179 Bert Jobs - Page 2

As an Agentic Thinker and visionary Generative AI Subject Matter Expert (SME) at UBS in Hyderabad, you will lead the design, development, and deployment of cutting-edge generative AI solutions to solve complex business challenges. UBS emphasizes innovation and agility to enhance responsiveness, adaptability, and overall innovation in the workplace. In this role, you will leverage large language models (LLMs), diffusion models, and other generative architectures to drive innovation and act as a technical authority for generative AI. Your responsibilities will include architecting, training, and fine-tuning generative AI models for various applications such as content generation, conversational AI, code automation, and data synthesis. Additionally, you will lead research and development initiatives to enhance model performance, efficiency, and alignment with business objectives. You will collaborate with product, engineering, and business teams to integrate generative AI into workflows and translate business requirements into technical specifications for generative AI use cases. Moreover, you will optimize generative models for latency, cost, and scalability, deploy models on cloud platforms and edge devices, and implement safeguards to mitigate risks such as bias and misinformation while ensuring compliance with data privacy regulations and ethical AI guidelines. As part of the Mainframe & Midrange Stream team in India, you will work on Mainframe and Midrange Gen AI Journey, aligning with UBS AI elements and the Emerging Technology and Modernization Team. Your expertise should include a master's or PhD in Computer Science, Machine Learning, or a related field, along with at least 5 years of experience in AI/ML development with a focus on generative AI. You should have a proven track record of deploying generative AI solutions in production environments, deep expertise in generative architectures such as GPT and Transformers, proficiency in Python, PyTorch/TensorFlow, and cloud platforms, as well as experience with NLP tools and vector databases. Preferred skills include knowledge of multimodal AI, reinforcement learning, and familiarity with AI ethics frameworks. UBS, as the world's largest and truly global wealth manager, operates through four business divisions and has a presence in over 50 countries. If you are passionate about driving innovation, solving complex business challenges with generative AI, and being part of a diverse and inclusive culture that values collaboration and empowerment, UBS is the place for you. Join us to grow, learn, and make a difference in a supportive and inclusive environment.,

Seeking a Senior AI Engineer with strong expertise in machine learning, deep learning, and model deployment to design and implement scalable AI solutions for complex business problems.

As a high-impact AI/ML Engineer, you will lead the design, development, and deployment of machine learning and AI solutions across vision, audio, and language modalities. You will be an integral part of a fast-paced, outcome-oriented AI & Analytics team, collaborating with data scientists, engineers, and product leaders to translate business use cases into real-time, scalable AI systems. Your responsibilities in this role will include architecting, developing, and deploying ML models for multimodal problems encompassing vision, audio, and NLP tasks. You will be responsible for the complete ML lifecycle, from data ingestion to model development, experimentation, evaluation, deployment, and monitoring. Leveraging transfer learning and self-supervised approaches where appropriate, you will design and implement scalable training pipelines and inference APIs using frameworks like PyTorch or TensorFlow. Collaborating with MLOps, data engineering, and DevOps teams, you will operationalize models using technologies such as Docker, Kubernetes, or serverless infrastructure. Continuously monitoring model performance and implementing retraining workflows to ensure sustained accuracy over time will be a key aspect of your role. You will stay informed about cutting-edge AI research and incorporate innovations such as generative AI, video understanding, and audio embeddings into production systems. Writing clean, well-documented, and reusable code to support agile experimentation and long-term platform development is an essential part of this position. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field, with a minimum of 5-8 years of experience in AI/ML Engineering, including at least 3 years in applied deep learning. In terms of technical skills, you should be proficient in Python, with knowledge of R or Java being a plus. Additionally, you should have expertise in ML/DL Frameworks like PyTorch, TensorFlow, and Scikit-learn, as well as experience in Computer Vision tasks such as image classification, object detection, OCR, segmentation, and tracking. Familiarity with Audio AI tasks like speech recognition, sound classification, and audio embedding models is also desirable. Strong capabilities in Data Engineering using tools like Pandas, NumPy, SQL, and preprocessing pipelines for structured and unstructured data are required. Knowledge of NLP/LLMs, Cloud & MLOps services, deployment & infrastructure technologies, and CI/CD & Version Control tools are also beneficial. Soft skills and competencies that will be valuable in this role include strong analytical and systems thinking, effective communication skills to convey models and results to non-technical stakeholders, the ability to work cross-functionally with various teams, and a demonstrated bias for action, rapid experimentation, and iterative delivery of impact.,

As a Senior AI Engineer (Tech Lead) at EY, you will have the opportunity to leverage your technical expertise to develop and implement cutting-edge AI solutions. With a minimum of 4 years of experience in Data Science and Machine Learning, including NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture, you will play a crucial role in driving innovation and creating impactful solutions for enterprise industry use cases. Your responsibilities will include contributing to the design and implementation of state-of-the-art AI solutions, leading a team of 4-6 developers, and collaborating with stakeholders to identify business opportunities and define AI project goals. You will stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. By utilizing generative AI techniques, such as LLMs and Agentic Framework, you will develop innovative solutions tailored to specific business requirements. Your role will also involve integrating with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to enhance generative AI capabilities. Additionally, you will be responsible for implementing and optimizing end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Your expertise in data engineering, DevOps, and MLOps practices will be valuable in curating, cleaning, and preprocessing large-scale datasets for generative AI applications. To excel in this role, you should hold a Bachelor's or Master's degree in Computer Science, Engineering, or a related field, and demonstrate proficiency in Python, Data Science, Machine Learning, OCR, and document intelligence. Strong collaboration with software engineering and operations teams, along with excellent problem-solving and analytical skills, will be essential in translating business requirements into technical solutions. Moreover, your familiarity with trusted AI practices, data privacy, security, and ethical considerations will ensure the fairness, transparency, and accountability of AI models and systems. Additionally, having a solid understanding of NLP techniques, frameworks like TensorFlow or PyTorch, and cloud platforms such as Azure, AWS, or GCP will be beneficial in deploying AI solutions in a cloud environment. Proficiency in designing or interacting with agent-based AI architectures, implementing optimization tools and techniques, and driving DevOps and MLOps practices will also be advantageous in enhancing the performance and efficiency of AI models. Join EY to build an exceptional experience for yourself and contribute to creating a better working world for all through the power of AI and technology.,

