89 Spacy Jobs - Page 4

Design, develop, and deploy machine learning models and algorithms using Python. Implement computer vision solutions for image and video analysis. Develop natural language processing (NLP) applications for text analysis and understanding. Utilize analytics workbench tools to create and manage data pipelines and workflows. Collaborate with data scientists, software engineers, and other stakeholders to understand project requirements and deliver effective solutions. Conduct research and stay updated with the latest advancements in AI and ML technologies. Ensure the scalability and performance of AI/ML solutions through rigorous testing and optimization. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proven experience as an AI/ML Engineer or similar role. Strong proficiency in Python and its libraries (e.g., TensorFlow, PyTorch, scikit-learn). Expertise in computer vision techniques and tools (e.g., OpenCV, YOLO, Mask R-CNN). c (e.g., NLTK, spaCy, Transformers). Familiarity with analytics workbench tools and data pipeline management. Excellent problem-solving skills and attention to detail. Strong communication and teamwork abilities. Preferred Qualifications: Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for deploying AI/ML solutions. Knowledge of big data technologies (e.g., Hadoop, Spark).

Python AIVirtusa is looking for AI engineers who have experience in the following:You should be a pro in PythonYou should have hands-on working knowledge of AI frameworks such asPyTorch/TensorFlow, Transformers, CV2, and HuggingFaceYou should have hands-on working knowledge training and prediction of NLPmodels such as Spacy, GliNER, and Reading Comprehension/ QA modelsYou should have hands-on working knowledge of common python/AI librariessuch as torch, numpy, nltk, pillow etc.Working knowledge of Computer Vision concepts and Vision and SentenceEncoder/Decoder models are a BIG plusYou should care about Performance, High availability and Scalabilityyou will get to work on building key elements of aKnowledge Analytics solution, includingThe state-of-the-art AI models encompassing Computer Vision, NaturalLanguage Processing, and Machine learning technologiesOntology-based domain modelingProcessing data with Knowledge GraphMicroservice based architecture Agile Software development Mandatory skills:PythonAI frameworksNLP

AI/ML Lead/ Architect: JD: Design, develop, and deploy machine learning models and algorithms using Python. Develop natural language processing (NLP) applications for text analysis and understanding. Utilize analytics workbench tools to create and manage data pipelines and workflows. Collaborate with data scientists, software engineers, and other stakeholders to understand project requirements and deliver effective solutions. Conduct research and stay updated with the latest advancements in AI and ML technologies. Ensure the scalability and performance of AI/ML solutions through rigorous testing and optimization. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proven experience as an AI/ML Engineer or similar role. Strong proficiency in Python and its libraries (e.g., TensorFlow, PyTorch, scikit-learn). Experience with NLP frameworks and libraries (e.g., NLTK, spaCy, Transformers). Familiarity with analytics workbench tools and data pipeline management. Excellent problem-solving skills and attention to detail. Strong communication and teamwork abilities. Preferred Qualifications: Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for deploying AI/ML solutions. Knowledge of Gen AI/ LLMs Preferrable. Certification in AI/ML or related technologies.

Design, develop, and deploy machine learning models and algorithms using Python. Implement computer vision solutions for image and video analysis. Develop natural language processing (NLP) applications for text analysis and understanding. Utilize analytics workbench tools to create and manage data pipelines and workflows. Collaborate with data scientists, software engineers, and other stakeholders to understand project requirements and deliver effective solutions. Conduct research and stay updated with the latest advancements in AI and ML technologies. Ensure the scalability and performance of AI/ML solutions through rigorous testing and optimization. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proven experience as an AI/ML Engineer or similar role. Strong proficiency in Python and its libraries (e.g., TensorFlow, PyTorch, scikit-learn). Expertise in computer vision techniques and tools (e.g., OpenCV, YOLO, Mask R-CNN). Experience with NLP frameworks and libraries (e.g., NLTK, spaCy, Transformers). Familiarity with analytics workbench tools and data pipeline management. Excellent problem-solving skills and attention to detail. Strong communication and teamwork abilities. Preferred Qualifications: Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for deploying AI/ML solutions. Knowledge of big data technologies (e.g., Hadoop, Spark). Certification in AI/ML or related technologies.

