633 Gen Ai Jobs - Page 16

Optum AI is UnitedHealth Groups enterprise AI team. We are AI/ML scientists and engineers with deep expertise in AI/ML engineering for health care. We develop AI/ML solutions for the highest impact opportunities across UnitedHealth Group businesses including UnitedHealthcare, Optum Financial, Optum Health, Optum Insight, and Optum Rx. In addition to transforming the health care journey through responsible AI/ML innovation, our charter also includes developing and supporting an enterprise AI/ML development platform. Optum AI team members: Have impact at scale: We have the data and resources to make an impact at scale. When our solutions are deployed, they have the potential to make health care system work better for everyone. Do ground-breaking work: Many of our current projects involve cutting edge ML, NLP and LLM techniques. Generative AI methods for working with structured and unstructured health care data are continuously being developed and improved. We are working in one of the most important frontiers of AI/ML research and development. Partner with world-class experts on innovative solutions: Our team members are developing novel AI/ML solutions to business challenges. In some cases, this includes the opportunity to file patents and publish papers about the methods we develop. We also collaborate with AI/ML researchers at some of the worlds top universities. OptumAI is looking for a Senior Machine Learning Engineer with deep subject matter expertise in text processing, NLU and SLU (Natural language understanding and Spoken Language Understanding) who will be part of a team leading the technical development and inventions that allow Optum machine learning products drive positive impact in the healthcare business. Your expertise will bring business and industry context to science and technology decisions. As part of the OptumAI AI/ML engineering group, you set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your code, designs and documents are exemplary and are used as references across the organization. A successful candidate is a hands-on AI/ML engineering expert that will tackle intrinsically hard problems, acquiring expertise as needed. The candidate will help decompose complex problems into straightforward solutions. Primary Responsibilities: Help design and develop the next generation of NLP, ML & AI products, and services for healthcare Develop machine learning and deep learning models and systems in domains including, but not limited to: NLP, NLU, NLG, SLU and multidimensional time series forecasting among others Exposure in RAG, LangChain, VectorDBs Ability to Quantize, Optimize GenAI models Manage NLP & ML models lifecycle for a suite of products Run large complex proof-of-concepts for the healthcare business Manage prioritization and technology work for building NLP, ML & AI solutions Lead the full end-to-end machine learning development process including data ingestion and preparation, feature engineering, analysis and modeling, model deployment, performance tracking and documentation Establish best practices for end-to-end deep learning and machine learning development cycle to ensure rigor in process and quality in outcome Work with a great deal of autonomy to find solutions to complex problems 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: Graduate degree in applicable area of expertise or equivalent experience Experience in deploying scalable solutions to complex problems, from defining the problem, implementing the solution, and launching the new product successfully Skill Set; NLP, NLU, NLI Architecture: Transformers, Attention Models: GPT, Llama, Mistral Model Quantization Model Optimization Retrieval & Ranking, RAG, RAGAS Statistics, Machine Learning Models, Model Deployment Proven excellent communication, writing and presentation skills Experience in the health care industry Preferred Qualification: Experience in the health care industry

Responsibilities Job Responsibilities: Lead the development of Gen AI solutions, including design, implementation, and deployment of AI models and systems Collaborate with cross-functional teams to identify business problems and develop AI-powered solutions to drive growth and efficiency Design and implement scalable and efficient AI solutions, leveraging technologies such as LangChain, Agentic AI, RAG, Event driven architecture using Kafka etc. Develop and maintain large-scale AI systems, ensuring high performance, reliability, and security Lead and mentor a team of AI developers, providing guidance and expertise to ensure high-quality deliverables Stay up-to-date with the latest advancements in Gen AI, Prompt Engineering, and related technologies, applying this knowledge to drive innovation and improvement Develop and maintain technical documentation, including architecture diagrams, design documents, and technical guides Participate in code reviews, ensuring high-quality code and adherence to coding standards and best practices Additional Responsibilities: Required Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or related field (B.E/B.Tech/M.E/M.Tech/MCA) At least 5-8 years of experience in software development, with a minimum of 2 years of experience in Gen AI Strong proficiency in LangChain, Python, Gen AI, Agentic AI, and Prompt Engineering Excellent communication, teamwork, problem-solving, and leadership skills Technical and Professional Requirements: Preferred Qualifications: Experience with Agentic Frameworks such LangGraph, AutoGen, CrewAI Experience with cloud-based AI platforms, such as AWS or Azure Knowledge of containerization technologies, such as Docker Familiarity with agile development methodologies, such as Scrum or Kanban Experience with AI-related tools and frameworks, such as TensorFlow or PyTorch Strong understanding of software design patterns, principles, and best practices Experience with DevOps practices, including continuous integration and continuous deployment (CI/CD) Certification in AI, machine learning, or related fields, such as Certified Data Scientist or Certified AI Engineer Preferred Skills: Technology->OpenSystem->Python - OpenSystem->Flask Technology->Artificial Intelligence->Artificial Intelligence - ALL Technology->Machine Learning->Python Technology->Programing language C->go lang Technology->Machine Learning->Generative AI->retrieval augmented generation (rag) Educational Requirements Bachelor of Engineering Service Line Information Systems

Role & responsibilities Mandate Skills : Python , AWS , Robot Framework , Selenium , Kafka (Knowledge), AI/ML(Gen AI etc..). Technical Skills: Proven experience in building automation frameworks for both frontend and backend systems. Hands-on experience with AWS services such as EC2, S3, Lambda, and Kafka. Strong understanding of Kafka, including producing and consuming messages for test automation. Hands-on experience with AI/ML tools for automation, such as Testim, Mabl, Functionize, or custom AI models (e.g., for NLP-based test generation or failure prediction). Prior experience in setting up AI-based test data generation. Experience in Python programming language. Familiarity with test automation tools and frameworks like Robot framework, Playwright, Selenium or similar. Strong understanding of REST APIs and API testing tools like Postman, Rest Assured etc.. Experience with CI/CD pipelines and tools such as Jenkins, GitLab etc Exposure to Graph DB, MongoDB, and Cassandra. Knowledge of Docker/Kubernetes is a plus Excellent problem-solving skills and attention to detail. Experience working in Agile projects Strong communication and collaboration skills to work effectively in a team environment. Essential Skills 1 Building automation frameworks for both frontend and backend systems. 2 Python Programing 3 AWS services such as EC2, S3, Lambda 4 Strong understanding of Kafka 5 AI/ML tools for automation, such as Testim, Mabl, Functionize Good to have 1 Experience with CI/CD pipelines 2 test automation tools and frameworks like Robot framework, Playwright, Selenium or similar. 3 Knowledge of Docker/Kubernetes