Your Key Responsibilities Would Include: Summary: The SW QA Engineer functions as part of the Regional Escalation Support (RES) Team within the Technical Assistance Center (TAC) organization. Within this role, the SW QA Engineer performs advanced level fault isolation and troubleshooting of assigned Customer issues. The SW QA Engineer operates cross-functionally with Infinera SW / HW Engineering, Product Line Management (PLM), Global Technical Support (GTS) Teams to effectively and efficiently resolve issues affecting the Customers networks. Manages assigned escalation support requests with a view towards driving increased Customer satisfaction, analyzing and providing software solutions through product enhancement, defect resolution, documentation, and creation of custom solutions. Responsibilities : Investigate and troubleshoot customer issues in both Production and Lab environments Provide root cause analysis and suggestions for corrective actions Produce and deliver Customer facing documents that explain technically complex issues Produce and deliver post-mortem actions to resolve issues in Customer networks Responsible for understanding the technical aspects of the supported product releases and diagnostic logs to provide expert advice concerning any issues that may arise Contribute to the development of Knowledge Base content Review new release of technical documents for accuracy and completeness Test and validate customized scripts prior to release Develop and support sustaining Technical Notes and Field Service Bulletins to be utilized by both internal and external operators Knowledge, Skills, and Abilities Prior experience with long haul or metro optical networks required Practical knowledge of Ethernet, SONET/SDH, DWDM and OTN Experience with optical test sets and solid optical troubleshooting skills using OTDR, OSA, BERT, optical power meters etc. Hands-on testing experience with ROADM, EDFA, Raman Amplifiers and Coherent Transponders Knowledge in TCP/IP networking, L2/L3 routing and switching is a plus Prior system test, scripting and/or new product introduction experience required Extensive experience with traffic generators and network protocols analysis tools Strong problem-solving skills, applicable to large and complex network scenarios Experience with creating Power Point presentations and Excel Highly detail-oriented, excellent analytical and troubleshooting skills Candidate must possess excellent inter-personal, oral and written communication skills

Key Responsibilities: Build, train, and validate machine learning models for prediction, classification, and clustering to support NBA use cases. Conduct exploratory data analysis (EDA) on both structured and unstructured data to extract actionable insights and identify behavioral drivers. Design and deploy A/B testing frameworks and build pipelines for model evaluation and continuous monitoring. Develop vectorization and embedding pipelines using models like Word2Vec, BERT, to enable semantic understanding and similarity search. Implement Retrieval-Augmented Generation (RAG) workflows to enrich recommendations by integrating internal and external knowledge bases. Collaborate with cross-functional teams (engineering, product, marketing) to deliver data-driven Next Best Action strategies. Present findings and recommendations clearly to technical and non-technical stakeholders. Required Skills & Experience: Strong programming skills in Python, including libraries like pandas, NumPy, and scikit-learn. Practical experience with text vectorization and embedding generation (Word2Vec, BERT, SBERT, etc.). Proficiency in Prompt Engineering and hands-on experience in building RAG pipelines using LangChain, Haystack, or custom frameworks. Familiarity with vector databases (e.g., PostgreSQL with pgvector, FAISS, Pinecone, Weaviate). Expertise in Natural Language Processing (NLP) tasks such as NER, text classification, and topic modeling. Sound understanding of supervised learning, recommendation systems, and classification algorithms. Exposure to cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes) is a plus.

Role & responsibilities Design, prototype, and deploy AI-driven applications leveraging LLMs (GPT-4, Perplexity, Claude, Gemini, etc.) and open-source transformer models. Lead or co-lead end-to-end AI/GenAI solutions : from data ingestion, entity extraction, and semantic search to user-facing interfaces. Implement RAG (Retrieval-Augmented Generation) architectures, knowledge grounding pipelines, and prompt orchestration logic. Fine-tune transformer models (BERT, RoBERTa, T5, LLaMA) on custom datasets for use cases like: Document understanding Conversational AI Question answering Summarization & Topic Modeling Integrate LLM workflows into scalable backend architectures with APIs and frontends. Work closely with business teams and pharma SMEs to translate requirements into GenAI solutions . Mentor junior engineers and contribute to AI capability development across the organization. Tech Stack & Skills Required Programming & Libraries : Python, FastAPI, LangChain, Pandas, PyTorch/TensorFlow, Transformers (HuggingFace), OpenAI SDK. Data Extraction & Processing : PDFMiner, PyMuPDF, Tabula, PyPDF2, Tesseract OCR, python-pptx. Gen AI / LLMs : OpenAI (GPT), Gemini, Perplexity, Cohere, DeepSeek, Mistral, LLaMA, BERT, RoBERTa, T5, Falcon. Use Cases : NER, Summarization, QA, Document Parsing, Clustering, Topic Modeling, QA over docs. Embedding & Vector Databases : Pinecone, FAISS, ChromaDB. RAG & Retrieval Pipelines : LangChain, Haystack, custom retrievers. Frontend/Backend Integration : React (preferred), FastAPI/Flask, REST/GraphQL APIs. Versioning & Deployment : Git, Docker, CI/CD (basic), cloud knowledge is a plus (AWS/GCP/Azure). Preferred candidate profile Degree in Computer Science, Engineering, Data Science, or related field (BE/BTech/MTech/MCA). 35 years of hands-on experience in AI/ML/NLP/LLM solution development. Strong understanding of GenAI, Prompt Engineering, LLM internals , and multi-layered data architectures. Exposure to pharma/healthcare domain is a significant plus. Excellent problem-solving skills, self-learner, and ability to work in cross-functonal teams. Experience developing new applications within an agile environment preferred. Ability to work independently and as part of a team. Exposure to MLOPs will be an added advantage.

Amplework Software is a full-stack development agency based in Jaipur (Rajasthan), IND, specializing in end-to-end software development solutions for clients worldwide. We are dedicated to delivering high-quality products that align with business requirements and leverage cutting-edge technologies. Our expertise encompasses custom software development, mobile applications, AI-driven solutions, and enterprise applications. Join our innovative team that drives digital transformation through technology. We are looking for a Mid-Level Python and AI Engineer to join our team. In this role, you will assist in building and training machine learning models using frameworks such as TensorFlow, PyTorch, and Scikit-Learn. You will experiment with pre-trained AI models for NLP, Computer Vision, and Predictive Analytics. Additionally, you will work with structured and unstructured data, collaborate with data scientists and software engineers, and continuously learn, experiment, and optimize models to enhance performance and efficiency. Ideal candidates should possess a Bachelor's degree in Computer Science, Engineering, AI, or a related field and proficiency in Python with experience in writing optimized and clean code. Strong problem-solving skills, understanding of machine learning concepts, and experience with data processing libraries are required. Familiarity with AI models and neural networks using frameworks like Scikit-Learn, TensorFlow, or PyTorch is essential. Preferred qualifications include experience with NLP using transformers, BERT, GPT, or OpenAI APIs, AI model deployment, database querying, and participation in AI-related competitions or projects. Soft skills such as analytical thinking, teamwork, eagerness to learn, and excellent English communication skills are highly valued. Candidates who excel in problem-solving, possess a willingness to adapt and experiment, and prefer a dynamic environment for AI exploration are encouraged to apply. A face-to-face interview will be conducted, and applicants should be able to attend the interview at our office location. Join the Amplework Software team to collaborate with passionate individuals, work on cutting-edge projects, make a real impact, enjoy competitive benefits, and thrive in a great working environment.,

