implementations. Experience building and operationalizing an AI/Chatbot architecture framework used enterprise-wide. Expertise in: Python , LangChain, ElasticSearch, NLP (spaCy, NLTK, Hugging Face) LLMs (e.g., GPT, BERT), RAG, prompt engineering Chatbot platforms (Azure OpenAI, MS Bot Framework), CLU, CQA AI solution deployment and monitoring at scale Familiarity with: Machine learning algorithms, deep learning, reinforcement learning NLP techniques for NLU/NLG Cloud platforms ( AWS, Azure, GCP ), Docker , Kubernetes Vector DBs (Pinecone, Weaviate, Qdrant) Semantic search, knowledge graphs, intelligent document processing Strong grasp of AI governance , documentation, and compliance standards Excellent team leadership, communication, and documentation skills Good-to-Have Skills Experience with Glean , Perplexity.ai , Rasa , XGBoost Familiarity with Salesforce , NetSuite , and business domains like Customer Success Knowledge of RPA tools like UiPath and its AI Center Role & responsibilities Interested candidate can call at 7087707007

We are looking for a passionate and skilled AI/ML Developer with 4 to 9 years of experience to join our team in Kolkata. The ideal candidate will have hands-on experience in building and deploying AI/ML models, with strong proficiency in Python, machine learning frameworks, and a solid understanding of modern development practices. Role & responsibilities Design, develop, and deploy machine learning and AI solutions for business needs. Work with Generative AI models, Whisper (Speech-to-Text/Text-to-Speech), and NLP-based chatbot solutions. Build and maintain scalable and reliable AI model pipelines. Collaborate with cross-functional teams using Agile methodologies. Perform data preprocessing, feature engineering, and model tuning. Deploy models to production environments and monitor performance. Integrate AI/ML solutions into web applications using technologies such as React.js, Oracle APEX, Oracle JET, and HTML5. Participate in system design and apply software engineering best practices including design patterns and testing. Preferred candidate profile AI/ML & Data: Machine Learning, Deep Learning Generative AI, Whisper (Speech-to-Text/Text-to-Speech) Chatbot Development, Natural Language Processing (NLP) AI Model Deployment (cloud/on-premise) Programming & Frameworks: Proficient in Python Experience with TensorFlow, PyTorch Frontend/Backend & Scripting: React.js, HTML5 Oracle APEX, Oracle JET Linux Shell Scripting Tools & DevOps: Docker, Git, Jira Methodologies: Agile Development System Design, Design Patterns Preferred Qualifications: Bachelors/Master’s degree in Computer Science, Engineering, or a related field. Strong analytical and problem-solving skills. Excellent communication and teamwork abilities. Experience working in a product or R&D environment is a plus.

We're looking for an experienced AI/ML Technical Lead to architect and drive the development of our intelligent conversation engine. Youll lead model selection, integration, training workflows (RAG/fine-tuning), and scalable deployment of natural language and voice AI components. This is a foundational hire for a technically ambitious platform. Role & responsibilities AI System Architecture: Design the architecture of the AI-powered agent including LLM-based conversation workflows, voice bots, and follow-up orchestration. Model Integration & Prompt Engineering: Leverage APIs from OpenAI, Anthropic, or deploy open models (e.g., LLaMA 3, Mistral). Implement effective prompt strategies and retrieval-augmented generation (RAG) pipelines for contextual responses. Data Pipelines & Knowledge Management: Build secure data pipelines to ingest, embed, and serve tenant-specific knowledge bases (FAQs, scripts, product docs) using vector databases (e.g., Pinecone, Weaviate). Voice & Text Interfaces: Implement and optimize multimodal agents (text + voice) using ASR (e.g., Whisper), TTS (e.g., Polly), and NLP for automated qualification and call handling. Conversational Flow Orchestration: Design dynamic, stateful conversations that can take actions (e.g., book meetings, update CRM records) using tools like LangChain, Temporal, or n8n. Platform Scalability: Ensure models and agent workflows scale across tenants with strong data isolation, caching, and secure API access. Lead a Cross-Functional Team: Collaborate with backend, frontend, and DevOps engineers to ship intelligent, production-ready features. Monitoring & Feedback Loops: Define and monitor conversation analytics (drop-offs, booking rates, escalation triggers), and create pipelines to improve AI quality continuously. Preferred candidate profile Qualifications Must-Haves: 5+ years of experience in ML/AI, with at least 2 years leading conversational AI or LLM projects. Strong background in NLP, dialog systems, or voice AI preferably with production experience. Experience with OpenAI, or open-source LLMs (e.g. LLaMA, Mistral, Falcon) and orchestration tools (LangChain, etc.). Proficiency with Python and ML frameworks (Hugging Face, PyTorch, TensorFlow). Experience deploying RAG pipelines, vector DBs (e.g. Pinecone, Weaviate), and managing LLM-agent logic. Familiarity with voice processing (ASR, TTS, IVR design). Solid understanding of API-based integration and microservices. Deep care for data privacy, multi-tenancy security, and ethical AI practices. Nice-to-Haves: Experience with CRM ecosystems (e.g. Salesforce, HubSpot) and how AI agents sync actions to CRMs. Knowledge of sales pipelines and marketing automation tools. Exposure to calendar integrations (Google Calendar API, Microsoft Graph). Knowledge of Twilio APIs (SMS, Voice, WhatsApp) and channel orchestration logic. Familiarity with Docker, Kubernetes, CI/CD, and scalable cloud infrastructure (AWS/GCP/Azure). What We Offer Founding team role with strong ownership and autonomy Opportunity to shape the future of AI-powered sales Flexible work environment Competitive salary Access to cutting-edge AI tools and training resources Post your resume and any relevant project links (GitHub, blog, portfolio) to career@sourcdeskglobal.com. Include a short note on your most interesting AI project or voicebot/conversational AI experience.