Job Description: We are seeking a talented and experienced Data Scientist to join our dynamic team. The ideal candidate will have a strong background in data analysis, machine learning, statistical modeling, and artificial intelligence. Experience with Natural Language Processing (NLP) is desirable. Experience delivering products that incorporate AI/ML, familiarity with Cloud Services such as AWS highly desirable. Key Responsibilities: Clean, prepare, and explore data to find trends and patterns Build, validate, and implement AI/ML models Extensively document all aspects of the work including data analysis, model development, results Collaborate with other team members teams to incorporate AI/ML models into software applications Stay updated with the latest advancements in AI/ML domain and incorporate into day-to-day work Required Skills/Qualifications: 3-5 years of experience in AI/ML related work Extensive experience in Python Familiarity with Statistical models such as Linear/Logistic regression, Bayesian Models, Classification/Clustering models, Time Series analysis Experience with deep learning models such as CNNs, RNNs, LSTM, Transformers Experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit- learn, Keras Experience with GenAI, LLMs, RAG architecture would be a plus Familiarity with cloud services such as AWS, Azure Familiarity with version control systems (e.g., Git), JIRA, Confluence Familiarity with MLOPs concepts, AI/ML pipeline tooling such as Kedro Knowledge of CI/CD pipelines and DevOps practices Experience delivering customer facing AI Solutions delivered as SaaS would be a plus Bachelors degree in Computer Science, Engineering, or a related field, or equivalent practical experience. Strong problem-solving skills and attention to detail Excellent verbal and written communication and teamwork skills Benefits: Competitive salary and benefits package Opportunity to work on cutting-edge technologies and innovative projects Collaborative and inclusive work environment Professional development and growth opportunities

About the role PubMatic is looking for engineers with expertise in Generative AI and AI agent development. You will be responsible for building and optimizing advanced AI agents that leverage the latest technologies in Retrieval-Augmented Generation (RAG), vector databases, and large language models (LLMs). You will work on developing state-of-the-art solutions that enhance Generative AI capabilities and enable our platform to handle complex information retrieval, contextual generation, and adaptive interactions. What You'll do Collaborate with engineers, architects, product managers, and UX designers to develop innovative AI solutions for new customer use-cases. Work independently and iterate quickly based on customer feedback to make product tweaks. Implement and optimize LLMs for specific use cases, including fine-tuning models, deploying pre-trained models, and evaluating their performance. Develop AI agents powered by RAG systems, integrating external knowledge sources to improve the accuracy and relevance of generated content. Design, implement, and optimize vector databases (e.g., FAISS, Pinecone, Weaviate) for efficient and scalable vector search, and work on various vector indexing algorithms. Create sophisticated prompts and fine-tune them to improve the performance of LLMs in generating precise and contextually relevant responses. Utilize evaluation frameworks and metrics (e.g., Evals) to assess and improve the performance of generative models and AI systems. Work with data scientists, engineers, and product teams to integrate AI-driven capabilities into customer-facing products and internal tools. Stay up to date with the latest research and trends in LLMs, RAG, and generative AI technologies to drive innovation in the companys offerings. Continuously monitor and optimize models to improve their performance, scalability, and cost efficiency We'd Love for You to Have Must Have Strong understanding of large language models (GPT, BERT, T5, etc.) and their underlying principles, including transformer architecture and attention mechanisms. Proven experience building AI agents with Retrieval-Augmented Generation to enhance model performance using external data sources (documents, databases). In-depth knowledge of vector databases, vector indexing algorithms, and experience with technologies like FAISS, Pinecone, Weaviate, or Milvus. Ability to craft complex prompts to guide the output of LLMs for specific use cases, enhancing model understanding and contextuality. Familiarity with Evals and other performance evaluation tools for measuring model quality, relevance, and efficiency. Proficiency in Python and experience with machine learning libraries such as TensorFlow, PyTorch, and Hugging Face Transformers. Experience with data preprocessing, vectorization, and handling large-scale datasets. Ability to present complex technical ideas and results to both technical and non-technical stakeholders. Nice-to-Have Experience in building AI agents using graph-based architectures, including knowledge graph embeddings and graph neural networks (GNNs). Experience with training small base models using custom data, including data collection, pre-processing, and fine-tuning models to specific domains or tasks. Familiarity with deploying AI models on cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). Publication or contributions to research in AI, LLMs, or related fields. Qualifications Should have a bachelors degree in engineering (CS / IT) or equivalent degree from a well-known Institutes / Universities. If interested, please visit the link below to apply: https://pubmatic.com/job/?gh_jid=4615220008