Join us as a Machine Learning/Artificial Intelligence Engineer, responsible for supporting the successful delivery of Location Strategy projects to plan, budget, agreed quality and governance standards. You'll spearhead the evolution of our digital landscape, driving innovation and excellence. You will harness cutting-edge technology to revolutionise our digital offerings, ensuring unparalleled customer experiences. To be successful as a Machine Learning/Artificial Intelligence Engineer, you should have experience with: - Good years of experience in IT with a background in Development, Machine Learning, and/or Data analysis. - Hands-on experience of NLP/AI/ML tools & technologies GPT, BERT, or other language models. - Experience in building GenAI applications, RAG-based architectures. - Model Development: Research, design, implement, and optimize machine learning models for specific use cases such as predictive analytics, NLP, computer vision, and recommender systems. - Data Preparation: Collect, preprocess, and analyze large datasets to extract meaningful insights and ensure data quality for model training. - Deployment: Build and deploy AI/ML solutions into production environments using appropriate tools and frameworks. - Knowledge of one of the cloud platforms is a must: AWS/AZURE. - Collaboration: Work closely with product managers, data engineers, and software developers to integrate AI capabilities into products and ensure alignment with business objectives. - Performance Monitoring: Evaluate and monitor model performance and accuracy post-deployment, iterating to address challenges and refine models as needed. - Strong Affinity to stay informed on the latest trends, tools, and research in AI and machine learning space. - Support and contribute to data collection efforts, as needed. - Verify data quality to ensure accurate analysis and reporting. - Help identify the business data needed to produce the most useful insights and future analytics. - Utilize data to make actionable recommendations at all levels. - Monitor data management processes to ensure data quality and consistency. - Monitor system performance, data integrity, and usage metrics. - Contribute to data dictionary, standards, training, and ongoing updates. Some other highly valued skills may include: - Web service development experience using REST services/APIs, JSON, XML, IVRs, Jenkins, other Cloud Platforms. - Experience in setting up DevOps pipelines. You may be assessed on the key critical skills relevant for success in the role, such as risk and controls, change and transformation, business acumen, strategic thinking, and digital and technology, as well as job-specific technical skills. This role is based in Pune. Purpose of the role: To design, develop, and improve software, utilizing various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues. Accountabilities: - Development and delivery of high-quality software solutions by using industry-aligned programming languages, frameworks, and tools. Ensuring that code is scalable, maintainable, and optimized for performance. - Cross-functional collaboration with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration and alignment with business objectives. - Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing. - Stay informed of industry technology trends and innovations and actively contribute to the organization's technology communities to foster a culture of technical excellence and growth. - Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions. - Implementation of effective unit testing practices to ensure proper code design, readability, and reliability. Assistant Vice President Expectations: - To advise and influence decision-making, contribute to policy development, and take responsibility for operational effectiveness. Collaborate closely with other functions/business divisions. - Lead a team performing complex tasks, using well-developed professional knowledge and skills to deliver work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives, and determination of reward outcomes. - If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviors to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviors are: L Listen and be authentic, E Energize and inspire, A Align across the enterprise, D Develop others. - OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialization to complete assignments. They will identify new directions for assignments and/or projects, identifying a combination of cross-functional methodologies or practices to meet required outcomes. - Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues. - Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda. - Take ownership of managing risk and strengthening controls in relation to the work done. - Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organization sub-function. - Collaborate with other areas of work, for business-aligned support areas to keep up to speed with business activity and the business strategy. - Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practices (in other areas, teams, companies, etc.) to solve problems creatively and effectively. - Communicate complex information. "Complex" information could include sensitive information or information that is difficult to communicate because of its content or its audience. - Influence or convince stakeholders to achieve outcomes. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset to Empower, Challenge, and Drive the operating manual for how we behave.,

As a Digital Product Engineering company, Nagarro is currently seeking a professional with over 5 years of experience in the field to join our team. The ideal candidate should possess a deep understanding of Generative AI fundamentals and transformer-based architectures along with a strong experience in Cloud Architecture for deploying scalable AI systems using platforms such as AWS, Azure, or GCP. The successful candidate will have hands-on experience working with Generative AI models, particularly in Azure AI, and should be familiar with BERT, GPT, LLaMA, and similar LLMs. Proficiency in prompt engineering, RAG techniques, and fine-tuning and deploying models using frameworks like Hugging Face Transformers or LangChain is also required. Additionally, experience with multi-agent AI systems, collaborative model workflows, Python, machine learning libraries (e.g., PyTorch, TensorFlow), and integrating models into enterprise platforms and APIs is essential. Responsibilities for this role include understanding clients" business use cases and technical requirements, translating them into technical designs, mapping decisions with requirements, identifying and narrowing down solutions that best meet client requirements, defining guidelines and benchmarks for NFR considerations, writing and reviewing design documents, reviewing architecture and design for various aspects, developing and designing solutions for defined requirements, and resolving issues raised during code reviews through systematic analysis. Qualifications for this position include a Bachelor's or Master's degree in Computer Science, Information Technology, or a related field. If you are passionate about AI, NLP, and Knowledge Engineering and possess the required skills and experience, we invite you to join our dynamic and non-hierarchical work culture at Nagarro.,

