145 Spacy Jobs - Page 6

Position Overview: The Provider Technology Shared Services Engineering team is seeking an Software Engineer Lead Analyst for a Band 3 Contributor Career Track position. The Software Engineer Lead Analyst will play a critical role in system development within the broader Provider Technology Solutions and Engineering organization, significantly influencing Operations and Technology Product Management. This position will provide expertise in the engineering, design, installation and startup of automated systems, including a self-service onboarding kit that enables users to begin utilizing the solution within minutes. The solutions developed will be accessible to individuals with minimal technical skills and will require no additional coding, ensuring zero maintenance is needed. As a member of our team, you will operate within a high-performance, high-frequency enterprise technology environment. This role entails collaborating closely with IT management and staff to identify automated solutions that leverage existing resources with tailored configurations for each use case. The objective is to minimize redundancy in solutions while promoting an enterprise mindset focused on reusability and maintaining high standards, ultimately ensuring minimal future maintenance requirements. The Software Engineer Lead Analyst demonstrates significant creativity, foresight, and sound judgment in the conception, planning, and execution of initiatives. This role requires extensive professional knowledge and expertise to effectively advise functional leaders. Additionally, the Lead Analyst stays informed about the latest advancements in technology, including AI and machine learning, to enhance both existing and new automation solutions. These solutions are designed to optimize production costs while facilitating the addition or updating of features aimed at improving the overall software development lifecycle experiences. Responsibilities: Provide comprehensive consultation to business unit and IT management, as well as personnel, regarding all facets of application development, testing and automation solutions across diverse development, financial, operational, and computing environments. Offers leadership and strategic vision in architectural design and AI/ML guidance for the team. Perform comprehensive research to identify and recommend the most efficient, cost-effective, and scalable AI/ML automation solutions applicable throughout the Software Development Life Cycle (SDLC). This includes areas such as test data generation, code generation, test case generation, test script generation, root cause analysis, predictive analysis, etc., with the aim of enhancing the overall SDLC from development to production support. Ensures that engineering solutions are aligned with the overall Technology strategy while addressing all application requirements. Demonstrate industry-leading technical abilities that enhance product quality and optimize day-to-day operations. Understand how changes impact work upstream and downstream including various back-end and front-end architectural modules. Enhance personnel effectiveness using heat matrices to prioritize Quality and Development Engineering resources on high-impact interfaces while identifying areas of lesser focus. Proactively monitor and manage the design of supported automation solutions, ensuring scalability, stability, flexibility, simplicity, performance, availability, security, and capacity. Develop and implement automation solutions to improve engineering and operational efficiency. Troubleshoot and optimize automated solutions and related artifacts to ensure seamless execution in CI/CD pipelines and on local machines, minimizing software and package dependencies or conflicts to reduce cycle time. Execute on a strategy to hand over the automation solutions to every Agile teams for adoption and use within their areas of focus, requiring zero maintenance and minimal effort for any enhancements without delving into coding. Encouraging and building automated processes wherever possible. Recognized internally as a subject matter expert. Required Skills: Foundations in Machine Learning and Deep Learning: Understanding algorithms, neural networks, supervised and unsupervised learning, and deep learning frameworks like TensorFlow, PyTorch, and Keras. Generative Models: Knowledge of generative models such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformers. Natural Language Processing (NLP): Knowledge in NLP techniques and libraries (e.g., spaCy, NLTK, Hugging Face Transformers) for text generation tasks. Model Deployment: Experience with deploying models using services like TensorFlow Serving, TorchServe, or cloud-based solutions (e.g., AWS SageMaker, Google AI Platform). Basic understanding of implementing Prompt Engineering, Finetuning and RAG. Strong foundation and practical experience in programming languages, especially Python, within the context of AI/ML workflows, crucial for transitioning from traditional software development processes to optimized and innovative solutions that enhance market agility. Containerization and Orchestration: Experience with Docker and Kubernetes / OpenShift for containerization and orchestration of applications. CI/CD Pipelines: Knowledge of continuous integration and continuous deployment tools and practices. Security Best Practices: understanding of security principles and best practices for protecting data and systems, including IAM, encryption and network Security. Cloud Services: Familiarity with cloud platforms like AWS / Google Cloud / Azure for deploying and managing applications and AI models. Required Experience & Education: A Bachelor's degree in Computer Science or a related field is required. A minimum of 5 years of experience in Software Development, including 3 years of professional experience in AI and Machine Learning engineering. At least 3 years of experience in Agile methodologies is required. Familiarity with an onshore/offshore operational model is essential. Demonstrated experience in the architecture, design and development of large-scale enterprise application solutions is required. Desired Experience: Proficient in AI / ML practices and automation techniques. Experienced in programming languages and scripting, including Python, Shell, Bash, Groovy, Ansible and Docker. Providing coaching and guidance to team members. Location & Hours of Work: Full-time position, working 40 hours per week. Expected overlap with US hours as appropriate. Primarily based in the Innovation Hub in Hyderabad, India in a hybrid working model (3 days WFO and 2 days WAH)