About the role PubMatic is looking for engineers with expertise in Generative AI and AI agent development. You will be responsible for building and optimizing advanced AI agents that leverage the latest technologies in Retrieval-Augmented Generation (RAG), vector databases, and large language models (LLMs). You will work on developing state-of-the-art solutions that enhance Generative AI capabilities and enable our platform to handle complex information retrieval, contextual generation, and adaptive interactions. What You'll Do Provide technical leadership and mentorship to engineering teams while collaborating with architects, product managers, and UX designers to create innovative AI solutions that address complex customer challenges. Lead the design, development, and deployment of AI-driven features. Drive end-to-end ownershipfrom feasibility analysis and design specifications to execution and releasewhile ensuring quick iterations based on customer feedback in a fast-paced Agile environment. Spearhead technical design meetings and produce detailed design documents that outline scalable, secure, and robust AI architectures. Ensure that the solutions are aligned with long-term product strategy and technical roadmaps. Implement and optimize LLMs for specific use cases, including fine-tuning models, deploying pre-trained models, and evaluating their performance. Develop AI agents powered by RAG systems, integrating external knowledge sources to improve the accuracy and relevance of generated content. Design, implement, and optimize vector databases (e.g., FAISS, Pinecone, Weaviate) for efficient and scalable vector search, and work on various vector indexing algorithms. Create sophisticated prompts and fine-tune them to improve the performance of LLMs in generating precise and contextually relevant responses. Utilize evaluation frameworks and metrics (e.g., Evals) to assess and improve the performance of generative models and AI systems. Work with data scientists, engineers, and product teams to integrate AI-driven capabilities into customer-facing products and internal tools. Stay up to date with the latest research and trends in LLMs, RAG, and generative AI technologies to drive innovation in the companys offerings. Continuously monitor and optimize models to improve their performance, scalability, and cost efficiency We'd Love for You to Have Must Have Strong understanding of large language models (GPT, BERT, T5, etc.) and their underlying principles, including transformer architecture and attention mechanisms. Proven experience building AI agents with Retrieval-Augmented Generation to enhance model performance using external data sources (documents, databases). In-depth knowledge of vector databases, vector indexing algorithms, and experience with technologies like FAISS, Pinecone, Weaviate, or Milvus. Ability to craft complex prompts to guide the output of LLMs for specific use cases, enhancing model understanding and contextuality. Familiarity with Evals and other performance evaluation tools for measuring model quality, relevance, and efficiency. Proficiency in Python and experience with machine learning libraries such as TensorFlow, PyTorch, and Hugging Face Transformers. Experience with data preprocessing, vectorization, and handling large-scale datasets. Ability to present complex technical ideas and results to both technical and non-technical stakeholders. Nice-to-Have Experience in building AI agents using graph-based architectures, including knowledge graph embeddings and graph neural networks (GNNs). Experience with training small base models using custom data, including data collection, pre-processing, and fine-tuning models to specific domains or tasks. Familiarity with deploying AI models on cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). Publication or contributions to research in AI, LLMs, or related fields. Qualifications Should have a bachelors degree in engineering (CS / IT) or equivalent degree from a well-known Institutes / Universities. If interested, please visit the link below to apply: https://pubmatic.com/job/?gh_jid=4615235008

About Client Hiring for One of the Most Prestigious Multinational Corporations Job Title: Generative AI Engineer Experience: 8 to 13 years Key Responsibilities : Research, design, and implement Generative AI solutions using foundation models like GPT, PaLM, Claude, or open-source LLMs (e.g., LLaMA, Falcon). Build and fine-tune custom models using Transfer Learning , RLHF , or LoRA for domain-specific applications. Develop intelligent applications using Natural Language Processing (NLP) , Computer Vision , or Multimodal AI . Apply data science techniques for feature engineering, model evaluation, and experimentation. Architect scalable ML pipelines using tools such as MLflow , Kubeflow , Vertex AI , SageMaker , or equivalent. Collaborate with cross-functional teams to understand business challenges and deliver GenAI-driven solutions. Ensure responsible AI practices by implementing explainability, bias detection, and governance mechanisms. Stay up to date with the latest research and trends in AI/ML, LLMs, and GenAI technologies. Technical Skills: Strong hands-on experience with core AWS services: EC2, S3, RDS, Lambda, IAM, VPC, CloudWatch, CloudTrail, ECS/EKS, etc. Expert in Infrastructure as Code (IaC) using Terraform , CloudFormation , or AWS CDK . Strong scripting and automation skills in Python , Bash , or Shell . Experience with containerization and orchestration tools ( Docker , Kubernetes /EKS). Solid understanding of networking, load balancing, and security concepts in the cloud. Experience with monitoring/logging tools like CloudWatch , Prometheus , Grafana , or ELK stack Knowledge of DevOps and CI/CD tools (Jenkins, GitLab CI, AWS CodePipeline, etc.). Familiarity with Agile/Scrum methodologies NOTE : Only immediate and 15 days joiners Notice period : Only immediate and 15 days joiners Location: Bangalore Mode of Work : WFO(Work From Office) Thanks & Regards, SWETHA Black and White Business Solutions Pvt.Ltd. Bangalore,Karnataka,INDIA. Contact Number:8067432433 rathy@blackwhite.in |www.blackwhite.in

Own and drive marketing tactics in close collaboration with the Tech & Alliance and growth marketing team. Assist in developing marketing collateral, promotional content and sales enablement content including email copy, brochures, web copy, presentations and sales material through workflow processes across several teams and touchpoints. Execute awareness and lead generation campaigns with demand generation and digital teams, including managing digital and social marketing, e-mail, webinars and paid search. Collaborate with internal comms team to increase awareness of tech & alliance content, sales enablement and events. Develop a deep understanding of our industries and competitive landscape. Create and manage ticketing system for new marketing projects. Generate, qualify and track leads to support campaign execution. Measure and assess marketing activities, reporting on outcomes and ROI. Create content and promotional assets for industry conferences and ZS-hosted events. What youll bring: Exceptional spoken and written American-English communication skills. Bachelors degree in business discipline, marketing preferred. 2-4 years of marketing experience, professional services or B2B technology marketing (product or solution marketing) preferred. Flexibility to work evening hours, think ahead and leverage time with global colleagues effectively so that individual work achieves maximum impact. Experience translating value propositions into impactful sales materials. Strong MS Office Skills (Word, Excel, PPT etc.), experience with Microsoft Dynamics and marketing automation a plus. Experience working with data and data tools to manipulate, analyze and interpret marketing data and outcome measures. Experience with Gen AI, design, and web tools. Experience balancing multiple tasks and delivering marketing tactics on deadline and within budget. Must be a self-starter with the ability to learn quickly and independently.