Dear Candidate, Greetings from Genworx.ai About Us Genworx.ai is a pioneering startup at the forefront of generative AI innovation, dedicated to transforming how enterprises harness artificial intelligence. We specialize in developing sophisticated AI agents and platforms that bridge the gap between cutting-edge AI technology and practical business applications. We have an opening for Full Stack Developer (Generative AI) position at Genworx.ai . please find below detailed Job Description for your understanding. Required Skills and Qualifications: Job Title: Full Stack Developer (Generative AI) Experience: 4+ years with atleast 5+ years in cloud automation Education: Bachelors or Masters degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field Work Location: Chennai Job Type: Full-Time Website: https://genworx.ai/ Key Responsibilities: 1. Problem Solving and Design: Analyse and address complex challenges in generative AI and application development. Debug and troubleshoot application and AI workflow issues for optimal performance Propose and implement scalable, efficient solutions tailored to real-world use cases. 2. Software Development and Integration: Coding: Design, Develop, test, and maintain front-end and back-end components for generative AI applications. Integration: Implement and manage APIs to integrate AI models into web and mobile platforms. Debugging: Debug and resolve application issues, ensuring smooth operation and integration. Build and maintain CI/CD pipelines for seamless deployment of AI-driven applications. Implement DevOps best practices to ensure efficient and secure operations. 3. Generative AI Development: Collaborate with machine learning teams to integrate pre-trained AI models into scalable applications. Work with state-of-the-art models, including large language models (LLMs), image generators, and more. Integrate pre-trained models, including large language models (LLMs). Optimize AI solutions for performance, scalability, and reliability. Experiment with new generative AI frameworks and technologies to enhance application capabilities. 4. Operational Excellence: Maintain high standards of performance, security, and scalability in design and implementation. Monitor and troubleshoot system performance to ensure reliability. Document technical workflows and ensure team adherence to operational guidelines. 5. Team Collaboration and Mentorship: Work closely with cross-functional teams, including product managers, ML engineers, and designers, to deliver high-quality solutions. Mentor junior engineers, fostering a collaborative and learning-oriented environment. Participate in code reviews, brainstorming sessions, and team discussions. 6. Continuous Learning and Innovation: Stay updated on the latest trends in generative AI, cloud platforms, and full-stack development. Experiment with emerging tools and frameworks to enhance system capabilities. Technical Skills: Proficiency in front-end technologies: HTML, CSS, JavaScript (React, Angular, or Vue.js). Proficiency in back-end technologies: Node.js, Python, or Java. Strong understanding of databases: SQL (MySQL/PostgreSQL) and NoSQL (MongoDB). Hands-on experience with CI/CD tools (Jenkins, GitHub Actions, GitLab CI/CD, CircleCI). Familiarity with AI frameworks such as TensorFlow, PyTorch, or Hugging Face. Nice-to-Have Skills: Experience with cloud platforms such as AWS, Azure, or Google Cloud. Knowledge of containerization tools (Docker, Kubernetes) and infrastructure as code (Terraform, CloudFormation). Understanding of transformer models like GPT, BERT, or similar architectures. Exposure to Agile development practices. Problem Solver: Ability to address and solve technical challenges effectively. Team Player: Collaborative and proactive attitude in achieving team goals. Strong communication skills to explain technical concepts clearly. Interested candidates, kindly send your updated resume and a link to your portfolio to anandraj@genworx.ai . Thank you Regards, Anandraj B Lead Recruiter Mail ID: anandraj@genworx.ai Contact: 9656859037 Website: https://genworx.ai/

NTT DATA is seeking a Digital Engineering Lead Engineer to join the team in Pune, Mahrshtra (IN-MH), India. As a part of the team, you will exercise expertise in developing AI/ML applications focusing on prediction, recommendation, text analytics, computer vision, bots, and content intelligence. You will apply statistical skills and advanced statistical techniques, demonstrating deep knowledge of ML frameworks like TensorFlow, PyTorch, Keras, Spacy, and scikit-learn. In this role, you will leverage advanced knowledge of Python open-source software stack such as Django or Flask, Django Rest or FastAPI, etc. You should have deep knowledge in statistics, Machine Learning models, deep learning models, NLP, Generative Adversarial Networks (GAN), and other generative models. Experience working with RAG technologies and LLM frameworks like Langchain and LlamaIndex, LLM model registries (Hugging Face), LLM APIs, embedding models, and vector databases (FAISS, Milvus, etc.) is essential. Proficiency in programming languages such as Python and understanding of various Python packages is required. You will develop and implement GenAI solutions, collaborating with cross-functional teams to support the successful execution of AI projects for a diverse range of clients. Additionally, you will contribute to the development of frameworks, capabilities, and features for NTT DATA's global GenAI platform and TechHub. The ideal candidate should have a minimum of 2+ years of experience architecting high-impact GenAI solutions for diverse clients, preferably in Private AI and Smart Agentic Solutions. Furthermore, 5+ year(s) of experience participating in projects focusing on predictive analytics, data design, generative AI, AI/ML, and ML Ops is preferred. A minimum of 3 years of experience using Python is required, along with the ability to travel at least 25% and a Bachelor's Degree. NTT DATA is a trusted global innovator of business and technology services committed to helping clients innovate, optimize, and transform for long-term success. As a Global Top Employer, NTT DATA has diverse experts in more than 50 countries, with services including business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation, and management of applications, infrastructure, and connectivity. Join us on our journey to help organizations and society move confidently and sustainably into the digital future. Visit us at us.nttdata.com.,

You should have the ability to work with large data sets using Python and possess a strong background in Python programming, MySQL, Linux, and Machine Learning. It is essential to have basic knowledge of other relevant technologies such as Cloud computing, Jupyter Notebook, Machine learning algorithms, TensorFlow, PyTorch, Tesseract OCR, and NLP techniques including models like SpaCy, Bert, NLTK, and AutoML. You will be required to work through the phases of the project. This is a full-time job that requires you to work in person. The interview will be conducted in person, and there are no telephonic interviews scheduled. The job follows a Day shift and Morning shift schedule. A Bachelor's degree is preferred for this role. Additionally, having 1 year of experience in C++ is required for this position.,