Overview: We are seeking an exceptional and technically accomplished Senior Data Scientist to join our rapidly growing team. This role is ideal for a hands-on AI expert with deep experience in Large Language Models (LLMs) , Natural Language Processing (NLP) , Cognitive AI , Conversational AI , and Agentic AI systems . You will work on designing, developing, and scaling state-of-the-art AI solutions that drive business innovation, operational intelligence, and customer experience transformation. This is a high-impact individual contributor role, focused on technical excellence and product-grade AI development. Key Responsibilities LLM & Cognitive AI Solution Development Architect and fine-tune LLM-based solutions (e.g., GPT, LLaMA, Claude, Mistral) using transfer learning, PEFT, and retrieval-augmented generation (RAG). Develop Agentic AI architectures with autonomous behavior and multi-agent collaboration capabilities. Apply prompt engineering , in-context learning , and tool former-style techniques to enable complex reasoning and task execution. Build Conversational AI systems using Transformer-based backbones and orchestration tools (LangChain, Haystack, Rasa, Semantic Kernel). Natural Language Processing (NLP) Design and implement advanced NLP pipelines for semantic search, summarization, NER, text classification, and knowledge extraction. Utilize and integrate tools such as SpaCy , BERT , RoBERTa , GloVe , Word2Vec , NLTK , and TextBlob . Conduct advanced text preprocessing, dependency parsing, sentiment analysis, tokenization, and multilingual NLP modeling. AI/ML Engineering Build scalable ML pipelines with FastAPI, gRPC, and RESTful interfaces. Containerize services using Docker and deploy to production environments via Kubernetes and cloud-native workflows. Integrate models into real-time and batch data systems, optimizing for latency, throughput, and reliability. Cloud & Infrastructure Develop and deploy solutions on AWS , Azure , or Google Cloud Platform (GCP) . Leverage services like SageMaker, Vertex AI, Azure ML Studio, and serverless orchestration tools. MLOps & CI/CD Design and maintain end-to-end MLOps pipelines using tools like MLflow, Kubeflow, or TFX for reproducibility and traceability. Automate model testing, monitoring, versioning, and rollback strategies in production. Big Data & Analytics Apply Spark, Hadoop, and Hive to process large-scale datasets efficiently. Perform complex data transformations and statistical modeling to extract actionable insights. Database & Data Engineering Interface with SQL and NoSQL systems (PostgreSQL, MongoDB, DynamoDB, etc.) for efficient data retrieval and processing. Design data schemas and optimize query performance for AI-centric applications. Cross-functional Collaboration Work closely with product managers, engineers, and domain experts to identify high-impact problems and deliver AI-driven solutions. Communicate findings and solution architectures clearly to technical and non-technical stakeholders. Technical Skills Expert in Python , PyTorch, HuggingFace Transformers, LangChain, and OpenAI/Anthropic/LLama APIs. Deep understanding of Transformer architectures , Attention Mechanisms , and LLM fine-tuning techniques . Familiarity with Agentic AI paradigms , including memory management, autonomous goal completion, and tool use. Strong experience with cloud platforms, container orchestration (Docker + Kubernetes), and deployment automation. Proficient in statistical modeling, probabilistic reasoning, and experimental design. Bonus Experience in Online Reputation Management (ORM) or product-centric platforms . Publications or open-source contributions in AI/ML/NLP.