Position Overview: As an AI Engineer, you will be responsible for designing, developing, and implementing cutting edge artificial intelligence solutions to address complex problems for banking domain. You will collaborate with cross-functional teams to understand business requirements and leverage AI technologies to create innovative solutions. Job Description: Design and implement generative AI models, including GANs, VAEs, and transformers, as well as large language models such as GPT, BERT, LLAMA and similar to create high-quality synthetic data and other outputs. Use cutting edge technologies to create a faster, more capable AI. Preprocess and analyse large datasets to train and validate AI and LLM models. Analyse statistics, data, and algorithms for projection accuracy. Use AI analysis to make strategy recommendations that align with company goals. Work with a team of machine-learning and data engineers to ensure seamless AI development and integration. Collaborate with software engineers to integrate AI models into production systems, ensuring scalability, reliability, and performance. Stay current on AI knowledge, trends, regulations and proactively apply them to enhance existing solutions. Collect, organize, and present progress with team leadership and stakeholders. Maintain thorough documentation of models, experiments, and methodologies. Qualifications: Proven experience in developing and deploying machine learning models in real-world applications. Proficiency in programming languages such as Python, Java, or C++, with experience in libraries and frameworks for AI development. Strong understanding of machine learning algorithms, deep learning architectures, and optimization techniques. Hands on experience with GANs, VAEs, transformers and LLMs such as GPT, BERT, LLAMA and similar with experience on TensorFlow, PyTorch, Keras, or Apache MXNet. Familiarity with natural language processing libraries such as NLTK, spaCy, or Transformers. Experience in computer vision tasks using frameworks like OpenCV, TensorFlow Object Detection API, or PyTorch Vision. Familiarity with cloud platforms like AWS, GCP, or Azure. Excellent problem-solving skills and the ability to work effectively in a fast paced, collaborative environment. Effective communication skills with the ability to convey complex technical concepts to nontechnical stakeholders. Demonstrated ability to manage multiple projects simultaneously and deliver highquality results on time.

Role: Python Fullstack Software Engineer Exper: min 15 Years Salary: 24 LPA Candidate must have minimum 6+ years of experience in Python and 5+ years in ReactJS) Location: Chennai, Bangalore Qualifi: Any Regards, Allen 7200495207

Job Title: NLP Engineer Job Location: Chennai / Coimbatore Experience: 2+ years Job Type: Full-Time We are seeking an exceptional Senior NLP Engineer to join our cutting-edge AI/ML team. In this role, you will leverage your deep expertise in natural language processing, large language models, and retrieval-augmented generation to develop and optimize innovative NLP applications. Responsibilities: Design, develop, and deploy state-of-the-art NLP solutions utilizing LLMs and RAG architectures. Implement and optimize vector databases for efficient retrieval and augmentation of LLM-based systems. Collaborate with cross-functional teams to identify and address complex NLP challenges. Stay at the forefront of NLP research and apply latest techniques to enhance our AI/ML applications. Mentor junior engineers and contribute to the growth and knowledge sharing within the team. Requirements: Bachelor or Masters in Computer Science, NLP, ML or related field 2+ years of experience in developing NLP applications, (expertise in LLMs and RAG would be a plus) Strong understanding of transformer architectures, few-shot learning, and prompt engineering. Hands-on experience with NLP frameworks like Hugging Face, spaCy, NLTK, AllenNLP, etc. Proficiency in Python, PyTorch, TensorFlow and familiarity with C++/CUDA for optimization Experience with vector databases like Pinecone, Weaviate, Milvus for building RAG systems. Excellent problem-solving skills and ability to design efficient, scalable NLP pipelines. Strong communication skills and ability to collaborate in a fast-paced environment. Preferred Qualifications: Experience with deploying NLP models in production using AWS, GCP or Azure Knowledge of MLOps best practices and tools like MLflow, Kubeflow, AWS SageMaker If you are passionate about pushing the boundaries of NLP and developing game-changing AI applications, we would love to hear from you. Join our world-class team and help shape the future of intelligent systems.