reliability Role Summary: The AI/ML Engineers will be responsible for developing, testing, and deploying machine learning models and AI algorithms that can be integrated into the product suite. The ideal candidate will have expertise in integrating large language models (LLMs) with external knowledge bases, fine-tuning model architectures for specific tasks, and optimizing retrieval strategies to improve the accuracy and relevance of generated content. Key Responsibilities: Implement and optimize AI/ML algorithms for product integration. Collaborate with data scientists to deploy models and integrate them with software products. Design scalable solutions for AI/ML applications. Develop automated pipelines for continuous model training and updates. Work with engineering teams to ensure smooth integration and operation of AI models in production. Monitor and troubleshoot AI/ML models to ensure reliability and performance. Required Experience: 4 - 6 years of hands-on experience in machine learning model development and deployment. Hands-on experience in developing and fine-tuning Generative AI models, specifically focusing on Retrieval-Augmented Generation (RAG) systems. Experience with frameworks such as Hugging Face, OpenAI, or other GenAI platforms, along with proficiency in data preprocessing and model evaluation, is required Proficiency in Python, TensorFlow, Keras, PyTorch, or other AI/ML frameworks. Experience with model deployment and monitoring in production environments. Strong problem-solving skills and experience with cloud computing platforms (AWS, GCP, Azure). Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).

Python Developer(Numpy, Scipy, Pandas, Dask, spaCy, NLTK, sci-kit-learn, and PyTorch) As part of the team, your primary role would be to get to the heart of customer issues, diagnose problem areas, design innovative solutions and facilitate deployment resulting in client delight. You will develop a proposal by owning parts of the proposal document and by giving inputs in solution design based on areas of expertise. You will plan the activities of configuration, configure the product as per the design, conduct conference room pilots and will assist in resolving any queries related to requirements and solution design You will conduct solution/product demonstrations, POC/Proof of Technology workshops and prepare effort estimates which suit the customer budgetary requirements and are in line with organizations financial guidelines Actively lead small projects and contribute to unit-level and organizational initiatives with an objective of providing high quality value adding solutions to customers.

We are seeking an experienced and innovative AI Specialist to join our dynamic team. The ideal candidate will possess deep expertise in artificial intelligence, machine learning, and neural networks, with a proven track record of designing, developing, and deploying AI solutions. The candidate should be adept at analyzing large datasets, developing optimized algorithms, and integrating AI models into production environments. This role offers the opportunity to contribute to cutting-edge AI applications that solve real-world problems and drive business value Key Responsibilities: AI System Design & Development: Design, develop, and implement AI systems and applications, including machine learning models, neural networks, and natural language processing (NLP) algorithms. Create and optimize AI algorithms for tasks such as image recognition, speech processing, and predictive analytics. Data Analysis & Feature Engineering: Analyze large datasets to identify trends, patterns, and actionable insights. Perform data preprocessing, data wrangling, and feature engineering to enhance model performance. Model Training & Optimization: Train and fine-tune machine learning models using labeled and unlabeled data to improve model accuracy and efficiency. Continuously monitor and optimize models for better performance. AI Model Integration: Deploy machine learning models into production environments, ensuring scalability and reliability. Integrate AI technologies with existing software and business processes using REST APIs. Utilize Docker and Kubernetes to containerize and manage AI models. Research & Innovation: Stay up to date with the latest advancements in AI and machine learning technologies. Explore and experiment with new AI applications, tools, and methodologies to enhance system capabilities. Collaboration & Agile Development: Work closely with cross-functional teams in an Agile environment to develop AI-driven solutions that meet business requirements. Communicate findings and results to stakeholders, ensuring AI solutions align with business goals. Primary Skills and Qualifications: AI and Machine Learning Expertise: Strong knowledge of supervised and unsupervised learning techniques, including classification, regression, clustering, and reinforcement learning. Hands-on experience developing and deploying machine learning models in production environments. Technical Proficiency: Programming Languages: Advanced proficiency in Python, with additional experience in R and SQL as a plus. ML Libraries/Frameworks: Expertise in TensorFlow, PyTorch, and scikit-learn. Cloud Platforms: Hands-on experience with AWS, Azure, or Google Cloud for model deployment and management. Model Deployment & Integration: Familiarity with REST APIs, Docker, and Kubernetes for seamless model integration. Secondary Skills and Preferred Qualifications: Natural Language Processing (NLP): Experience with NLP frameworks such as NLTK, spaCy, Hugging Face, and BERT. Agile Methodologies: Knowledge of Agile practices, with experience using tools like JIRA for project management. Mathematics and Statistics: Strong foundation in probability, statistics, and linear algebra to support model development and evaluation. Data Handling & Preprocessing: Proficiency in data cleaning, transformation, and feature engineering to prepare data for modeling.

We are looking for an experienced Python Developer who possessesadeep understanding of the Python programming language and its ecosystem. Theideal candidate will be responsible for designing, implementing, and maintaininghigh- performance, scalable applications while collaborating with cross-functional teamstodeliver exceptional software solutions. The role offers an exciting opportunity toworkondiverse projects and leverage emerging technologies to drive innovation. Qualifications: 1. Bachelor's degree in Computer Science, Engineering, or related field; Master'sdegree preferred. 2. Proven experience (5 to 8 years) as a Python Developer or similar role, withastrongportfolio of Python-based projects and applications. 3. Proficiency in Python programming language and its standard libraries, frameworks, and tools such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, sci-kit-learn, andPyTorch 4. Experience REST API libraries and frameworks such as Django, Flask, andSQLAlchemy. 5. Solid understanding of object-oriented programming (OOP) principles, datastructures, and algorithms. 6. Experience with database design, SQL, and ORM frameworks (e.g., SQL Alchemy, Django ORM). 7. Familiarity with front-end technologies such as HTML, CSS, JavaScript, and client-sideframeworks (e.g., React, Angular, Vue.js). 8. Knowledge of version control systems (e.g., Git) and collaborative developmentworkflows (e.g., GitHub, GitLab). 9. Strong analytical and problem-solving skills, with a keen attention to detail andapassion for continuous improvement. 10. Excellent communication and interpersonal skills, with the ability to collaborateeffectively in a team environment and communicate technical concepts tonon- technical stakeholders. Preferred Qualifications: 1. Experience with cloud platforms and services (e.g., AWS, Azure, GoogleCloudPlatform). 2. Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes). 3. Understanding of software testing principles and practices, including unit testing, integration testing, and test automation frameworks (e.g., pytest). 4. Familiarity with DevOps practices and CI/CD pipelines for automated softwaredeployment and delivery.