Role Overview: We' re looking for a Lead Data Scientist to join our fast-growing, mission-driven team. This is a high-impact leadership role at the intersection of technology, strategy, and innovation where your expertise will power intelligent solutions that redefine how we think about data, products, and customer experience. If you thrive in high-performance environments and want to lead cutting-edge projects with Generative AI, LLMs, and large-scale NLP systems, this is your opportunity to make a lasting impact. Key Responsibilities: Build the Future with AI/ML Architect scalable AI systems to solve real-world, high-value business challenges cross domains. Design and deploy cutting-edge solutions with Generative AI, Transformer architectures, and custom Large Language Models (LLMs). Apply state-of-the-art ML techniques prompt engineering, transfer learning, multi-modal learning to push the boundaries of what's possible. NLP at Scale Lead the development of advanced NLP systems: semantic search, question answering, summarization, classification, and conversational AI. Work with best-in-class models and libraries: BERT, GPT, RoBERTa, Word2Vec, SpaCy, NLTK, Hugging Face Transformers, and more. Leverage language understanding to transform unstructured data into strategic insights. Full-Lifecycle Model Deployment Build robust MLOps pipelines for training, testing, deployment, and monitoring using MLflow, Kubeflow, Airflow, and CI/CD tools. Containerize and orchestrate AI models using Docker and Kubernetes across cloud environments (AWS, GCP, Azure). Design APIs and inference services using FastAPI or gRPC, optimized for performance, scalability, and uptime. Lead, Inspire, and Elevate Build and mentor a world-class data science team, nurturing talent and fostering a culture of curiosity, experimentation, and technical excellence. Drive the data science strategy, influence key decisions, and align AI initiatives with business goals. Establish best-in-class practices for model development, code quality, documentation, and performance evaluation. Data at the Core Work hands-on with structured, semi-structured, and unstructured data. Optimize high-volume data pipelines, integrate with SQL and NoSQL databases, and leverage big data ecosystems like Spark, Hive, and Hadoop. Use statistical modeling and experimental design to derive actionable intelligence from data Collaborate Across the Enterprise Work closely with engineering, product, and executive teams to define problems, explore solutions, and deliver AI products that move the needle. Translate technical concepts into strategic recommendations and insights that influence roadmaps and revenue. Champion AI literacy and advocate for ethical, explainable, and scalable data science across the organization. Education Bachelors or Master’s in Computer Science, AI, Data Science, Machine Learning, Engineering, or a related technical discipline. PhD is a plus. Experience 6+ years of experience in data science or machine learning, with 2+ years in a leadership or managerial role. Proven record of building and deploying AI solutions at scale in real-world production environments. Experience in GenAI, NLP, cloud-native architectures, and full-cycle ML development. Technical Expertise Languages & Libraries: Python, Scikit-learn, PyTorch, TensorFlow, Hugging Face, NumPy, Pandas NLP: BERT, GPT, Word2Vec, SpaCy, NLTK, TextBlob, CoreNLP, Transformer-based architectures Cloud & Deployment: AWS, Azure, GCP, Docker, Kubernetes, FastAPI, gRPC Big Data: Spark, Hive, Hadoop, Kafka Data Systems: PostgreSQL, MongoDB, Cassandra, Snowflake, BigQuery MLOps & Monitoring: MLflow, Airflow, Kubeflow, Prometheus, Grafana Nice to Have Experience in online reputation management, customer analytics, or product-led organizations. Familiarity with responsible AI, fairness, and explainability techniques (SHAP, LIME).

Required skills and qualifications 5+ years of experience as a Python Developer with a strong portfolio of projects. Bachelor's degree in Computer Science, Software Engineering or a related field. In-depth understanding of the Python software development stacks, ecosystems, frameworks and tools such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, sci-kit-learn and PyTorch. MATLAB experience is must Experience with front-end development using HTML, CSS, and JavaScript. Familiarity with database technologies such as SQL and NoSQL. Excellent problem-solving ability with solid communication and collaboration skills. Preferred skills and qualifications Experience with popular Python frameworks such as Django, Flask or Pyramid. Knowledge of data science and machine learning concepts and tools. A working understanding of cloud platforms such as AWS, Google Cloud or Azure. Contributions to open-source Python projects or active involvement in the Python community.