Quality Engineering GenAI Platform Architect Job Profile Blend of domain expertise in Testing and Quality Engineering with experience and hands on with designing systems over Generative AI technologies for developing and operationalizing use cases across SDLC- STLC. In this role, the Architect will be responsible for formulating mechanisms to use, deploy Generative AI for multiple use case in Software Testing lifecycle. Formulate architecture patterns for building platform over Generative AI technologies that can automate- orchestrate activities for day in a life of tester. Create the designs for integrations with relevant Testing tools, DevOps pipelines for exchanging inputs and outputs from GenAI engines. Expertise in LLMs and specific libraries within LLMs with inputs ranging from text, images, media and processing them relevant business logic and produce specific outputs that align with the test flow, test tools in variety of formats- templates that is grounded to the specified context. Expertise with technology stacks like MEAN, MERN, LAMP and provide guidance, collaborate with development team of Front-end, back-end on building the platform. QE GenAi platform architect will be solely responsible and accountable for operationalizing GenAi for QE use cases with the easy to use wrapper platform for testers delivering in centralized, federated and agile ways of working. Experience in natural language processing (NLP), model optimization, Fine-tuning language models, Retrieval-Augmented Generation (RAG) techniques, context-aware generation to create comprehensive approach for use cases in testing and quality engineering leveraging the power of embeddings, groundings and vector databases. Key skills: Total experience of 7-11 years spanning across domain of Testing- Quality engineering (5+ years), Data science (2+ years) with recent technologies of Generative AI (1+ years) and Design- Architecting hands on (5+ years) Programming and Scripting:Proficiency in programming languages commonly used in AI and automation, such as Python, Java, or Ruby. Ability to write scripts for test automation and data generation. Machine Learning and AI:Understanding of generative models and their applications in testing. Knowledge of machine learning frameworks like TensorFlow or PyTorch. Data Management and Vector Database:Skills in data handling, preprocessing, and manipulation. Proficiency in managing vector databases embeddings, designing and optimizing indexing strategies, efficient retrieval. Testing and Quality Engineering:Strong background in software testing principles and methodologies. Experience in creating test plans, test cases, and executing manual and automated tests. Familiarity with various testing types, including functional, regression, performance, and security testing. Test Transformation Consulting:Awareness on understanding the current state and creating roadmap for testing transformation, typical challenges, ways of working, delivery constructs, centralized- federated models of test teams, tools & frameworks for test automation and adjacent areas, shift left, shift right Industry Domain Testing experience:Understanding of two or more industry or domain for which testing is being performed. Like Banking, Retail, Telecom, Health, Insurance,. Awareness of specific quality and compliance standards relevant to the domain. Natural Language Processing (NLP):Understanding of NLP concepts and techniques, such as tokenization, part-of-speech tagging, named entity recognition, and sentiment analysis. Familiarity with NLP libraries and frameworks, such as NLTK, spaCy, or Hugging Face Transformers. Industry LLMs:experience in working with atleast two:ChatGPT, Azure OpenAI, VertexAi, Plam, Llama, Falcon, Hugging face, Sagemaker, " Model Architecture Understanding:In-depth understanding of the generic architecture of LLMs and how it processes and generates language. Fine-Tuning RAG Models using pre-trained embeddings:Skills in fine-tuning RAG models on specific datasets or domains to improve performance for testing and quality engineering tasks Contextual Grounding:Ability to ground entities in context, considering the dynamic nature of information and the evolving context. Ethical and Security, Data Privacy Considerations:Awareness of ethical considerations in AI, including bias mitigation and responsible AI practices and data privacy, security elements Industry skills: Pipeline Integration:Proficiency in integrating into existing testing and quality engineering pipelines. Problem-Solving and Analytical Skills:Ability to analyze complex systems and identify areas for improvement in testing processes. Strong problem-solving skills to address issues related to test automation and generative AI. Communication Skills:Effective communication to collaborate with cross-functional teams, including developers, QA engineers, and business stakeholders. Ability to communicate complex technical concepts to non-technical audiences. Continuous Learning:A mindset of continuous learning to stay updated on the latest advancements in AI, testing methodologies, and industry trends. Collaboration, Teamwork, Documentation, version control:Ability to work collaboratively in a team environment and contribute to a positive and productive work culture. Strong documentation skills for creating and maintaining assets and all documentation. Proficiency