We are looking for a highly skilled and experienced AI Engineer with 2 to 7 years of experience to join our team in Bengaluru. The ideal candidate will have a strong background in artificial intelligence, machine learning, and software engineering. ### Roles and Responsibility Design, develop, and deploy AI models and systems that align with business objectives. Conduct data analysis, pre-processing, and feature engineering to ensure high-quality input for AI algorithms. Train, evaluate, and optimize AI models using various machine learning algorithms and techniques. Implement scalable and efficient AI solutions in production environments, considering performance, latency, and reliability. Collaborate with AI and software engineers to integrate AI models into production systems and monitor their performance. Analyze and interpret AI model outputs, providing insights and recommendations to stakeholders. ### Job Requirements Deep understanding of AI and machine learning algorithms, including regression, classification, clustering, and deep learning. Proficiency in Python for AI model development, along with experience in deep learning frameworks such as TensorFlow, PyTorch, or Keras. Familiarity with cloud platforms, preferably Azure, to deploy scalable AI solutions, and knowledge of distributed computing frameworks like Spark. Strong foundation in software engineering practices, including version control with Git, testing, documentation, and code review. Understanding of NLP techniques and frameworks such as Hugging Face's Transformers, BERT, GPT, or Transformer models, TensorFlow's NLP library, or spaCy for language-related AI applications. Experience with natural language processing (NLP) techniques and frameworks, and generative AI techniques, including prompt engineering and fine-tuning LLMs. Proficiency in data pre-processing, visualization, SQL, and big data technologies, along with strong skills in Python for AI model development and implementation. Knowledge of containerization tools like Docker and an understanding of responsible AI practices and data privacy. Generative AI Techniques: Knowledge and experience in Generative AI techniques, prompt engineering, vector database, LLMs such as OpenAI, Azure OpenAI, Open-source LLMs. Fine-tuning: Collaborate with the research and development teams to fine-tune large language models using prompts, ensuring the models produce accurate, contextually relevant, and safe responses. Model Evaluation and Optimization: Experience with model evaluation, hyperparameter tuning, and optimization techniques. Data Pre-processing and Visualization: Solid understanding of techniques for data pre-processing, feature engineering, and data visualization. Cloud Platforms: Familiarity with cloud platforms like AWS, Azure, or GCP for scalable AI solutions. (Azure preferred) Distributed Computing: Knowledge of distributed computing frameworks, particularly Spark, for large-scale data processing. Version Control Systems: Proficient in using version control systems like Git for collaborative AI development. Troubleshooting and Debugging: Ability to troubleshoot and debug complex AI systems and models. Containerization: Knowledge of containerization tools like Docker for efficient deployment of AI solutions. Software Engineering Practices: Familiarity with software engineering practices, including testing, documentation, and code review.

The Team: As a Senior Lead Machine Learning Engineer of the Document Platforms and AI Team, you will play a critical role in building the next generation of data extraction tools, working on cutting-edge ML-powered products and capabilities that power natural language understanding, information retrieval, and data sourcing solutions for the Enterprise Data Organization and our clients. This is an exciting opportunity to shape the future of data transformation and see your work make a real difference, all while having fun in a collaborative and engaging environment. You'll spearhead the development and deployment of production-ready AI products and pipelines, leading by example and mentoring a talented team. This role demands a deep understanding of machine learning principles, hands-on experience with relevant technologies, and the ability to inspire and guide others. You'll be at the forefront of a rapidly evolving field, learning and growing alongside some of the brightest minds in the industry. If you're passionate about AI, driven to make an impact, and thrive in a dynamic and supportive workplace, we encourage you to join us! The Impact: The Document Platforms and AI team has already delivered breakthrough products and significant business value over the last 3 years. In this role you will be developing our next generation of new products while enhancing existing ones aiming at solving high-impact business problems. Whats in it for you: Be a part of a global company and build solutions at enterprise scale Collaborate with a highly skilled and technically strong team Contribute to solving high complexity, high impact problems Responsibilities: Build production ready data acquisition and transformation pipelines from ideation to deployment. Being a hands-on problem solver and developer helping to extend and manage the data platforms. Apply best practices in data modeling and building ETL pipelines (streaming and batch) using cloud-native solutions Technical leadership: Drive the technical vision and architecture for the extraction project, making key decisions about model selection, infrastructure, and deployment strategies. Model development: Design, develop, and evaluate state-of-the-art machine learning models for information extraction, leveraging techniques from NLP, computer vision (if applicable), and other relevant domains. Data preprocessing and feature engineering: Develop robust pipelines for data cleaning, preprocessing, and feature engineering to prepare data for model training. Model training and evaluation: Train, tune, and evaluate machine learning models, ensuring high accuracy, efficiency, and scalability. Deployment and monitoring: Deploy and maintain machine learning models in a production environment, monitoring their performance and ensuring their reliability. Research and innovation: Stay up-to-date with the latest advancements in machine learning and NLP, and explore new techniques and technologies to improve the extraction process. Collaboration: Work closely with product managers, data scientists, and other engineers to understand project requirements and deliver effective solutions. Code quality and best practices: Ensure high code quality and adherence to best practices for software development. Communication: Effectively communicate technical concepts and project updates to both technical and non-technical audiences. What Were Looking For: 8-10 years of professional software work experience, with a strong focus on Machine Learning, Natural Language Processing (NLP) for information extraction and MLOps Expertise in Python and related NLP libraries (e.g., spaCy, NLTK, Transformers, Hugging Face) Experience with Apache Spark or other distributed computing frameworks for large-scale data processing. AWS/GCP Cloud expertise, particularly in deploying and scaling ML pipelines for NLP tasks. Solid understanding of the Machine Learning model lifecycle, including data preprocessing, feature engineering, model training, evaluation, deployment, and monitoring, specifically for information extraction models . Experience with CI/CD pipelines for ML models, including automated testing and deployment. Docker & Kubernetes experience for containerization and orchestration. OOP Design patterns, Test-Driven Development and Enterprise System design SQL (any variant, bonus if this is a big data variant) Linux OS (e.g. bash toolset and other utilities) Version control system experience with Git, GitHub, or Azure DevOps. Excellent Problem-solving, Code Review and Debugging skills Software craftsmanship, adherence to Agile principles and taking pride in writing good code Techniques to communicate change to non-technical people Nice to have Core Java 17+, preferably Java 21+, and associated toolchain Apache Avro Apache Kafka Other JVM based languages - e.g. Kotlin, Scala C# - in particular .NET Core