#ONSITE We are looking for a highly experienced NLP Analyst with deep expertise in linguistic data analysis, annotation design, and production-scale NLP model evaluation. This role requires a blend of linguistic acumen, analytical rigor, and real-world application experience. You will drive the design and execution of NLP initiatives across diverse domains and guide cross-functional teams on best practices in language data handling and annotation quality. Key Responsibilities Manage large-scale text annotation and labeling pipelines for supervised and semi-supervised learning. Conduct advanced linguistic analysis of unstructured content (e.g., clinical notes, legal contracts, customer communications, claim documents) to identify patterns, gaps, and modeling opportunities. Define and enforce annotation schemas and QA protocols for complex NLP tasks (e.g., NER, relation extraction, coreference resolution, sentiment/intent classification). Evaluate and improve the performance of NLP models through rigorous error analysis and metric-driven feedback loops. Collaborate with ML/NLP engineers, data scientists, and domain experts to build robust NLP pipelines that scale across use cases. Lead internal research efforts on emerging NLP methodologies, including LLM prompt engineering, hybrid rule-learning approaches, and few-shot learning. Provide mentorship to junior analysts and contribute to developing internal NLP knowledge repositories and annotation standards. Required Qualifications Master’s in computational Linguistics, NLP, Data Science, Computer Science, or a related field. 5+ years of professional experience in NLP, with a strong track record of hands-on work in data annotation, language model evaluation, and NLP pipeline development. Expertise in Python and key NLP libraries (spaCy, NLTK, Scikit-learn, Hugging Face Transformers, etc.). Advanced proficiency in building and managing annotation workflows using tools like Prodigy, doccano, Brat, or in-house platforms. Deep understanding of linguistic structures (syntax, semantics, pragmatics) and their application to real-world NLP challenges. Experience evaluating ML/NLP models using metrics like F1, ROUGE, BLEU, precision/recall, and embedding-based similarity. Solid grasp of vectorization methods (TF-IDF, embeddings, transformer-based encodings) and modern language models (e.g., BERT, GPT, LLaMA). Preferred Qualifications Experience with domain-specific NLP (e.g., clinical/biomedical, legal, fintech). Knowledge of knowledge graph construction, relation extraction, and entity linking. Experience integrating structured/unstructured data for downstream AI/ML applications. Familiarity with prompt engineering for LLMs and tuning foundation models. Strong data querying and visualization skills (SQL, pandas, seaborn, Power BI/Tableau). Perficient is always looking for the best and brightest talent and we need you! We’re a quickly-growing, global digital consulting leader, and we’re transforming the world’s largest enterprises and biggest brands. You’ll work with the latest technologies, expand your skills, and become a part of our global community of talented, diverse, and knowledgeable colleagues.

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 : Natural Language Processing (NLP) Good to have skills : NA Minimum 7 year(s) of experience is required Educational Qualification : 15 years full time education Summary: As an AI / ML Engineer, you will develop applications and systems that utilize AI tools and Cloud AI services. You will be responsible for creating a proper cloud or on-prem application pipeline with production-ready quality. Additionally, you will apply GenAI models as part of the solution, which may include deep learning, neural networks, chatbots, and image processing. Your role will involve developing cutting-edge AI solutions and contributing to the advancement of technology in this field. Roles & Responsibilities: Build predictive models, develop advanced algorithms that extract and classify information from large datasets quantify model performance 2 Evaluate emerging technologies that may contribute to our analytical platform Identify and exploit new patterns in data using various techniques 3 Work with product managers and engineers to deploy models into production 4 Work with developers to integrate front end with backend Good to have the knowledge in Insurance, Banking and Capital markets domains Professional & Technical Skills: strong coding ability and familiarity with Python R programming languages Relevant experience, passionate about applications in data crunching billions of data points for statistical modeling, data mining for insights and recommendation solutions 2 Worked with ML data mining toolkits like NLP, Semantic Web, R,Core NLP,NLTK etc Information retrieval libraries like Lucene SOLR fast paced, test driven, collaborative and iterative programming env 3 Analyze data, develop robust statistical algorithms model Good in communication Good in Team handling Additional Information: - A 15 years full-time education is required