Job description Looking for SDET/ Automation testing with Gen AI Testing Interested ones share CV and below details to snidafazli@altimetrik.com Name(as per aadhar card): Phone Number: EmailID: Current CTC: Fixed CTC: Expected CTC: holding any offers: Current Company: Payroll Company: Notice period: If serving Notice period, exact LWD: Current Location: Preferred location: Total years of experience: Relevant Experience below in years, SDET: Gen AI Testing: Python/Java: Selenium: API Automation: Rest Assured: BDD: Cucumber:

Job Description We are seeking a Senior Software Engineer to lead and guide our engineering team in building and enhancing our internal AI Gateway platform. This platform empowers internal organizations to create and deploy AI use cases, integrating with Azure OpenAI, AWS Bedrock, Databricks, and other cloud platforms. You will drive architecture, design, and implementation of scalable data/model management pipelines, agentic AI, RAGs, tracing, and MCP server components. Essential to have hands on Development experience in Python JavaScript, TypeScript, Node JS Essential to have hands on experience in building scalable GenAI applications leveraging LLMs e.g. GPT, Claude, Anthropic using various techniques e.g. RAG, Agentic AI etc. Preferred experience in Developing GenAI Solutions using frameworks e.g. Langchain, LlamaIndex. Preferred experience in building AI pipelines for interaction via Chatbots, User Interface, Autonomous Agents. Must have excellent communication skills to understand complex AI concepts & work with architects to build the solution as well as the ability to explain it to Nontechnical Stakeholders. Preferred experience of deploying solutions on AWS with best, practices. Good to have built capabilities in GenAI backed by evaluation (any existing framework for evaluation or custom built for the specific use case).Contributions to AI research, opensource models or AI hackathons are a plus. Responsib0ilities: Lead the design and development of the AI Gateway platform and its integrations (Azure OpenAI, AWS Bedrock, Databricks, etc.). Architect and implement scalable, secure, and maintainable data/model management pipelines. Guide the team in building agentic AI, RAG (Retrieval-Augmented Generation), tracing, and MCP server solutions. Mentor and upskill team members, conduct code reviews, and enforce best practices. Collaborate with product, DevOps, and data science teams to deliver robust solutions. Drive automation and CI/CD for model and data pipeline deployments. Ensure platform reliability, observability, and security. Requirements: 7+ years of software engineering experience, with at least 2 years in a technical leadership role. Strong Python (FastAPI, asyncio), cloud (Azure, AWS), and data engineering skills. Experience with LLMs, agentic AI, RAGs, and orchestration frameworks. Hands-on with cloud ML services (Azure OpenAI, AWS Bedrock, Databricks). Familiarity with CI/CD, Docker, Kubernetes, and infrastructure-as-code.

JOB DESCRIPTION Title: Senior Software Engineer - Data Science Full time Chennai Data Scientist Role Type: Location: Reports to: Summary of the profile: We are seeking a highly motivated and innovative Data Scientist with 3-5 years of experience to join our team, with a focus on leveraging Generative AI and Large Language Models (LLMs). The ideal candidate will be passionate about exploring the potential of these cutting-edge technologies to solve complex problems and create impactful solutions. You will collaborate with cross-functional teams to research, develop, and deploy generative AI models and LLM-powered applications. What youll do here: Explore and experiment with various generative AI models (e.g., GANs, VAEs, diffusion models) and LLMs (e.g., GPT, BERT, Llama). ¢ Fine-tune pre-trained LLMs for specific tasks and domains. Develop and implement generative models for tasks like data augmentation, content generation, and synthetic data creation. ¢ ¢ ¢ Prompt engineering, and prompt iteration. Collect, clean, and preprocess large text datasets for LLM training and evaluation. Perform natural language processing (NLP) tasks such as text classification, sentiment analysis, and entity recognition. ¢ ¢ Use LLMs to assist in data cleaning and data understanding. Develop and evaluate machine learning models, including those leveraging generative AI and LLMs. ¢ Evaluate model performance using relevant metrics and techniques, including those specific to LLMs (e.g., perplexity, BLEU score). ¢ ¢ Tune hyperparameters to optimize model performance. Create compelling visualizations and reports to communicate insights from generative AI and LLM experiments. ¢ ¢ Present findings to both technical and non-technical audiences. Collaborate with engineers, product managers, and researchers to define project requirements and deliver solutions. ¢ ¢ Communicate effectively with team members and stakeholders, both verbally and in writing. Stay up-to-date with the latest advancements in generative AI and LLMs. Copyright © RESULTICKS Solution Inc 1 ¢ ¢ Assist in deploying generative AI models and LLM-powered applications to production environments. Monitor model performance and retrain models as needed. What you will need to thrive: ¢ ¢ 3-5 years of professional experience in data science, with a growing interest in Generative AI and LLMs. Proficiency in Python and relevant libraries (e.g., NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Hugging Face Transformers). ¢ ¢ ¢ ¢ ¢ ¢ Experience with NLP techniques and libraries. Understanding of machine learning algorithms and statistical concepts. Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau, Power BI). Excellent problem-solving and analytical skills. Strong communication and collaboration skills. Experience with Prompt engineering, version control systems like Git and cloud platforms like GCP, AWS or Azure is a plus Preferred Skills: ¢ ¢ ¢ ¢ ¢ ¢ Experience with fine-tuning LLMs for specific tasks. Experience with deploying LLMs in production environments. Knowledge of deep learning architectures relevant to generative AI and LLMs. Familiarity with vector databases. Experience with RAG (Retrieval Augmented Generation) architectures. Experience with the Langchain Library. Education: ¢ Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field. Core competencies: ¢ Communication, Analytical & Problem-Solving Skills Copyright © RESULTICKS Solution Inc 2 About RESULTICKS RESULTICKS is a fully integrated connected experience platform for Real Time Audience Engagement. RESULTICKS empowers brands to create data-driven communications to their audiences and drives business decisions through its award-winning, AI-powered big data cloud solution. Supported by the worlds first customer data blockchain, RESULTICKS unlocks incredible digital transformation possibilities by delivering the full 360 view of the customer through data consolidation and omnichannel orchestration. Built from the ground up by experts in marketing, technology, and business management, RESULTICKS enables brands to make a transformational leap to conversion- driven, growth-focused personalized engagement. With an advanced CDP at its core. RESULTICKS offers AI-powered omnichannel orchestration, complete analytics, next-best engagement, attribution at the segment-of-one level, and the worlds first marketing block chain. ¢ RESULTICKS has been named to the Gartners Magic Quadrant 2021 for Multichannel Marketing Hubs for five years in a row and has been awarded with the Microsoft Elevating Customer Experience with AI award. ¢ Headquartered in Singapore and New York City, RESULTICKS is one of the top global martech solutions servicing both B2B/B2B2C and B2C segments. RESULTICKS global presence includes the United States, India, Singapore, Indonesia, Malaysia, Vietnam, Thailand, and the Philippines. Watch video on RESULTICKS - https://www.youtube.com/watch?v=G_OwGy6unP8 Copyright © RESULTICKS Solution Inc 3