Dear Candidate, We are hiring a Robotics Engineer to develop intelligent robotic systems for automation and industrial applications. The role requires expertise in robotics programming, sensor integration, and AI-driven automation. Key Responsibilities: Design and develop robotic systems using ROS, C++, and Python. Implement AI-based perception and motion planning algorithms. Integrate sensors, actuators, and embedded controllers. Optimize robotic navigation and real-time decision-making. Test and validate robotic applications in real-world environments. Required Skills & Qualifications: Robotics Frameworks: ROS, OpenCV, TensorFlow Programming: C++, Python, MATLAB Hardware Integration: LIDAR, IMU, Cameras, Actuators Control Systems: PID, Kalman Filters, Path Planning Experience with autonomous vehicles or robotic arms is a plus. Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Srinivasa Reddy Kandi Delivery Manager Integra Technologies

AI advocates, specializing within the NLP space. You’ll be responsible for developing and mentoring the team to develop their best work to contribute and amplify IBM’s credibility within engineering/AI communities. You will establish partnerships with our technical sales teams to understand the different use cases that are emerging within POCs You should be able to consume and understand information on complex technology topics from trusted sources to author informational articles and tutorials in a clear and concise manner. Your articles should avoid buzzwords and business jargon. Stay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact within our day-to-day work as a team Partner with product marketing to weave in IBM’s point of view on a specific technology topics. Navigate IBM products, like watsonx, to document common industry-related tasks (e.g. using a Jupyter notebook in watsonx.ai to build machine learning models) Collaborate with SEO strategists and user researchers to understand the content needs of our core audience You enjoy public speaking at meetups, conferences, and internal events. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Strong expertise in NLP – familiarity with transformers, LLMs, text classification, sentiment analysis, and named entity recognition. Experience with ML/DL frameworks – such as PyTorch, TensorFlow, Hugging Face, spaCy, or LangChain. Programming skills – proficiency in Python (primary), plus optional knowledge of JavaScript or other scripting languages. AI/ML model lifecycle knowledge – including data preprocessing, model training, evaluation, fine-tuning, and deployment. Hands-on with open-source AI/NLP tools – and understanding of community-driven innovation and best practices. Familiarity with MLOps – model versioning, monitoring, and pipeline management. Preferred technical and professional experience Advocacy & Community Engagement: Content creation – ability to write technical blogs, tutorials, demo code, and record videos/webinars that simplify complex NLP concepts. Public speaking – experience presenting at conferences, meetups, or internal forums. Developer relations – understanding how to engage, grow, and support AI/NLP developer communities. Social media presence – ability to build credibility and promote content on platforms.

Project Role : Software Development Lead Project Role Description : Develop and configure software systems either end-to-end or for a specific stage of product lifecycle. Apply knowledge of technologies, applications, methodologies, processes and tools to support a client, project or entity. Must have skills : Data Engineering, Python (Programming Language) Good to have skills : NA Minimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Software Development Lead, you will be responsible for developing and configuring software systems, applying knowledge of technologies, methodologies, and tools to support projects or clients. You will lead a team in the software development process and ensure successful project delivery. Roles & Responsibilities: Expected to be an SME Collaborate and manage the team to perform Responsible for team decisions Engage with multiple teams and contribute on key decisions Expected to provide solutions to problems that apply across multiple teams Lead the software development team in designing and implementing software solutions Provide technical guidance and mentorship to team members Collaborate with stakeholders to define project requirements and deliverables Professional & Technical Skills: -Proficiency in Python programming with a focus on BOT development and automation.-Experience with BOT frameworks like Rasa, Dialogflow, or Microsoft Bot Framework.-Knowledge of natural language processing (NLP) and machine learning techniques.-Write efficient, modular, and scalable Python code for BOT development and AI-related tasks.-Utilize Python libraries such as NLTK, spaCy, or TensorFlow for natural language processing (NLP).-Create RESTful APIs to integrate BOTs with external systems-Familiarity with APIs, webhooks, and integration tools.-Strong debugging and troubleshooting skills.-Develop intelligent automation scripts using Python to optimize workflows and reduce manual effort.-Implement AI-driven features like intent recognition, entity extraction, and natural language understanding in BOTs-Experience with cloud platforms like AWS, Azure, or Google Cloud for BOT deployment.-Knowledge of chatbot analytics and performance tracking.-Familiarity with Docker and Kubernetes for deploying BOTs in containerized environments.-Understanding of user experience (UX) design principles for BOT interactions.-Strong communication and teamwork skills Ready to work in shifts -12 PM to 10 PM Additional Information: The candidate should have a minimum of 12 years of experience in Data Engineering This position is based at our Hyderabad office A 15 years full time education is required Qualification 15 years full time education