in using version control systems (e.g., Git) for tracking changes and managing different versions. Quality Engineering GenAI Consultant Job Profile Blend of domain expertise in Testing and Quality Engineering with experience and hands on with Generative AI technologies as well coding for automation with the key objective of developing and operationalizing use cases across SDLC- STLC. In this role, the Consultant will be responsible for mapping the STLC, activities- dependencies within STLC, identifying opportunities to brig GenAi in the loop, breaking down the problems into granular chunks, formulating outputs and reverse engineering inputs and analysis mechanisms with GenAI to augment, enhance, automate and orchestrate relevant activities for day in a life of tester and/or in Software Testing lifecycle. Prioritize the use cases for piloting groom the use cases in the client context, with technology and ways of working within the landscape and exploring use of Generative AI technologies that client has subscribed for. Formulate designs for integrations with relevant Testing tools, DevOps pipelines for exchanging inputs and outputs from GenAI engines. Expertise in LLMs and specific libraries within LLMs with inputs ranging from text, images, media and formulating the business logic, process flow and produce specific outputs that align with the test flow, test tools in variety of formats- templates that is grounded to the specified context. QE GenAi consultant will be solely responsible and accountable for identifying- enabling and operationalizing use cases with GenAi for testers with well defined inputs- outcomes and business logic for testers delivering across centralized, federated and agile ways of working. Experience in multiple LLMs and their libraries, Embeddings, Retrieval-Augmented Generation (RAG) techniques, context-aware grounded generation to create comprehensive approach for addressing use cases in testing and quality engineering. Key skills: Total experience of 7-11 years spanning across domain of Testing- Quality engineering (5+ years), Test automation- Java- selenium- python (2+ years) with recent technologies of Generative AI (1+ years) and hands on role of Test lead (5+ years) across variety of testing programs and industry domains. Programming and Scripting:Proficiency in programming languages used for Test automation, Test Automation Framework creation. Ability to write scripts for test automation and data generation and handling test dependencies like mocking. Data Management and Vector Database:Skills in data handling, preprocessing, and manipulation. Proficiency in managing vector databases embeddings, designing and optimizing indexing strategies, efficient retrieval. Testing and Quality Engineering:Strong background in software testing principles and methodologies. Experience in creating test plans, test cases, and executing manual and automated tests. Familiarity with various testing types, including functional, regression, performance, and security testing. Having handled complex test programs, integrations with CICD- DevOps pipelines" Test Transformation Consulting:Awareness on understanding the current state and creating roadmap for testing transformation, typical challenges, ways of working, delivery constructs, centralized- federated models of test teams, tools & frameworks for test automation and adjacent areas, shift left, shift right Industry Domain Testing experience:Understanding of two or more industry or domain for which testing is being performed. Like Banking, Retail, Telecom, Health, Insurance,. Awareness of specific quality and compliance standards relevant to the domain. Industry LLMs:experience in working with two or more open source / licensed:ChatGPT, Azure OpenAI, VertexAi, Plam, Llama, Falcon, Hugging face, Sagemaker, " Basic understanding of Model Architecture and how it processes and generates content. Retrieval augmented generation- RAG:Extensive experience if using RAG models on specific datasets or domains to improve and reference outcomes for testing and quality engineering tasks Contextual Grounding:Ability to ground entities in context, considering the dynamic nature of information and the evolving context. Ethical and Security, Data Privacy Considerations:Awareness of ethical considerations in AI, including bias mitigation and responsible AI practices and data privacy, security elements Industry skills: Pipeline Integration:Proficiency in integrating into existing testing and quality engineering pipelines. Problem-Solving and Analytical Skills:Ability to analyze complex systems and identify areas for improvement in testing processes. Strong problem-solving skills to address issues related to test automation and generative AI. Communication Skills:Effective communication to collaborate with cross-functional teams, including developers, QA engineers, and business stakeholders. Ability to communicate complex technical concepts to non-technical audiences. Continuous Learning:A mindset of continuous learning to stay updated on the latest advancements in AI, testing methodologies, and industry trends. Collaboration, Teamwork, Documentation, version control:Ability to work collaboratively in a team environment and contribute to a positive and productive work culture. Strong documentation skills for creating and maintaining assets and all documentation.