Contract 1 Year OnsiteOnly No Remote (Work from Office from Day 1) Contact: +91 90329 56160 PrimarySkills Python ,FastAPI ,ReactJS ,Full Stack Lead ,Web Development ,Team Lead Must Have Skills 7+ years experience in developing scalable web applications Hands-on development using Python with FastAPI Front-end development using ReactJS Proven experience in leading a full stack development team Strong understanding of RESTful services and modern web architecture Good To Have Skills Cloud deployment experience AWS / Azure / GCP Hands-on with containerized solutions: Docker and #Kubernetes Strong problem-solving and team collaboration abilities Coding Skills Must be able to write pseudo code using both #Python (#FastAPI) and #React Strong hands-on coding, architecture, and debugging experience required ApplicationChecklist Please include the following details when submitting your profile: Current CTC Expected CTC Current Location Notice Period Only Immediate Joiners or Max 15 Days

Job Summary: We are seeking a highly skilled MLOps Engineer to design, deploy, and manage machine learning pipelines in Google Cloud Platform (GCP). In this role, you will be responsible for automating ML workflows, optimizing model deployment, ensuring model reliability, and implementing CI/CD pipelines for ML systems. You will work with Vertex AI, Kubernetes (GKE), BigQuery, and Terraform to build scalable and cost-efficient ML infrastructure. The ideal candidate must have a good understanding of ML algorithms, experience in model monitoring, performance optimization, Looker dashboards and infrastructure as code (IaC), ensuring ML models are production-ready, reliable, and continuously improving. You will be interacting with multiple technical teams, including architects and business stakeholders to develop state of the art machine learning systems that create value for the business. Responsibilities: Managing the deployment and maintenance of machine learning models in production environments and ensuring seamless integration with existing systems. Monitoring model performance using metrics such as accuracy, precision, recall, and F1 score, and addressing issues like performance degradation, drift, or bias. Troubleshoot and resolve problems, maintain documentation, and manage model versions for audit and rollback. Analyzing monitoring data to preemptively identify potential issues and providing regular performance reports to stakeholders. Optimization of the queries and pipelines. Modernization of the applications whenever required Qualifications: Expertise in programming languages like Python, SQL Solid understanding of best MLOps practices and concepts for deploying enterprise level ML systems. Understanding of Machine Learning concepts, models and algorithms including traditional regression, clustering models and neural networks (including deep learning, transformers, etc.) Understanding of model evaluation metrics, model monitoring tools and practices. Experienced with GCP tools like BigQueryML, MLOPS, Vertex AI Pipelines (Kubeflow Pipelines on GCP), Model Versioning & Registry, Cloud Monitoring, Kubernetes, etc. Solid oral and written communication skills and ability to prepare detailed technical documentation of new and existing applications. Strong ownership and collaborative qualities in their domain. Takes initiative to identify and drive opportunities for improvement and process streamlining. Bachelors Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience. Bonus Qualifications: Experience in Azure MLOPS, Familiarity with Cloud Billing. Experience in setting up or supporting NLP, Gen AI, LLM applications with MLOps features. Experience working in an Agile environment, understanding of Lean Agile principles.

Job Description : As an LLMOps Engineer, you will play a crucial role in the deployment, maintenance, and optimization of large language models (LLMs). Your responsibilities will span the entire lifecycle of LLMs, from initial deployment to ongoing operations, ensuring optimal performance, scalability, and reliability. Key Responsibilities : LLM Deployment and Integration - Deploy and integrate large language models into production environments, ensuring seamless integration with existing systems and applications. Infrastructure Planning and Scaling - Collaborate with cross-functional teams to plan and design the infrastructure required for LLM deployment. Implement scalable solutions to accommodate growing data volumes and user loads. Automation of Deployment Processes - Develop and maintain automation scripts and tools for efficient deployment, scaling, and versioning of LLMs. Streamline deployment processes to minimize downtime. Continuous Monitoring and Alerting - Implement monitoring systems to track LLM performance metrics. Set up alerts for potential issues and respond promptly to ensure uninterrupted service. Performance Monitoring and Optimization - Monitor the performance of LLMs in real-time, conduct regular assessments, and implement optimizations to enhance efficiency and responsiveness. Fault Tolerance and Disaster Recovery - Design and implement fault-tolerant systems for LLMs, incorporating strategies such as redundancy, sharding, and replication. Develop and maintain disaster recovery plans. Security Measures Implementation - Implement robust security measures to safeguard LLMs and associated data. Ensure compliance with data security regulations and industry standards. Collaboration with NLP Engineers and Data Scientists - Collaborate with NLP (Natural Language Processing) engineers and data scientists to understand model requirements and implement necessary infrastructure adjustments. Skills & Tools Infrastructure as Code (IaC) - Experience with IaC tools such as Terraform or Ansible for automating infrastructure provisioning. Containerization and Orchestration - Proficiency in containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) for managing LLM deployments. Cloud Platforms - Familiarity with cloud platforms such as AWS (Bedrock), Azure, or GCP, and experience in deploying and managing applications in a cloud environment. Monitoring and Logging Tools - Knowledge of monitoring tools (e.g., Prometheus, Grafana) and logging systems (e.g., ELK stack) for real-time performance monitoring and analysis. Security Measures - Understanding of security guardrails using tools like LLM Guard and familiarity of how to mask / redact / obfuscate sensitive data, protect the input and output of toxic and harmful content to / from LLMs and understand the performance implications of the same. Scripting and Automation - Proficient in scripting languages such as Python, Shell, or similar, and experience in automating deployment and maintenance processes.