We are seeking a seasoned Data Science Engineer to spearhead the development of intelligent, autonomous AI systems. The ideal candidate will have a robust background in agentic AI, LLMs, SLMs, vector DB, and knowledge graphs. This role involves designing and deploying AI solutions that leverage Retrieval-Augmented Generation (RAG), multi-agent frameworks, and hybrid search techniques to enhance enterprise applications. Your key responsibilities Design & Develop Agentic AI Applications:Utilise frameworks like LangChain, CrewAI, and AutoGen to build autonomous agents capable of complex task execution. Implement RAG Pipelines: Integrate LLMs with vector databases (e.g., Milvus, FAISS) and knowledge graphs (e.g., Neo4j) to create dynamic, context-aware retrieval systems. Fine-Tune Language Models:Customise LLMs (e.g., Gemini, chatgpt, Llama) and SLMs (e.g., Spacy, NLTK) using domain-specific data to improve performance and relevance in specialised applications. NER Models: Train OCR and NLP leveraged models to parse domain-specific details from documents (e.g., DocAI, Azure AI DIS, AWS IDP) Develop Knowledge Graphs: Construct and manage knowledge graphs to represent and query complex relationships within data, enhancing AI interpretability and reasoning. Collaborate Cross-Functionally:Work with data engineers, ML researchers, and product teams to align AI solutions with business objectives and technical requirements. Optimise AI Workflows:Employ MLOps practices to ensure scalable, maintainable, and efficient AI model deployment and monitoring. Your skills and experience 8+ years of professional experience in AI/ML development, with a focus on agentic AI systems. Proficient in Python, Python API frameworks, SQL and familiar with AI/ML frameworks such as TensorFlow or PyTorch. Experience in deploying AI models on cloud platforms (e.g., GCP, AWS). Experience with LLMs (e.g., GPT-4), SLMs (Spacy), and prompt engineering. Understanding of semantic technologies, ontologies, and RDF/SPARQL. Familiarity with MLOps tools and practices for continuous integration and deployment. Skilled in building and querying knowledge graphs using tools like Neo4j. Hands-on experience with vector databases and embedding techniques. Familiarity with RAG architectures and hybrid search methodologies. Experience in developing AI solutions for specific industries such as healthcare, finance, or e-commerce. Strong problem-solving abilities and analytical thinking. Excellent communication skills for cross-functional collaboration. Ability to work independently and manage multiple projects simultaneously.

About the Role: Grade Level (for internal use): 09 The Team: As a member of the Data Transformation team you will work on building ML powered products and capabilities to power natural language understanding, data extraction, information retrieval and data sourcing solutions for S&P Global Market Intelligence and our clients. You will spearhead development of production-ready AI products and pipelines while leading-by-example in a highly engaging work environment. You will work in a (truly) global team and encouraged for thoughtful risk-taking and self-initiative. The Impact: The Data Transformation team has already delivered breakthrough products and significant business value over the last 3 years. In this role you will be developing our next generation of new products while enhancing existing ones aiming at solving high-impact business problems. Whats in it for you: Be a part of a global company and build solutions at enterprise scale Collaborate with a highly skilled and technically strong team Contribute to solving high complexity, high impact problems Key Responsibilities Design, Develop and Deploy ML powered products and pipelines Play a central role in all stages of the data science project life cycle, including: Identification of suitable data science project opportunities Partnering with business leaders, domain experts, and end-users to gain business understanding, data understanding, and collect requirements Evaluation/interpretation of results and presentation to business leaders Performing exploratory data analysis, proof-of-concept modelling, model benchmarking and setup model validation experiments Training large models both for experimentation and production Develop production ready pipelines for enterprise scale projects Perform code reviews & optimization for your projects and team Spearhead deployment and model scaling strategies Stakeholder management and representing the team in front of our leadership Leading and mentoring by example including project scrums What Were Looking For: 2+ years of professional experience in Data Science domain Expertise in Python (Numpy, Pandas, Spacy, Sklearn, Pytorch/TF2, HuggingFace etc.) Experience with SOTA models related to NLP and expertise in text matching techniques, including sentence transformers, word embeddings, and similarity measures Expertise in probabilistic machine learning model for classification, regression & clustering Strong experience in feature engineering, data preprocessing, and building machine learning models for large datasets. Exposure to Information Retrieval, Web scraping and Data Extraction at scale OOP Design patterns, Test-Driven Development and Enterprise System design SQL (any variant, bonus if this is a big data variant) Linux OS (e.g. bash toolset and other utilities) Version control system experience with Git, GitHub, or Azure DevOps. Problem-solving and debugging skills Software craftsmanship, adherence to Agile principles and taking pride in writing good code Techniques to communicate change to non-technical people Nice to have Prior work to show on Github, Kaggle, StackOverflow etc. Cloud expertise (AWS and GCP preferably) Expertise in deploying machine learning models in cloud environments Familiarity in working with LLMs

Minimum of 5-7 years of experience in ML engineering with large-scale production systems. Strong experience with Azure cloud computing and containerization technologies (like Docker, Kubernetes). Experience in API creation and deployments (for ex. Fast API, flask etc.) Experience with Python/OOPs programming languages and data science frameworks like (Pandas, Numpy, TensorFlow, Keras, PyTorch, sklearn). Knowledge of DevOps tools such as Git, Jenkins, Sonar, Nexus is must. Building python wheels and debugging build process. Data pipeline building and debugging (by creating and following log traces). Basic knowledge of DevOps practices. Concepts of Unit Testing and Test-Driven development. Experience with Databricks and its ecosystem is highly preferred External Skills And Expertise Minimum of 5-7 years of experience in ML engineering with large-scale production systems. Strong experience with Azure cloud computing and containerization technologies (like Docker, Kubernetes). Experience in API creation and deployments (for ex. Fast API, flask etc.) Experience with Python/OOPs programming languages and data science frameworks like (Pandas, Numpy, TensorFlow, Keras, PyTorch, sklearn). Knowledge of DevOps tools such as Git, Jenkins, Sonar, Nexus is must. Building python wheels and debugging build process. Data pipeline building and debugging (by creating and following log traces). Basic knowledge of DevOps practices. Concepts of Unit Testing and Test-Driven development. Experience with Databricks and its ecosystem is highly preferred