Introduction We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA- as the world around us changes, so do we. Wipro empowers companies to transform their business and deliver superior experiences for their customers, partners and employees. With an entrepreneurial mindset and a sense of fun, we thoughtfully evaluate clients problems; craft innovative solutions that leverage cutting-edge technologies; and work side-by-side with clients to drive business outcomes. Enterprise Futuring is the largest global business line across Wipro, they offer our clients forward-looking solutions for large-scale enterprise transformation. They offer intelligent insights, enterprise data, application platforms, digital operations, and cybersecurity risk services. At Enterprise Futuring, the AI practice has deep industry knowledge, incredible passion, and strong customer relationships. Wipro stands firm as a leading partner in AI service innovation, creating impactful realizations of business potential. Through the development of robust, personalized solutions enhanced by the innovative power of AI technology, Wipro is committed to building transformative journeys for clients. Roles & Responsibilities Day-to-day technical responsibilities Design solutions and implement generative AI models and algorithms, utilizing state-of-the-art algorithms such as GPT, VAE, and GANs. Work on integrating cloud with GenAI algorithms like ChatGPT, Bedrock, Bard, PaLM etc. Collaborate with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals. Research the latest advancements in generative AI, machine learning, and deep learning techniques, and identify opportunities to integrate them into our products and services. Optimize existing generative AI models for improved performance, scalability, and efficiency. Develop and maintain AI pipelines, including data pre-processing, feature extraction, model training, and evaluation. Drive the team to build GenAI products and solutions, working in an agile methodology Stakeholder Interaction & Management Work with internal teams and get relevant data/inputs for preparing documents such as RFP responses, capability demonstrations, client presentations and collaterals, participating in the customer calls to sell solutions etc. Collaborate with relevant stakeholders/teams to get feedback and make revisions to ensure that the proposal stays relevant to the needs throughout various proposal stages. Ensures communication among all parties throughout the proposal process Identifies bottlenecks in the process escalating accordingly to higher level, as necessary, to ensure timetable and deliverables remain on track Reach out to the below mentioned internal teams during proposal creation. Effective Project Management Effectively and efficiently plan, organize, lead and control the delivery of the final solution/proposal/document Prepare a work plan that lists the tasks required to create the proposal, such as design, writing, editing, review and production Uses strong interpersonal, organizational, and time management skills to juggle multiple tasks with differing deadlines to consistently produce the document Collaborate and influence internal key stakeholders to get relevant data within the specified timeline to ensure relevant data in plugged into the solution Ensure promptness and compliance of proposals by creating and managing proposal calendars, compliance checklists, compliance matrices, trackers, etc. Oversees collection and completion of all proposal components (technical, cost, management, annexes) working in collaboration with internal teams, as well as partners. Follow up with relevant stakeholders/teams to get feedback and revisions and ensure that the proposal development stays on schedule. Update the sales team and other stakeholders on a regular basis on the progress of the proposal Tech skills you will have You have solid experience over the last few years developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs. You are proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras. Familiarity with cloud-based platforms and services, such as AWS, GCP, or Azure. Prompt engineering for GenAI algorithms Experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face. Deployment of GenAI models Scrum/ Agile Why work at Wipro We pride ourselves on creating an inclusive workplace that provides equal opportunities to all persons regardless of their age, cultural background, sexual orientation, gender identity and expression, disability, veteran status, or anything else. If you only meet some of the requirements for this role, that's okay! We value a diverse range of backgrounds & ideas and believe this is fundamental for our future success. So, if you have the curiosity to learn and the willingness to teach what you know, we'd love to hear from you. Wipro has been globally recognized by several organizations for our commitment to sustainability, inclusion, and diversity. Social good is in our DNA, we believe in sustainability for the health of our planet, its inhabitants, and our business. For over 75 years we have operated as a purpose-driven company with an unwavering commitment to our customers and our communities. Energized by what we call the Spirit of Wipro, we commit ourselves to being a catalyst for change- working to build a more just, equitable and sustainable society. Around 66% of Wipros economic ownership is pledged towards philanthropic purposes. All of our employees are expected to embody Wipros 5-Habits for Success which are:Being Respectful, Being Responsive, Always Communicating, Demonstrate Stewardship, Building Trust.