Job Responsibility: Products.looking for a data scientist who will help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver AI/ML based Enterprise Software Products. • Develop solutions related to machine learning, natural language processing and deep learning & Generative AI to address business needs. • Your primary focus will be in applying Language/Vision techniques, developing llm based applications and building high quality prediction systems. • Analyze Data: Collaborate with cross-functional teams to understand data requirements and identify relevant data sources. Analyze and preprocess data to extract valuable insights and ensure data quality. • Evaluation and Optimization: Evaluate model performance using appropriate metrics and iterate on solutions to enhance performance and accuracy. Continuously optimize algorithms and models to adapt to evolving business requirements. • Documentation and Reporting: Document methodologies, findings, and outcomes in clear and concise reports. Communicate results effectively to technical and non-technical stakeholders. Work experience background required: • Experience building software from the ground up in a corporate or startup environment. Essential skillsets required: • 3-6 years experience in software development • Educational Background: Strong computer science and Math/Statistics • Experience with Open Source LLM and Langchain Framework and and designing efficient prompt for LLMs. • Proven ability with NLP and text-based extraction techniques. • Experience in Generative AI technologies, such as diffusion and/or language models. • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc. • Familiarity with cloud computing platforms such as GCP or AWS. Experience to deploy and monitor model in cloud environment. • Experience with common data science toolkits, such as NumPy, Pandas etc • Proficiency in using query languages such as SQL • Good applied statistics skills, such as distributions, statistical testing, regression, etc. • Experience working with large data sets along with data modeling, language development, and database technologies • Knowledge in Machine Learning and Deep Learning frameworks (e.g., TensorFlow, Keras, Scikit-Learn, CNTK, or PyTorch), NLP, Recommender systems, personalization, Segmentation, microservices architecture and API development. • Ability to adapt to a fast-paced, dynamic work environment and learn new technologies quickly. • Excellent verbal and written communication skills

Python Full Stack Developer (Lead Role) with React ,Gen ai ,Fast API Contract 1 Year Onsite Only No Remote (Work from Office from Day 1) Locations: 1/G1, SIPCOT IT Park, Navalur, Siruseri, Tamil Nadu 603103 Galaxy Park, IT Park, Block A 44-45, B Block Road, Sector 62, Noida - 201301 XPMP+8PV, ITPL Main Rd, Kadugodi, Whitefield, Bengaluru, Karnataka 560066 Share resumes to: navaneetha@suzva.com Contact: +91 90329 56160 Primary Skills Python, FastAPI, ReactJS, FullStackLead,Web Development, TeamLead Must Have Skills 7+ years experience in developing scalable web applications Hands-on development using Python with FastAPI Front-end development using ReactJS Proven experience in leading a full stack development team Strong understanding of RESTful services and modern web architecture Good To Have Skills Cloud deployment experience AWS / Azure / GCP Hands-on with containerized solutions: Docker and Kubernetes Strong problem-solving and team collaboration abilities Coding Skills Must be able to write pseudo code using both Python (FastAPI) and #React Strong hands-on coding, architecture, and debugging experience required Application Checklist Please include the following details when submitting your profile: Current CTC Expected CTC Current Location Notice Period Only Immediate Joiners or Max 15 Days

Job Summary: We are seeking a highly skilled MLOps Engineer to design, deploy, and manage machine learning pipelines in Google Cloud Platform (GCP). In this role, you will be responsible for automating ML workflows, optimizing model deployment, ensuring model reliability, and implementing CI/CD pipelines for ML systems. You will work with Vertex AI, Kubernetes (GKE), BigQuery, and Terraform to build scalable and cost-efficient ML infrastructure. The ideal candidate must have a good understanding of ML algorithms, experience in model monitoring, performance optimization, Looker dashboards and infrastructure as code (IaC), ensuring ML models are production-ready, reliable, and continuously improving. You will be interacting with multiple technical teams, including architects and business stakeholders to develop state of the art machine learning systems that create value for the business. Responsibilities: Managing the deployment and maintenance of machine learning models in production environments and ensuring seamless integration with existing systems. Monitoring model performance using metrics such as accuracy, precision, recall, and F1 score, and addressing issues like performance degradation, drift, or bias. Troubleshoot and resolve problems, maintain documentation, and manage model versions for audit and rollback. Analyzing monitoring data to preemptively identify potential issues and providing regular performance reports to stakeholders. Optimization of the queries and pipelines. Modernization of the applications whenever required Qualifications: Expertise in programming languages like Python, SQL Solid understanding of best MLOps practices and concepts for deploying enterprise level ML systems. Understanding of Machine Learning concepts, models and algorithms including traditional regression, clustering models and neural networks (including deep learning, transformers, etc.) Understanding of model evaluation metrics, model monitoring tools and practices. Experienced with GCP tools like BigQueryML, MLOPS, Vertex AI Pipelines (Kubeflow Pipelines on GCP), Model Versioning & Registry, Cloud Monitoring, Kubernetes, etc. Solid oral and written communication skills and ability to prepare detailed technical documentation of new and existing applications. Strong ownership and collaborative qualities in their domain. Takes initiative to identify and drive opportunities for improvement and process streamlining. Bachelors Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience. Bonus Qualifications: Experience in Azure MLOPS, Familiarity with Cloud Billing. Experience in setting up or supporting NLP, Gen AI, LLM applications with MLOps features. Experience working in an Agile environment, understanding of Lean Agile principles.