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 : Natural Language Processing (NLP) Good to have skills : NA Minimum 7 year(s) of experience is required Educational Qualification : 15 years full time education Summary: As an AI / ML Engineer, you will develop applications and systems that utilize AI tools and Cloud AI services. You will be responsible for creating a proper cloud or on-prem application pipeline with production-ready quality. Additionally, you will apply GenAI models as part of the solution, which may include deep learning, neural networks, chatbots, and image processing. Your role will involve developing cutting-edge AI solutions and contributing to the advancement of technology in this field. Roles & Responsibilities: 1 Build predictive models, develop advanced algorithms that extract and classify information from large datasets quantify model performance 2 Evaluate emerging technologies that may contribute to our analytical platform Identify and exploit new patterns in data using various techniques 3 Work with product managers and engineers to deploy models into production 4 Work with developers to integrate front end with backend Good to have the knowledge in Insurance, Banking and Capital markets domains Professional & Technical Skills: 1 strong coding ability and familiarity with Python R programming languagesRelevant experience, passionate about applications in data crunching billions of datapoints for statistical modeling,data mining for insights and recommendation solutions 2 Worked with ML data mining toolkits like NLP,Semantic Web,R,Core NLP,NLTK etcInformation retrieval libraries like Lucene SOLR fast paced,test driven, collaborative and iterative programming env 3 Analyze data,develop robust statistical algorithms model Good in communication Good in Team handling Additional Information: - A 15 years full-time education is required

Description - External Role – AIML Data Scientist Location : Kochi Mode of Interview - In Person Date : 14th June 2025 (Saturday) Job Description: 1. Be a hands on problem solver with consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges a. Use the knowledge of wide variety of AI/ML techniques and algorithms to find what combinations of these techniques can best solve the problem b. Improve Model accuracy to deliver greater business impact c. Estimate business impact due to deployment of model 2. Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge 3. Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines 4. Design , develop & deploy Deep learning models using Tensorflow / Pytorch 5. Experience in using Deep learning models with text, speech, image and video data a. Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etc b. Design and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCV c. Knowledge of State of the art Deep learning algorithms 6. Optimize and tune Deep Learnings model for best possible accuracy 7. Use visualization tools/modules to be able to explore and analyze outcomes & for Model validation eg: using Power BI / Tableau 8. Work with application teams, in deploying models on cloud as a service or on-prem a. Deployment of models in Test / Control framework for tracking b. Build CI/CD pipelines for ML model deployment 9. Integrating AI&ML models with other applications using REST APIs and other connector technologies 10. Constantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact. Technology/Subject Matter Expertise Sufficient expertise in machine learning, mathematical and statistical sciences Use of versioning & Collaborative tools like Git / Github Good understanding of landscape of AI solutions – cloud, GPU based compute, data security and privacy, API gateways, microservices based architecture, big data ingestion, storage and processing, CUDA Programming Develop prototype level ideas into a solution that can scale to industrial grade strength Ability to quantify & estimate the impact of ML models Softskills Profile Curiosity to think in fresh and unique ways with the intent of breaking new ground. Must have the ability to share, explain and “sell” their thoughts, processes, ideas and opinions, even outside their own span of control Ability to think ahead, and anticipate the needs for solving the problem will be important Ability to communicate key messages effectively, and articulate strong opinions in large forums Desirable Experience: Keen contributor to open source communities, and communities like Kaggle Ability to process Huge amount of Data using Pyspark/Hadoop Development & Application of Reinforcement Learning Knowledge of Optimization/Genetic Algorithms Operationalizing Deep learning model for a customer and understanding nuances of scaling such models in real scenarios Optimize and tune deep learning model for best possible accuracy Understanding of stream data processing, RPA, edge computing, AR/VR etc Appreciation of digital ethics, data privacy will be important Experience of working with AI & Cognitive services platforms like Azure ML, IBM Watson, AWS Sagemaker, Google Cloud will all be a big plus Experience in platforms like Data robot, Cognitive scale, H2O.AI etc will all be a big plus

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