Short Description: Ford Artificial Intelligence Advancement Center is looking for professionals experienced in NLP/LLM/GenAI, who are hands-on and can employ many NLP/Prompt engineering techniques from traditional statistical/ML NLP to DL-based sequence models and transformers in their day-to-day work. Description: You'll be working alongside leading technical experts from all around the world, on a variety of products involving Sequence/token classification, QA/chatbots, translation, semantic/search and summarization, among others. Responsibilities: Design NLP/LLM/GenAI applications/products by following robust coding practices, Explore SoTA models/techniques so that they can be applied for automotive industry usecases Conduct ML experiments to train/infer models; if need be, build models that abide by memory & latency restrictions, Deploy REST APIs or a minimalistic UI for NLP applications using Docker and Kubernetes tools. Showcase NLP/LLM/GenAI applications in the best way possible to users through web frameworks (Dash, Plotly, Streamlit, etc.,) Converge multibots into super apps using LLMs with multimodalities. Develop agentic workflow using Autogen, Agentbuilder, langgraph Build modular AI/ML products that could be consumed at scale. Qualifications: Education : Bachelors or master’s degree in computer science, Engineering, Maths or Science Performed any modern NLP/LLM courses/open competitions is also welcomed. Technical Requirements : Soft Skills : Strong communication skills and do excellent teamwork through Git/slack/email/call with multiple team members across geographies. GenAI Skills : Experience in LLM models like PaLM, GPT4, Mistral (open-source models), Work through the complete lifecycle of Gen AI model development, from training and testing to deployment and performance monitoring. Developing and maintaining AI pipelines with multimodalities like text, image, audio etc. Have implemented in real-world Chat bots or conversational agents at scale handling different data sources. Experience in developing Image generation/translation tools using any of the latent diffusion models like stable diffusion, Instruct pix2pix. Expertise in handling large scale structured and unstructured data. Efficiently handled large-scale generative AI datasets and outputs. ML/DL Skills : High familiarity in the use of DL theory/practices in NLP applications Comfort level to code in Huggingface, LangChain, Chainlit, Tensorflow and/or Pytorch, Scikit-learn, Numpy and Pandas Comfort level to use two/more of open source NLP modules like SpaCy, TorchText, fastai.text, farm-haystack, and others NLP Skills : Knowledge in fundamental text data processing (like use of regex, token/word analysis, spelling correction/noise reduction in text, segmenting noisy unfamiliar sentences/phrases at right places, deriving insights from clustering, etc.,) Have implemented in real-world BERT/or other transformer fine-tuned models (Seq classification, NER or QA) from data preparation, model creation and inference till deployment. Python Project Management Skills Familiarity in the use of Docker tools, pipenv/conda/poetry env Comfort level in following Python project management best practices (use of setup.py, logging, pytests, relative module imports,sphinx docs,etc.,) Familiarity in use of Github (clone, fetch, pull/push,raising issues and PR, etc.,) Cloud Skills and Computing : Use of GCP services like BigQuery, Cloud function, Cloud run, Cloud Build, VertexAI, Good working knowledge on other open-source packages to benchmark and derive summary. Experience in using GPU/CPU of cloud and on-prem infrastructures. Skillset to leverage cloud platform for Data Engineering, Big Data and ML needs. Deployment Skills : Use of Dockers (experience in experimental docker features, docker-compose, etc.,) Familiarity with orchestration tools such as airflow, Kubeflow Experience in CI/CD, infrastructure as code tools like terraform etc. Kubernetes or any other containerization tool with experience in Helm, Argoworkflow, etc., Ability to develop APIs with compliance, ethical, secure and safe AI tools. UI : Good UI skills to visualize and build better applications using Gradio, Dash, Streamlit, React, Django, etc., Deeper understanding of javascript, css, angular, html, etc., is a plus. Miscellaneous Skills : Data Engineering: Skillsets to perform distributed computing (specifically parallelism and scalability in Data Processing, Modeling and Inferencing through Spark, Dask, RapidsAI or RapidscuDF) Ability to build python-based APIs (e.g.: use of FastAPIs/ Flask/ Django for APIs) Experience in Elastic Search and Apache Solr is a plus, vector databases.

Dear Candidate, We are looking for an experienced Machine Learning Engineer to develop and deploy ML models for real-world applications. If you have expertise in Python, TensorFlow, and data science pipelines, wed love to hear from you! Key Responsibilities: Design, develop, and deploy machine learning models for predictive analytics. Work with large datasets to train and fine-tune models. Optimize model performance and scalability. Implement MLOps practices for model deployment and monitoring. Collaborate with data scientists and engineers on AI/ML projects. Required Skills & Qualifications: Strong programming skills in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn). Experience with deep learning, NLP, or computer vision. Knowledge of cloud-based ML services (AWS SageMaker, Azure ML, Google AI). Familiarity with data preprocessing, feature engineering, and model evaluation. Understanding of MLOps and CI/CD for machine learning pipelines. Soft Skills: Strong analytical and problem-solving abilities. Ability to work with cross-functional teams. Excellent communication and presentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Reddy Delivery Manager Integra Technologies

You should be proficient in programming languages such as Python and R. You must have a strong understanding of machine learning algorithms and frameworks like TensorFlow, PyTorch, and scikit-learn. Experience with conversational AI platforms, especially Oracle Digital Assistant, is preferred. Additionally, you should have familiarity with data processing tools and platforms such as Apache Spark and Hadoop. It is essential to be familiar with Oracle Cloud Infrastructure (OCI) and its services for deploying ODA & AI/ML models. Experience with natural language processing (NLP) techniques and libraries like NLTK and SpaCy is required. Understanding deep learning architectures for NLP, such as transformers and BERT, is a plus. Knowledge of containerization and orchestration tools like Docker and Kubernetes is beneficial. Moreover, you should possess skills in statistical analysis and data visualization using the R-language. This position is full-time and requires working the morning shift. Ideally, candidates should have at least 2 years of experience in AI/ML. The work location is in person.,

Imagine what you could do here. At Apple, new ideas have a way of becoming phenomenal products, services, and customer experiences very quickly. Every single day, people do amazing things at Apple. Do you want to impact the future of Manufacturing here at Apple through cutting edge ML techniques This position involves a wide variety of skills, innovation, and is a rare opportunity to be working on ground breaking, new applications of machine-learning, research and implementation. Ultimately, your work would have a huge impact on billions of users across the globe. You can help inspire change, by using your skills to influence globally recognized products" supply chain. The goal of Apple's Manufacturing & Operations team is to take a vision of a product and turn it into a reality. Through the use of statistics, the scientific process, and machine learning, the team recommends and implements solutions to the most challenging problems. Were looking for experienced machine learning professionals to help us revolutionize how we manufacture Apples amazing products. Put your experience to work in this highly visible role. Operations Advanced Analytics team is looking for creative and motivated hands-on individual contributors who thrive in a dynamic environment and enjoy working with multi-functional teams. As a member of our team, you will work on applied machine-learning algorithms to seek problems that focus on topics such as classification, regression, clustering, optimizations and other related algorithms to impact and optimize Apples supply chain and manufacturing processes. As a part of this role, you would work with the team to build end-to-end machine learning systems and modules, and deploy the models to our factories. You'll be collaborating with Software Engineers, Machine Learning Engineers, Operations, and Hardware Engineering teams across the company. Minimum Qualifications - 3+ years experience in machine learning algorithms, software engineering, and data mining models with an emphasis on large language models (LLM) or large multimodal models (LMM). - Masters in Machine Learning, Artificial intelligence, Computer Science, Statistics, Operations Research, Physics, Mechanical Engineering, Electrical Engineering, or related field. Preferred Qualifications - Proven experience in LLM and LMM development, fine-tuning, and application building. Experience with agents and agentic workflows is a major plus. - Experience with modern LLM serving and inference frameworks, including vLLM for efficient model inference and serving. - Hands-on experience with LangChain and LlamaIndex, enabling RAG applications and LLM orchestration. - Strong software development skills with proficiency in Python. Experienced user of ML and data science libraries such as PyTorch, TensorFlow, Hugging Face Transformers, and scikit-learn. - Familiarity with distributed computing, cloud infrastructure, and orchestration tools, such as Kubernetes, Apache Airflow (DAG), Docker, Conductor, Ray for LLM training and inference at scale is a plus. - Deep understanding of transformer-based architectures (e.g., BERT, GPT, LLaMA) and their optimization for low-latency inference. - Ability to meaningfully present results of analyses in a clear and impactful manner, breaking down complex ML/LLM concepts for non-technical audiences. - Experience applying ML techniques in manufacturing, testing, or hardware optimization is a major plus. - Proven experience in leading and mentoring teams is a plus. Submit CV,