Before you apply to a job, select your language preference from the options available at the top right of this page. Experience in designing and developing a new test automation framework from scratch using a test automation tool like Playwright/JavaScript/TypeScript or /Selenium/Cucumber/Java or Selenium/C#.net/Spec Flow or similar frameworks. Hands-on experience in software testing and writing test automation code in at least one programming or scripting language (JavaScript, TypeScript, Java, C# and/or Python) and guide team members on technical front. Hands-on experience in developing and executing test scripts for REST or SOAP based APIs. Experience in intercepting and mocking complex HTTP API calls in UI and API tests. Experience in messaging systems (AMQ, WMQ or Kafka). Experience in writing and guiding teams on complex end-to-end tests automation. Experience on test management and defect tracking tools like Jira, Azure DevOps, HP ALM, etc. Experience in driving defect management strategy (create, set priority/severity, retest, close, traceability, reporting etc.) Experience in driving the team to implement automated test suites for all testing types (unit, component, API, UI, UAT, E2E, etc.) Hands-on experience in writing and executing complex SQL queries and understands concepts like indexing, schemas, views, etc. Experience in training team members to understand version control concepts. Perform lead-level automation code review as a required approver. Experience in guiding the team on version control concepts, tools and hands-on experience on commands and operations (like commit, fetch, push, pull, squash, resolve merge conflicts etc.) Experience in establishing branching strategy and best practices for automation code review process (in coordinate with Engg. lead, DevSecOps) Hands-on experience on at least one of the performance testing tools (e.g., JMeter, K6, LoadRunner, NeoLoad, etc.). Experience in analyzing performance testing requirements and implementation of load, stress, endurance, volume testing etc. Experience in leading the team on CI/CD pipeline implementation for automated tests suites. (in coordination with DevSecOps team) Experience in creating test plan for accessibility and security testing. Hands-on experience on cloud platforms (e.g., Azure, AWS, GCP) Understanding of Gen AI, Gen AI tools (e.g., GitHub CoPilot) and experience in leveraging Gen AI in quality engineering space. Language requirementEnglish ________________________________ The Lead Software Quality Engineer establishes plans and objectives for the Quality Assurance (QA) team, leads and develops staff, and ensures resources are effectively utilized for meeting business goals. He/She drives team results, including quality of work, timeliness, and budgetary goals. This position serves as a technical resource and provides expertise in key UPS business functions and supporting technologies. He/She collaborates with management to plan, coordinate, schedule, and manage QA resources. This position leads the improvement of work procedures and processes. He/She monitors project budget, timelines, and resource allocation (e.g., team members, contractors, vendors, etc.). The Lead Software Quality Engineer interacts with staff, customers, Information Services (I.S.) management, internal and external networks, QA professionals, and vendors to ensure effective integration between different functions, units, and teams. He/She contributes to initial project design phases, provides testing expertise, and develops test plans and strategies for projects. This position leads testing and development staff within the testing organization.

Job Description : Technical Skills Minimum 5 years of relevant experience as developer in Microsoft technologies(C#, VB.NET, Python) Hands on experience in SQL • Desired Skills o Domain Knowledge: Healthcare, Banking & Financial, Supply Chain or Manufacturing o BPO industry related domain background. Roles & Responsibility. Team member is responsible for the below listed activities. • Writes efficient, re-usable, optimal, and well documented code. • Designs, codes, tests and documents software programs for systems of the moderate to high complexity and engages in peer code reviews. • Perform architecture, design and review of development policies for adherence to standards and best practices • Participates in client/ external interactions on technical matters. • Drives engineering processes for the project such as build automation, unit testing, software configuration management and packaging. • Being a team player and adhering to project schedule. • Writing code enhancements and supporting existing code. • Providing guidance to junior developers in the team • Should have good logical skills and experience in delivering good quality code. • Provide software solutions to customer issues and responds to suggestions for improvements and enhancements / new tools. • Interacts with business users, I/T, vendors and customers to Identify potential tasks with production teams, customers and implement Robotic Process Automation including other applicable technologies for current and future application requirement

Build and maintain strong relationships with external customers to gain valuable insights into their behaviors, pain points, and expectations. Use customer insights to identify opportunities for innovation and to improve the products usability, performance, and overall value. Collaborate closely with design teams to create wireframes, prototypes, and user interfaces that align with customer needs and business goals. Work alongside engineering teams to refine requirements, address technical constraints, and ensure smooth execution of development cycles. Lead sprint planning, manage backlogs, and actively participate in daily stand-ups and retrospectives to keep projects on track. Education: 5+ years of experience in software product management, preferably in the collaboration or work management domain. Proven ability to prioritize effectively and focus on high-impact activities. Expertise in gathering and transforming product requirements into actionable roadmaps. A strong commitment to understanding customer needs and delivering customer-centric solutions. Experience with GenAI tools and building AI-driven product features. Contract to Hire role Immediate Joiners only Face to Face Interview Only Candidate from Hyderabad