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Good to have skills : NAMinimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :These roles have many overlapping skills with GENAI Engineers and architects. Description may scaleup/scale down based on expected seniority. Roles & Responsibilities:-Implement generative AI models, identify insights that can be used to drive business decisions. Work closely with multi-functional teams to understand business problems, develop hypotheses, and test those hypotheses with data, collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.-Conducting 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 our products and services.-Optimizing existing generative AI models for improved performance, scalability, and efficiency.-Ensure data quality and accuracy-Leading the design and development of prompt engineering strategies and techniques to optimize the performance and output of our GenAI models.-Implementing cutting-edge NLP techniques and prompt engineering methodologies to enhance the capabilities and efficiency of our GenAI models.-Determining the most effective prompt generation processes and approaches to drive innovation and excellence in the field of AI technology, collaborating with AI researchers and developers-Experience working with cloud based platforms (exampleAWS, Azure or related)-Strong problem-solving and analytical skills-Proficiency in handling various data formats and sources through Omni Channel for Speech and voice applications, part of conversational AI-Prior statistical modelling experience-Demonstrable experience with deep learning algorithms and neural networks-Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.-Contributing to the establishment of best practices and standards for generative AI development within the organization. Professional & Technical Skills: -Must have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.-Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.-Must have strong knowledge of data structures, algorithms, and software engineering principles.-Must be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.-Need to have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.-Must be familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.-Need to have knowledge of software development methodologies, such as Agile or Scrum.-Possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions. Additional Information:-Must have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is highly desirable.-strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.-You possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Qualification 15 years full time education

Job Overview: We are seeking a Generative AI Developer with expertise in Retrieval-Augmented Generation (RAG) architecture, LangChain, Python, and Large Language Models (LLMs) . The ideal candidate will have experience in building chatbots using LLMs and a strong understanding of LLMOps/MLOps for scalable AI solutions. Key Responsibilities: Develop and optimize Generative AI applications using LLMs, RAG pipelines, and LangChain . Design and implement chatbot solutions leveraging LLMs for conversational AI. Integrate retrieval mechanisms to enhance chatbot accuracy and contextual relevance. Apply LLMOps/MLOps best practices for model deployment, monitoring, and optimization. Collaborate with cross-functional teams to integrate AI solutions into business applications. Research and implement the latest advancements in Generative AI and NLP. Ensure scalability and efficiency of AI models using vector databases and embeddings . Required Skills: Expertise in RAG architecture for AI-driven retrieval systems. Strong proficiency in Python for AI model development. Experience with LangChain for building AI-powered applications. Hands-on experience in chatbot development using LLMs. Knowledge of LLMOps/MLOps for model lifecycle management. Understanding of vector databases (FAISS, Pinecone) for efficient data retrieval. Familiarity with cloud-based AI services (AWS Bedrock, Azure AI). Preferred Skills: Experience with NLP frameworks (spaCy, Hugging Face, NLTK). Knowledge of deep learning architectures (Transformers, CNN, RNN). Proficiency in Streamlit for AI application prototyping. Exposure to CI/CD pipelines for AI model deployment.

Position Overview : We are seeking an experienced NLP & LLM Specialist to join our team. The ideal candidate will have deep expertise in working with transformer-based models, including GPT, BERT, T5, RoBERTa, and similar models. This role requires experience in fine-tuning these pre-trained models on domain-specific tasks, as well as crafting and optimizing prompts for natural language processing tasks such as text generation, summarization, question answering, classification, and translation. The candidate should be proficient in Python and familiar with NLP libraries like Hugging Face, SpaCy, and NLTK, with a solid understanding of model evaluation metrics. Roles and Responsibilities : - Model Expertise : Work with transformer models such as GPT, BERT, T5, RoBERTa, and others for a variety of NLP tasks, including text generation, summarization, classification, and translation. - Model Fine-Tuning : Fine-tune pre-trained models on domain-specific datasets to improve performance for specific applications such as summarization, text generation, and question answering. - Prompt Engineering : Craft clear, concise, and contextually relevant prompts to guide transformer-based models towards generating desired outputs for specific tasks. - Iterate on prompts to optimize model performance. - Instruction-Based Prompting : Implement instruction-based prompting to guide the model toward achieving specific goals, ensuring that the outputs are contextually accurate and aligned with task objectives. - Zero-shot, Few-shot, Many-shot Learning : Utilize zero-shot, few-shot, and many-shot learning techniques to improve model performance without the need for full retraining. - Chain-of-Thought (CoT) Prompting : Implement Chain-of-Thought (CoT) prompting to guide models through complex reasoning tasks, ensuring that the outputs are logically structured and provide step-by-step explanations. - Model Evaluation : Use evaluation metrics such as BLEU, ROUGE, and other relevant metrics to assess and improve the performance of models for various NLP tasks. - Model Deployment : Support the deployment of trained models into production environments and integrate them into existing systems for real-time applications. - Bias Awareness : Be aware of and mitigate issues related to bias, hallucinations, and knowledge cutoffs in LLMs, ensuring high-quality and reliable outputs. - Collaboration : Collaborate with cross-functional teams including engineers, data scientists, and product managers to deliver efficient and scalable NLP solutions. Must Have Skill : - Overall 7 years with at least 5+ years of experience working with transformer-based models and NLP tasks, with a focus on text generation, summarization, question answering, classification, and similar tasks. - Expertise in transformer models like GPT (Generative Pre-trained Transformer), BERT (Bidirectional Encoder Representations from Transformers), T5 (Text-to-Text Transfer Transformer), RoBERTa, and similar models. - Familiarity with model architectures, attention mechanisms, and self-attention layers that enable LLMs to generate human-like text. - Experience in fine-tuning pre-trained models on domain-specific datasets for tasks such as text generation, summarization, question answering, classification, and translation. - Familiarity with concepts like attention mechanisms, context windows, tokenization, and embedding layers. - Awareness of biases, hallucinations, and knowledge cutoffs that can affect LLM performance and output quality. - Expertise in crafting clear, concise, and contextually relevant prompts to guide LLMs towards generating desired outputs. - Experience in instruction-based prompting. - Use of zero-shot, few-shot, and many-shot learning techniques for maximizing model performance without retraining. - Experience in iterating on prompts to refine outputs, test model performance, and ensure consistent results. - Crafting prompt templates for repetitive tasks, ensuring prompts are adaptable to different contexts and inputs. - Expertise in chain-of-thought (CoT) prompting to guide LLMs through complex reasoning tasks by encouraging step-by-step breakdowns. - Proficiency in Python and experience with NLP libraries (e.g., Hugging Face, SpaCy, NLTK). - Experience with transformer-based models (e.g., GPT, BERT, T5) for text generation tasks. - Experience in training, fine-tuning, and deploying machine learning models in an NLP context. - Understanding of model evaluation metrics (e.g., BLEU, ROUGE). Qualification : - BE/B.Tech or Equivalent degree in Computer Science or related field. - Excellent communication skills in English, both verbal and written.