You will be responsible for building and interpreting machine learning models on real business data from the SigView platform, such as Logistic Regression, Boosted trees (Gradient boosting), Random Forests, and Decision Trees. Your tasks will include identifying data sources, integrating multiple sources or types of data, and applying data analytics expertise within a data source to develop methods to compensate for limitations and extend the applicability of the data. Moreover, you will be expected to extract data from relevant data sources, including internal systems and third-party data sources, through manual and automated web scrapping. Your role will involve validating third-party metrics by cross-referencing various syndicated data sources and determining the numerical variables to be used in the same form as they are from the raw datasets, categorized into buckets, and used to create new calculated numerical variables. You will perform exploratory data analysis using PySpark to finalize the list of compulsory variables necessary to solve the business problem and transform formulated problems into implementation plans for experiments by applying appropriate data science methods, algorithms, and tools. Additionally, you will work with offshore teams post data preparation to identify the best statistical model/analytical solution that can be applied to the available data to solve the business problem and derive actionable insights. Your responsibilities will also include collating the results of the models, preparing detailed technical reports showcasing how the models can be used and modified for different scenarios in the future to develop predictive insights. You will develop multiple reports to facilitate the generation of various business scenarios and provide features for users to generate scenarios. Furthermore, you will be interpreting the results of tests and analyses to develop insights into formulated problems within the business/customer context and provide guidance on risks and limitations. Acquiring and using broad knowledge of innovative data analytics methods, algorithms, and tools, including Spark, Elasticsearch, Python, Databricks, Azure, Power BI, Azure Cloud services, LLMs-Gen AI, and Microsoft Suite will be crucial for success in this role. This position may involve telecommuting and requires 10% travel nationally to meet with clients. The minimum requirements for this role include a Bachelor's Degree in Electronics Engineering, Computer Engineering, Data Analytics, Computer Science, or a related field plus five (5) years of progressive experience in the job offered or related occupation. Special skill requirements for this role include applying statistical methods to validate results and support strategic decisions, building and interpreting advanced machine learning models, using various tools such as Python, Scikit-Learn, XGBoost, Databricks, Excel, and Azure Machine Learning for data preparation and model validation, integrating diverse data sources using data analytics techniques, and performing data analysis and predictive model development using AI/ML algorithms. Your mathematical knowledge in Statistics, Probability, Differentiation and Integration, Linear Algebra, and Geometry will be beneficial. Familiarity with Data Science libraries such as NumPy, SciPy, and Pandas, Azure Data Factory for data pipeline design, NLTK, Spacy, Hugging Face Transformers, Azure Text Analytics, OpenAI, Word2Vec, and BERT will also be advantageous. The base salary for this position ranges from $171,000 to $190,000 per annum for 40 hours per week, Monday to Friday. If you have any applications, comments, or questions regarding the job opportunity described, please contact Piyush Khemka, VP, Business Operations, at 111 Town Square Pl., Suite 1203, Jersey City, NJ 07310.,

As a NLP & Generative AI Engineer at Gigaforce, you will be part of our dynamic AI/ML team based in Noida, working on cutting-edge technologies to revolutionize the insurance claims processing industry. We are a California-based InsurTech company with a strong focus on innovation and digital transformation in the Property and Casualty sector. You must have a minimum of 2 years of hands-on experience in traditional machine learning, natural language processing, and modern generative AI techniques to be considered for this role. We are looking for individuals who are passionate about deploying GenAI solutions to production, working with open-source technologies, and handling document-centric pipelines efficiently. Your main responsibilities will include building and deploying NLP and GenAI-driven products focusing on document understanding, summarization, classification, and retrieval. You will be designing and implementing models using LLMs such as GPT, T5, and BERT, along with working on scalable, cloud-based pipelines for training, serving, and monitoring models. Collaboration is key at Gigaforce, and you will work closely with cross-functional teams including data scientists, ML engineers, product managers, and developers. Additionally, you will contribute to open-source tools and frameworks in the ML ecosystem, deploying production-ready solutions using MLOps practices, and working on distributed/cloud systems with GPU-accelerated workflows. To be successful in this role, you should have a strong grasp of traditional ML algorithms, NLP fundamentals, and modern NLP & GenAI models. Proficiency in Python, experience with cloud platforms like AWS SageMaker, GCP, or Azure ML, and familiarity with MLOps tools and distributed computing are essential. Experience with document processing pipelines and understanding insurance-related documents is a plus. If you are looking for a challenging role where you can lead the design, development, and deployment of innovative AI/ML solutions in the insurance industry, then this position at Gigaforce is the perfect opportunity for you. Join us in our mission to transform the claims lifecycle into an intelligent, end-to-end digital experience.,