Job Summary: We are seeking a highly skilled Functional AI Engineer to join our team and lead the development of custom knowledge-based AI models and large language model (LLM) implementations. The ideal candidate will have a strong background in artificial intelligence, machine learning, and natural language processing, with a focus on building innovative AI solutions that leverage knowledge-based systems and generative AI use cases. Key Responsibilities: - Design, develop, and implement knowledge-based AI models and LLMs to solve complex business problems. - Collaborate with cross-functional teams to identify opportunities for AI-driven solutions and develop custom use cases. - Conduct research and stay updated on the latest advancements in AI, machine learning, and NLP technologies. - Optimize and fine-tune AI models for performance, accuracy, and scalability. - Develop and maintain documentation for AI models, algorithms, and processes. - Ensure the ethical and responsible use of AI technologies in all implementations. - Provide technical guidance and mentorship to junior AI engineers and data scientists. - Work closely with stakeholders to understand business requirements and translate them into technical specifications. - Evaluate and integrate third-party AI tools and platforms as needed. - Monitor and analyze the performance of AI models, making necessary adjustments to improve outcomes. Qualifications: - Bachelor's or masters degree in computer science, Artificial Intelligence, Machine Learning, or a related field. - Proven experience in developing and implementing knowledge-based AI models and LLMs. - Strong programming skills in Python, TensorFlow, PyTorch, or similar AI frameworks. - Experience with natural language processing (NLP) and understanding of language models. - Familiarity with data management, data mining, and data visualization techniques. - Excellent problem-solving skills and ability to work independently and collaboratively. - Strong communication skills to effectively convey complex technical concepts to non-technical stakeholders. - Experience in the paints industry or similar sectors is a plus. Looking for immediate joiners 0-60 Days priority. Interested candidates can send their resume dhanashree.chitre@weareams.com

Data Scientist with 5+ years of relevant experience in: Python, SQL, NLP, LLM, GenAI, H2O

Req ID: 328247 NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now. We are currently seeking a APAC Presales Solution Architect to join our team in Bangalore, Karn?taka (IN-KA), India (IN). Job Duties: Senior Data and AI Architect - Presales Grade 11 Seeking a senior data solution architect to closely work with India and APAC sales teams for technical solutioning and presales work. The Consultant is a seasoned level expert who is responsible for participating in the delivery of multi-technology consulting services to clients by providing strategies and solutions on all aspects of infrastructure and related technology components. This role collaborates with other stakeholders on the development of the architectural approach for one or more layer of a solution. This role has the primary objective is to work on strategic projects that ensure the optimal functioning of the client's technology infrastructure. . Key Responsibilities: . Ability and experience to have conversations with the CEO, Business owners and CTO/CDO . Break down intricate business challenges, devise effective solutions, and focus on client needs. . Craft high level innovative solution approach for complex business problems . Utilize best practices and creativity to address challenges . Leverage market research, formulate perspectives, and communicate insights to clients . Establish strong client relationships . Interact at appropriate levels to ensure client satisfaction Minimum Skills Required: . Knowledge and Attributes: . Ability to focus on detail with an understanding of how it impacts the business strategically. . Excellent client service orientation. . Ability to work in high-pressure situations. . Ability to establish and manage processes and practices through collaboration and the understanding of business. . Ability to create new and repeat business for the organization. . Ability to contribute information on relevant vertical markets . Ability to contribute to the improvement of internal effectiveness by contributing to the improvement of current methodologies, processes and tools. . Academic Qualifications and Certifications: . BE/BTech or equivalent in Information Technology and/or Business Management or a related field. . Scaled Agile certification desirable. . Relevant consulting and technical certifications preferred, for example TOGAF. . Required Experience: 12-15 years . Seasoned demonstrable experience in a similar role within a large scale (preferably multi- national) technology services environment. . Very good understanding of Data, AI, Gen AI and Agentic AI . Must have Data Architecture and Solutioning experience. Capable of E2E Data Architecture and GenAI Solution design. . Must be able to work on Data & AI RFP responses as Solution Architect . 10+ years of experience in Solution Architecting of Data & Analytics, AI/ML & Gen AI Technical Architect . Develop On-prem, Cloud-native technical approach and proposal plans identifying the best practice solutions meeting the requirements for a successful proposal. Create, edit, and review documents, diagrams, and other artifacts in response to RPPs RFQs and Contribute to and participate in presentations to customers regarding proposed solutions. . Experience with large scale consulting and program execution engagements in AI and data . Seasoned multi-technology infrastructure design experience. . Seasoned demonstrable level of expertise coupled with consulting and client engagement experience, demonstrating good experience in client needs assessment and change management. . Additional Job Description . Knowledge and application: . Seasoned, experienced professional has complete knowledge and understanding of area of specialization. . Uses evaluation, judgment, and interpretation to select right course of action. . Problem solving: . Works on problems of diverse scope where analysis of information requires evaluation of identifiable factors. . Resolves and assesses a wide range of issues in creative ways and suggests variations in approach. . Interaction: . Enhances relationships and networks with senior internal/external partners who are not familiar with the subject m About NTT DATA NTT DATA is a $30 billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long term success. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity. We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a part of NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Visit us at NTT DATA endeavors to make accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at . This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. 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Key Requirements: A minimum of 5+ years of experience as an ML Engineer is must. Experience in ML model development applying Data Science algorithms and GenAI Are proficient with Python and Databricks , including open-source data libraries (e.g. Pandas, Numpy, Scikit learn, etc.). Strong understanding and experience of DevOps technologies such as Docker/Terraform and ML Ops practices and platforms/ frameworks like ML Flow ( Amazon Sagemaker/Azure Machine Learning) . Strong experience in production using machine learning models. Working experience in any one of predictive modelling, optimisation or recommendation systems. Hands-on experience with agile delivery methodologies and CI/CD. Hands-on experience with Unit Testing . Have a broad understanding of data extraction, data manipulation and feature engineering techniques. Are familiar with statistical and mathematical methodologies. Have an advanced degree in Computer Science, Mathematics or a similar quantitative discipline. Excellent communication skills. Good to Haves: PySpark/Ray for processing big data. DBT for data management. Understanding of NLP algorithms and techniques. Applied experience using graphs. Experience with Large Language Models (fine-tuning, RAG, agents, LangChain). Experience with cloud infrastructure. Good to have a masters degree in ML Engineering

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