Your Role 4-5 years of experience hand-on experience of data-science and machine learning techniques & algorithms for supervised & unsupervised problems, NLP and computer vision. Good, applied statistics skills, such as distributions, statistical inference & testing, etc. in preferably in Life Sciences domain. Proficient in data mining and data cleansing techniques. 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, Go, SAS, Matlab etc. Experience with common data science toolkits, such as NumPy, Pandas, StatModel, Scikit learn, SciPy, NLTK, Spacy, Gensim, OpenCV, MLFlow, Tensorflow, Pytorch etc. Excellent understanding and hand-on experience of data-science and machine learning techniques & algorithms for supervised and unsupervised problems (such as k-NN, Regression, Naive Bayes, SVM, Decision Tree, Random Forests, k-means, PCA, SVD, GenAI (LLM) etc.). Good applied statistics skills, such as distributions, statistical inference & testing, etc. Experience with common data science frameworks such as Tensorflow, Keras, PyTorch, XGBoost, H2O etc. Exposure or knowledge in cloud (AWS/GCP/Azure) and big data technologies such as Hadoop, Hive, MapReduce, Pyspark etc. Your Profile Post - Graduate degree (M.E/ M.Tech/ M.Sc etc) Experience on deployment of model in production. Experience in data management and visualization task. Excellent understanding / hand-on experience in NLP and computer vision. Familiarity with database systems of SQL and NoSQL. Familiarity with data visualization tools such as Tableau, MS PowerBI etc Ability to think creatively to solve real world business problems. Critical thinking and problem solving capabilities. Data-oriented personality. Hands on experience in GenAI. Good presentation skills. Proficient in verbal and written communication. Knowledge/ hand-on experience Exposure on large scale dataset and respective tool & framework like Hadoop, Pyspark, etc. Knowledge/ hand-on experience on deployment of model in production & deployment.

Responsibilities: Develop and implement machine learning algorithms and models, particularly focusing on natural language processing (NLP) applications. Develop and maintain APIs using web frameworks like Django, Flask, or similar, ensuring efficient and reliable integration of machine learning solutions into applications. Stay updated with the latest advancements in machine learning, NLP, and cloud technologies, and contribute to the continuous improvement of the team's knowledge and practices. Deploy machine learning models to cloud platforms such as Azure and Google Cloud for production use. Design, train, and optimize deep learning models using TensorFlow, Keras, and PyTorch for NLP tasks. Utilize SQL for data manipulation, querying, and analysis, ensuring data quality and integrity throughout the process. Collaborate with cross-functional teams to understand requirements and translate them into scalable and efficient solutions. Utilize Azure services for developing and deploying document processing solutions, leveraging large language models like GPT3.5-Turbo and GPT-4. Qualifications To succeed in this position, you must: Bachelor's or Master's degree in Computer Science, AI, or a related field. Strong proficiency in Python and familiarity with relevant libraries and frameworks (NumPy, SciPy, scikit-learn, pandas, matplotlib, spaCy, NLTK, etc.). Experience with deep learning frameworks such as TensorFlow, Keras, and PyTorch, with a focus on NLP applications. Familiarity with cloud platforms (e.g., Azure, Google Cloud) Experience with Django, Flask, or similar web frameworks for API development. Proficiency in SQL for data manipulation and analysis. Strong communication skills and ability to collaborate effectively in a cross-functional team environment. Experience with telecom integrations (e.g., Avaya, Twilio) would be advantageous. Develop and implement enterprise solutions for document processing, utilizing cutting-edge technologies like large language models and generative AI. Handson working with Azure Services, Large Language Models like GPT3.5-Turbo, GPT-4 etc

Role & responsibilities Overall 7 years with at least 5+ years of experience working with transformer-based models and NLP tasks, with a focus on text generation, summarization, question answering, classification, and similar tasks. Expertise in transformer models like GPT (Generative Pre-trained Transformer), BERT (Bidirectional Encoder Representations from Transformers), T5 (Text-to-Text Transfer Transformer), RoBERTa, and similar models. Familiarity with model architectures, attention mechanisms, and self-attention layers that enable LLMs to generate human-like text. Experience in fine-tuning pre-trained models on domain-specific datasets for tasks such as text generation, summarization, question answering, classification, and translation. Familiarity with concepts like attention mechanisms, context windows, tokenization, and embedding layers. Awareness of biases, hallucinations, and knowledge cutoffs that can affect LLM performance and output quality. Expertise in crafting clear, concise, and contextually relevant prompts to guide LLMs towards generating desired outputs. Experience in instruction-based prompting Use of zero-shot, few-shot, and many-shot learning techniques for maximizing model performance without retraining. Experience in iterating on prompts to refine outputs, test model performance, and ensure consistent results. Crafting prompt templates for repetitive tasks, ensuring prompts are adaptable to different contexts and inputs. Expertise in chain-of-thought (CoT) prompting to guide LLMs through complex reasoning tasks by encouraging step-by-step breakdowns. Proficiency in Python and experience with NLP libraries (e.g., Hugging Face, SpaCy, NLTK). Experience with transformer-based models (e.g., GPT, BERT, T5) for text generation tasks. Experience in training, fine-tuning, and deploying machine learning models in an NLP context. Understanding of model evaluation metrics (e.g., BLEU, ROUGE)