Role: Lead ML Developer (NLP) Job Summary: This job requires candidate to lead the design and development work with Large Language model and application of Large Language models for different use cases. As an expert in using Generative AI, particularly LLM models, and proficient in Python programming, he/she will be responsible for developing and deploying a system that can convert natural language queries to handle the use cases like building SQL query statements for searching tables in DB or searching the documents for Q&A. This role requires a deep understanding of natural language processing (NLP) techniques, database management systems, SQL Query optimization, and passion for building intelligent systems. Responsibilities: Develop and implement a robust system for converting natural language queries with help of prompt engineering into useful format, which can be further programmatically used for search a set of SQL tables or set of documents. Development and application of word embedding techniques (Woprd2vec, Transformer model based encoders, LLM based encoder, BERT based encoders etc) Fine Tuning of Large Language Models with custom data sets. Utilize Generative AI techniques, leveraging Large Language models, to accurately interpret and convert natural language queries into SQL statements. Use of LLMs for the NLP state of art techniques like Text Classification, NER, Keyword Extraction, Text-to-SQL conversion. Check the feasibility of use cases based on Large Language Models, specifically in area chatbot for sales and finance problems. Develop mechanism to summarize SQL tables into user-level summary text, providing concise and meaningful insights from the data retrieved. Design and build scalable architecture that can handle a large volume of queries efficiently, ensuring high performance and minimal latency. Collaborate with cross-functional teams, including data scientists, software engineers, and database administrators, to understand requirements and integrate the solution into existing systems. Conduct thorough research and stay up to date with the latest advancements in NLP, machine learning, and Generative AI to continuously improve the systems accuracy and efficiency. Optimize and fine-tune SQL queries to ensure efficient data retrieval, taking into account query execution plans, indexes, and query performance optimization techniques. Develop testing frameworks and conduct rigorous testing to validate the systems accuracy, reliability, and scalability. Document the system architecture, design decisions, and codebase to facilitate future maintenance and enhancements. Skills MUST Strong experience in architecting and development of ML, NLP based projects is a must. Strong track record of ML led solution development from scratch. Strong proficiency in Python Programming (very strong Python credentials only apply) and experience with relevant libraries and frameworks for NLP such as NLTK, spaCy, Hugging Face transformers. In-depth knowledge and experience in using Generative AI techniques for NLP tasks, preferable with Large Language models (e.g., GPT-3, GPT-4), GCP PALM models (code bison, text bison) or Hugging Face models. Good exposure to word embedding techniques. (BERT, Word2Vec, LLM based encoders etc.) Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and deep learning architectures. Hands on experience with Langchain framework. Solid understanding of SQL and experience working with popular relational database management systems. Proficiency in writing both simple standard SQL queries and complex joining queries to fetch data from a database. Experience with query optimization techniques and understanding of indexes, execution plans, and performance tuning. Familiarity with cloud-based data warehousing platforms. Strong problem-solving skills and ability to translate business requirements into technical solutions. Excellent communication skills to collaborate effectively with multidisciplinary teams. Ability to work independently, manage priorities, and deliver high-quality results within project timelines. Strong attention to detail and a commitment to producing clean, well-documented code.