Job Overview As a manager in the Signal Integrity team you will lead the SI engineers focusing on aspects of electrical design, simulation, and verification-validation testing of high speed products in the connector and/or cable assembly, radio system industrytargeting high speed communications and connectivity within datacenters and wireless infrastructure. You will be expected to drive development teams in the areas of signal integrity for product and system design including modeling, simulation, testing and circuit board layout. You will work collaboratively within a broader cross functional team of mechanical, manufacturing, & operations to execute leading edge products designs. You will assign resources to work on the signal integrity performance of a product/platform beginning with the initial analysis through prototype fabrication & evaluation, and production verification testing. You will be expected to coordinate to drive the advancement of simulation tools and capabilities, identifying potential areas of process improvement, and solving complex problems and ensuring product development success. Responsibilities: Align the technology roadmap with front end / customer, and implement accordingly Familiar with signal integrity design, simulation and validation activities through product development cycles Coordinate to define signal integrity design performance/functional requirements for new products by closely engaging with front teams / lead customers Guide the team to preform signal integrity simulations for multiple high-speed standards on each product, including determining the correct simulation methodology, as well as a good understanding of the criteria for each interface. Driving product development for business success Engaging in innovative simulation and test tool improvement and process enhancement Driving best practices and efficiency in connector design and component qualifications from a signal integrity standpoint. Being a mentor and teacher to other engineers across disciplines / BUs, writes and presents technical papers at internal and external conferences. Being an expert in analyzing competitive products and driving internal & competing IP positions Mandate Skills: Bachelors degree in electrical engineering or equivalent work experience; Masters degrees highly recommended Minium of 10 years of relevant work experience in electrical design, RF design, or PCB design, with 3+ years managerial experience in leading an electrical or SI engineering team Familiar with signal integrity analysis tools (Agilent ADS, Ansys HFSS, CST, or equivalent tools) A solid understanding of electromagnetic theory and electrical circuit behavior Good analytical capabilities to interpret simulation and lab data to identify issues and provide guidance to team to fix identified problem. Familiarity with printed circuit board design, fabrication and assembly. Fluent in English (both verbal and written) to facilitate global communication both internally and with external customers. Strong background to work in a global environment able to accommodate varying time zones and capable of collaborating with individuals across geographies. Ability to, and experience with, teaching and training peers in applying software tools and methodologies, and in the use of electrical test equipment, including VNAs and TDRs Individual must be highly motivated, a quick learner, and able to work independently Nice to have Skills: Experience with interconnect design, including socket/connector/cable/cable assembly design (high-speed twinax cables, direct attach copper (DAC) cables), and/or RF antenna, RF sub-system Design experience with communication systems (high-speed servers, switches, routers, storage, antennas, RF front end or similar systems) Solid presentation skills with an ability to clearly communicate technical concepts to diverse audiences in English Strong organizational and time management skills with an ability to manage and execute multiple tasks/deadlines/projects simultaneously with limited direction. Printed circuit board design, fabrication and assembly (Altium, AutoCAD) Test equipment (oscilloscope, vector network analyzer, BERT) Signal conditioning techniques (equalization, amplification) Direct customer design and support experience Application and test knowledge of high-speed devices and equalization techniques

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. Optum’s Applied AI team is seeking an experienced and pragmatic Lead Data Scientist to drive the end-to-end ML lifecycle, from problem definition to robust, scalable model deployment and continuous improvement. This role demands deep expertise in machine learning, particularly with advanced transformer models and Large Language Models (LLMs), applied to complex domains such as clinical document understanding and semantic search. Primary Responsibilities: Own the end-to-end data science lifecycle – from problem definition and experimentation to deployment, monitoring, and continuous improvement Design and deploy robust, explainable, and scalable ML models for clinical document understanding, named entity recognition, context disambiguation, and semantic search across prospective and retrospective use cases Lead model development with a focus on production-readiness, incorporating solid MLOps, reproducibility, and experimentation practices Diagnose and optimize model performance, mitigate bias, and ensure analytical integrity, accuracy, and operational efficiency Work hands-on with multi-modal transformer models for tasks like NER, handwriting and form understanding, and document classification Leverage LLMs and SLMs for clinical reasoning, automated annotation, data generation, and downstream distillation Collaborate with cross-functional teams – including ML engineers, annotators, and clinical domain experts – to translate business challenges into deployable AI solutions Implement automated data labeling pipelines using techniques like active learning, weak supervision, and human-in-the-loop systems Ensure reproducibility and operational excellence through Git, DVC, CI/CD pipelines, and orchestration tools (e.g., Airflow, Kafka) Mentor and guide junior scientists and engineers, lead technical design reviews, and set best practices for model architecture and evaluation Continuously identify and close gaps in the ML platform, proposing and implementing innovative solutions to improve performance, scalability, and reliability Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: Bachelor’s degree in Computer Science or adjacent field Advanced degree in a field that emphasizes the use of data science/statistics techniques (e.g., Computer Science, Applied Mathematics, or a field with direct NLP application) 5+ years of experience in Data Science with a focus on Machine Learning and Natural Language Processing Solid understanding of machine learning algorithms, NLP principles, and data modeling principles Proficiency in Python, R, and SQL. Experience in NLP libraries such as NLTK, SpaCy, and BERT Proven excellent Communication Skills Proven flexibility to provide support during critical business periods Proven ability to interpret and present complex data in various formats. Proven solid leadership skills, ability to meet deadlines, and work independently. An analytical mindset for addressing complex business needs Proven positive team player with a drive to learn and contribute to achieving results Willingness to work in varying shifts At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone–of every race, gender, sexuality, age, location and income–deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission. #NJP External Candidate Application Internal Employee Application

Design and fine-tune AI apps using GPT, BERT, Azure OpenAI, and Cognitive Services. Build chatbots with Copilot Studio, RAG pipelines, vector DBs, Graph API, and M365 Plugins. Code in Python/Node.js with REST API integration. Required Candidate profile 5+ years of experience in AI/ML or Conversational AI Strong grip on prompt engineering and model fine-tuning Deep understanding of Microsoft’s AI ecosystem