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Good to have skills : NAMinimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :These roles have many overlapping skills with GENAI Engineers and architects. Description may scaleup/scale down based on expected seniority. Roles & Responsibilities:-Implement generative AI models, identify insights that can be used to drive business decisions. Work closely with multi-functional teams to understand business problems, develop hypotheses, and test those hypotheses with data, collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.-Conducting 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 our products and services.-Optimizing existing generative AI models for improved performance, scalability, and efficiency.-Ensure data quality and accuracy-Leading the design and development of prompt engineering strategies and techniques to optimize the performance and output of our GenAI models.-Implementing cutting-edge NLP techniques and prompt engineering methodologies to enhance the capabilities and efficiency of our GenAI models.-Determining the most effective prompt generation processes and approaches to drive innovation and excellence in the field of AI technology, collaborating with AI researchers and developers-Experience working with cloud based platforms (exampleAWS, Azure or related)-Strong problem-solving and analytical skills-Proficiency in handling various data formats and sources through Omni Channel for Speech and voice applications, part of conversational AI-Prior statistical modelling experience-Demonstrable experience with deep learning algorithms and neural networks-Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.-Contributing to the establishment of best practices and standards for generative AI development within the organization. Professional & Technical Skills: -Must have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.-Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.-Must have strong knowledge of data structures, algorithms, and software engineering principles.-Must be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.-Need to have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.-Must be familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.-Need to have knowledge of software development methodologies, such as Agile or Scrum.-Possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions. Additional Information:-Must have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is highly desirable.-strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.-You possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Qualification 15 years full time education

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Good to have skills : NAMinimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :These roles have many overlapping skills with GENAI Engineers and architects. Description may scaleup/scale down based on expected seniority. Roles & Responsibilities:-Implement generative AI models, identify insights that can be used to drive business decisions. Work closely with multi-functional teams to understand business problems, develop hypotheses, and test those hypotheses with data, collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.-Conducting 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 our products and services.-Optimizing existing generative AI models for improved performance, scalability, and efficiency.-Ensure data quality and accuracy-Leading the design and development of prompt engineering strategies and techniques to optimize the performance and output of our GenAI models.-Implementing cutting-edge NLP techniques and prompt engineering methodologies to enhance the capabilities and efficiency of our GenAI models.-Determining the most effective prompt generation processes and approaches to drive innovation and excellence in the field of AI technology, collaborating with AI researchers and developers-Experience working with cloud based platforms (exampleAWS, Azure or related)-Strong problem-solving and analytical skills-Proficiency in handling various data formats and sources through Omni Channel for Speech and voice applications, part of conversational AI-Prior statistical modelling experience-Demonstrable experience with deep learning algorithms and neural networks-Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.-Contributing to the establishment of best practices and standards for generative AI development within the organization. Professional & Technical Skills: -Must have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.-Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.-Must have strong knowledge of data structures, algorithms, and software engineering principles.-Must be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.-Need to have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.-Must be familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.-Need to have knowledge of software development methodologies, such as Agile or Scrum.-Possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions. Additional Information:-Must have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is highly desirable.-strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.-You possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Qualification 15 years full time education

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :These roles have many overlapping skills with GENAI Engineers and architects. Description may scaleup/scale down based on expected seniority. Roles & Responsibilities:-Implement generative AI models, identify insights that can be used to drive business decisions. Work closely with multi-functional teams to understand business problems, develop hypotheses, and test those hypotheses with data, collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.-Conducting 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 our products and services.-Optimizing existing generative AI models for improved performance, scalability, and efficiency.-Ensure data quality and accuracy-Leading the design and development of prompt engineering strategies and techniques to optimize the performance and output of our GenAI models.-Implementing cutting-edge NLP techniques and prompt engineering methodologies to enhance the capabilities and efficiency of our GenAI models.-Determining the most effective prompt generation processes and approaches to drive innovation and excellence in the field of AI technology, collaborating with AI researchers and developers-Experience working with cloud based platforms (exampleAWS, Azure or related)-Strong problem-solving and analytical skills-Proficiency in handling various data formats and sources through Omni Channel for Speech and voice applications, part of conversational AI-Prior statistical modelling experience-Demonstrable experience with deep learning algorithms and neural networks-Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.-Contributing to the establishment of best practices and standards for generative AI development within the organization. Professional & Technical Skills: -Must have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.-Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.-Must have strong knowledge of data structures, algorithms, and software engineering principles.-Must be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.-Need to have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.-Must be familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.-Need to have knowledge of software development methodologies, such as Agile or Scrum.-Possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions. Additional Information:-Must have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is highly desirable.-strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.-You possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Qualification 15 years full time education

Why this job matters The Software Engineering Professional supports the execution of the software engineering strategy and roadmap that supports BT's commercial strategy through cross functional project and technical delivery and the participation of a team that pursues innovation as well as engineering excellence. Required Ansible:Strong experience in using Ansible for configuration management, automation of infrastructure tasks, and orchestration. Ability to write efficient playbooks, roles, and manage inventories across environments. Jenkins:Expertise in setting up and maintaining Jenkins pipelines for continuous integration and continuous deployment (CI/CD). Familiarity with Jenkins plugins, scripted and declarative pipelines, and integration with version control systems like Git. Docker:Solid understanding of containerization concepts using Docker. Experience in building, deploying, and managing Docker containers, writing Dockerfiles, and working with Docker Compose for multi-container applications. Django:Hands-on experience in developing web applications using the Django framework. Knowledge of Django ORM, views, templates, middleware, and RESTful API development. Familiarity with deployment practices and performance optimization. Candidate need to have a good understanding on the following concepts System architecture CI/CD pipelines Containerization Configuration management Web application frameworks Familiarity with cloud platforms and agile methodologies is also beneficial Desirable: Natural Language Understanding (NLU): Exposure to NLU concepts and tools such as spaCy, NLTK, or transformer-based models. Ability to integrate NLU capabilities into applications to enable intelligent text processing, intent recognition, and conversational interfaces