9+ years experience in designing, developing and deploying production-grade machine learning solutions (supervised, unsupervised, reinforcement learning), deep learning framework (e.g. TensorFlow, PyTorch, Keras, etc) and NLP (NLTK, Spark NLP, spaCy, HuggingFace, Flair, NLTK, etc) for real-world business problems Experience with Open Source LLM and Langchain Framework Expertise in Python and SQL, with working experience in Apache Spark, Hadoop, Databricks, Snowflake, or other big data systems Development and ML experience in cloud platforms such as Microsoft Azure Combination of deep technical skills and business sense, to interface with all levels and disciplines within an organization. Excellent written and verbal communication skills to explain complex research to both technical and non-technical audiences Self-motivated individual that thrives in a dynamic environment

Responsibilities Software Developers at IBM are the backbone of our strategic initiatives to design, code, test, and provide industry-leading solutions that make the world run today – planes and trains take off on time, bank transactions complete in the blink of an eye and the world remains safe because of the work our software developers do. Are you interested in working in one of the most impactful areas of technology in the world today? Do you want to build generative AI skills while working on a project to transform the most mission-critical IT workloads for organizations that power the global economy? Come join the team that is at the intersection of cutting-edge AI and mainframe software development, a key strategic pillar for IBM. As a Backend Developer, you will be responsible for the technical approach and implementation of new and existing applications within your workstream. You are a software engineer who is comfortable leading agile development teams in a hands-on way, providing guidance regarding best practices and working in cooperation with your team’s leadership, Scrum Master, designer, and other engineers. You make informed decisions with input from informed parties at all levels of the organization to quickly deliver valuable working software. You are comfortable providing mentoring guidance to less-experienced team members and collaborating with other senior members of your team. You have a passion for high-quality, reliable, and maintainable code. You have a product mindset, and are agile and retrospective, and not afraid to identify what we are doing wrong so we can fix it, and what we are doing right so we can improve upon it. You will work with multidisciplinary teams to define requirements and develop solutions. You will design, code, and test solutions for modernization of the IBM Z platform, that use programming languages including Python, Java, Golang and leverage technologies and platforms like Ansible, Kubernetes, Docker. Comfortable with multi-tasking and working as part of a global team, as well as providing technical leadership and taking ownership. Adaptive to ambiguity and willing to change in a fast-paced environment Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise 10 – 12 years of software development experience Expertise in translating product requirements into technical requirements, preparing HLD/LLD, working closely with team members to translate the requirements into product work items. 5+ years of experience in leading product development teams on AI applications written in Python, Ansible; knowing Golang is a plus. Hands-on experience with AI/ML libraries such as TensorFlow, PyTorch, Scikit-Learn, and NLP libraries such as SpaCy, NLTK, or Hugging Face Transformers Solid understanding of ML algorithms such as supervised learning, unsupervised learning, reinforcement learning and deep learning Proficient in NLP techniques for understanding and processingcode, documentation, and user input. Skills in data collection, cleaning, processing, and analysis to build and train AI models Exposure working with the following:Kubernetes, Docker, etc. Exposure to DevOps concepts, CI/CD tools and setting up CI/CD pipelines. Preferred technical and professional experience Familiarity or exposure to IBM Z Architecture, IBM z/OS Systems Programming, Application development on IBM z/OS. Solid understanding of ML algorithms such as supervised learning, unsupervised learning, reinforcement learning and deep learning Hands-on experience working with Java, Golang, Ansible, Kubernetes, Docker Proficient in source control management tools (Tekton, Jenkins) and with Agile Life Cycle

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 : NA Minimum 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 (example:AWS, 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. Qualifications 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 : NA Minimum 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 (example:AWS, 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. Qualifications 15 years full time education