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Principal Consultant-Data Scientists with AI and Generative Model experience! We are currently looking for a talented and experienced Data Scientist with a strong background in AI, specifically in building generative AI models using large language models, to join our team. This individual will play a crucial role in developing and implementing data-driven solutions, AI-powered applications, and generative models that will help us stay ahead of the competition and achieve our ambitious goals. Responsibilities Collaborate with cross-functional teams to identify , analyze , and interpret complex datasets to develop actionable insights and drive data-driven decision-making. Basics of Statistics Experience in ML models Linear Regression, Logistic regression, Random forest etc Design, develop, and implement advanced statistical models, machine learning algorithms, AI applications, and generative models using large language models such as GPT-3, BERT and also frameworks like RAG, Knowledge Graphs etc. Experience in Azure platform Communicate findings and insights to both technical and non-technical stakeholders through clear and concise presentations, reports, and visualizations. Continuously monitor and assess the performance of AI models, generative models, and data-driven solutions, refining and optimizing them as needed. Stay up-to-date with the latest industry trends, tools, and technologies in data science, AI, and generative models, and apply this knowledge to improve existing solutions and develop new ones. Mentor and guide junior team members, helping to develop their skills and contribute to their professional growth. Qualifications we seek in you: Minimum Qualifications . Bachelor%27s or Master%27s degree in Data Science , Computer Science, Statistics, or a related field. . Experience in data science, machine learning, AI applications, and generative AI modelling. . Strong expertise in Python, R, or other programming languages commonly used in data science and AI, with experience in implementing large language models and generative AI frameworks. . Proficient in statistical modelling, machine learning techniques, AI algorithms, and generative model development using large language models such as GPT-3, BERT, or similar frameworks like RAG, Knowledge Graphs etc. . Experience working with large datasets and using various data storage and processing technologies such as SQL, NoSQL, Hadoop, and Spark. . Strong analytical, problem-solving, and critical thinking skills, with the ability to draw insights from complex data and develop actionable recommendations. . Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and explain complex concepts to non-technical stakeholders. Preferred Qualifications/ skills . Experience in deploying AI models, generative models, and applications in a production environment using cloud platforms such as AWS, Azure, or GCP. . Knowledge of industry-specific data sources, challenges, and opportunities relevant to Insurance . Demonstrated experience in leading data science projects from inception to completion, including project management and team collaboration skills. Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Job Area: Engineering Group, Engineering Group > Hardware Engineering General Summary: As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Hardware Engineer, you will plan, design, optimize, verify, and test electronic systems, bring-up yield, circuits, mechanical systems, Digital/Analog/RF/optical systems, equipment and packaging, test systems, FPGA, and/or DSP systems that launch cutting-edge, world class products. Qualcomm Hardware Engineers collaborate with cross-functional teams to develop solutions and meet performance requirements. Minimum Qualifications: Bachelor's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 3+ years of Hardware Engineering or related work experience. OR Master's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 2+ years of Hardware Engineering or related work experience. OR PhD in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 1+ year of Hardware Engineering or related work experience. BDC Post Silicon Engineering group has an opening for a Digital Bench characterization Engineer. This group develops Test solutions for Design verification of Highly integrated SOCs (System on Chip) designed by Qualcomm. We work with Design, System, Program Management, Yield, Reliability and Manufacturing teams to Test, support and commercialize Qualcomms products. As part of the Post Silicon Engineering group, you will be responsible for developing Test strategy & executing Bench characterization for leading edge LPDDR & PCDDR Subsystem components (DRAM, DRAM Controller, DRAM PHY, IOs, PLL/DLL, clocking architecture, Delay circuits, Power Distribution Network) and High-Speed IO interfaces (PCIe, USB2/3, Display Port, HDMI, MIPI-CSI/DSI, UFS & PLL). You will drive first Silicon debug, qualify semiconductor fabrication process, evaluate parametric performance of DDR & High-Speed IO IPs and perform failure analysis to root-cause a design problem. You with be working with IC design engineering, system engineering and Hardware applications engineering teams across the globe in a time critical environment. Education Requirements MTech, BTech or Equivalent in Electronics or Electrical Engineering with 1-3 years of related work experience Skills/Experience: Solid understanding of Electronics engineering fundamentals, DDR & High-Speed IO circuit analysis techniques and Semiconductor manufacturing process, Good understanding of Test and characterization methodology of DDR and High-Speed IO interfaces In-depth understanding of Mobile & PC DDR 2/3/4 protocol, timing diagrams, HSIO IPs PHY level understanding and Electrical parametric compliance specifications (eye diagram, differential signaling, jitter analysis, Receiver-Jitter-Tolerance, signal integrity, transmission line considerations, de-embedding). Hands-on experience using Bench instruments such as oscilloscopes, J-BERT, network / spectrum analyzers, signal generators and Logic analyzers is a must. Solid software skills for writing and debugging Test code using C, C# or Python. LabView knowledge is a plus. Using CAD software such as Mentor Graphics DA or Cadence Allegro is a plus. Ability to work effectively in a fast-paced environment with strong verbal and written communication skills. Keywords DDR, High-Speed IO, Electrical Spec compliance, Eye Diagram, Jitter, C, C#, Python, LabVIEW Applicants Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers.

Job Area: Engineering Group, Engineering Group > Systems Engineering General Summary: Qualcomms Audio Systems team is seeking a talented and highly motivated engineer specialized in the implementation of Voice AI and Audio solutions. You will work with a team to prototype, optimize, and productize state-of-the-art ML models, ensuring efficient deployment on snapdragon platforms Responsibilities: - Develop, optimize, and deploy Voice AI and audio ML models for audio applications, with a focus on inference efficiency across NPUs, GPUs, and CPUs. - Perform model evaluation, quantization, and compression to enable fast, robust inference on embedded hardware. - Analyze and compare model architectures (such as Diffusion Models, U-Nets, Transformers, BERT, BART, etc.) for use in audio applications. - Collaborate with cross-functional R&D, systems, and integration teams for system use case verification and commercialization support. - Contribute to the design and software implementation of audio ML models in embedded C/C++ and Python. - Evaluate system performance, debug, and optimize for performance and robustness. - Participate in industry trends, benchmarking and performance analysis of various Model architecture, and bring up-to-date architectural or technical innovations to the team. Requirements: - Strong programming skills in C/C++, Python. - Experience with audio processing and embedded solutions. - Hands-on experience working with audio framework and audio solutions on any platform - Familiarity with ML frameworks (PyTorch, TensorFlow, ONNX, etc.). - Knowledge of model quantization and compression techniques, and experience optimizing inference and deployment on embedded hardware. - Strong understanding of ML model architectures such as, CNNs, RNNs, Transformers, U-Nets, and statistical modeling techniques. - Understanding of DSP or Microcontroller architectures and frameworks - Experience developing and debugging software on embedded platforms; familiarity with software design patterns, multi-threaded programming (e.g., POSIX, PTHREADS), and fixed-point coding. - Excellent verbal and written communication skills; ability to work independently and as a team player in geographically dispersed, multidisciplinary teams. - Proven ability to work in a dynamic, multi-tasked environment "” quick learner, self-motivated, and results-driven. Minimum Qualifications: Bachelors, Masters or PhD in Computer Science, Electronics and Communication, Electrical Engineering, or a related field (or equivalent work experience). Preferred Qualifications: - Experience working with Qualcomm AI HW accelerators (NPUs) and Qualcomm SDKs - Knowledge of Qualcomm Audio framework, platforms and tools Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field. Applicants Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers.