254 Ml Algorithms Jobs - Page 5

Expected Notice Period: 30 Days Shift: (GMT+05:30) Asia/Kolkata (IST) Opportunity Type: Remote What do you need for this opportunity Must have skills required: Start-up Experience, Python, Ml frameworks, Statistical analysis, CNNs, Machine Learning, Computer Vision, AI models Leegality is Looking for: What you'll do As an ML Engineer, you will develop solutions to interesting technical problems, explore exciting growth opportunities, and have a real impact on our product. To ensure success as a machine learning engineer, you should demonstrate solid data science knowledge and experience in a related ML role. A first-class machine learning engineer will be someone whose expertise translates into the enhanced performance of predictive automation software. Responsibilities: Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models. Transforming data science prototypes and applying appropriate ML algorithms and tools. Solving complex problems with multi-layered data sets and optimizing existing machine learning libraries and frameworks. Developing ML algorithms to analyze huge volumes of historical data to make predictions. Running tests, performing statistical analysis, and interpreting test results. Exposure to generative AI (LLM) based ML architectures Experienced in working with CNN. Knows how to train and fine-tune CNN-based models. Documenting machine learning processes. Requirements: 1+ years of relevant experience in Machine Learning Engineering. Advanced proficiency with Python. Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture. Superb analytical and problem-solving abilities. Great communication and collaboration skills. Preferences: Start-up experience is good to have. Willing to join immediately, ideally. Female candidates are preferred Interview Process - Technical Round 1 - ML Fundamentals, NLP models Assessment Technical Round 2 - Discussion on the assignment submitted modify it according to the requirements Round 3 - with the Tech Lead - Tech Managerial - Past projects in-depth knowledge of ML

As Analyst/ Lead /Scientist, you will play a pivotal role in optimizing our SRE team's ability to proactively identify and resolve issues within our voice, text messaging platform infrastructure. You will leverage your expertise in AI/ML and data analysis to model system behavior, flag anomalies, and analyze large-scale datasets to drive data-driven optimization and ensure effective utilization of ML capabilities. Qualifications/Skills/Abilities Minimum Requirements Formal Education Bachelor's degree in computer science, Information Technology, or a related field with specialization in data science (or equivalent experience). Experience (type duration) 5+ years of experience in data analysis or data science, preferably in a technical or engineering environment. Telecom domain experience is good to have. Skills Proficiency in data analysis tools (e.g., SQL, Python, etc.,). Strong understanding of statistical concepts and techniques. Experience with data visualization tools (e.g., Tableau, Power BI, kibana, graphana, DOMO). Familiarity with cloud-based infrastructure and applications (e.g., AWS, Azure, GCP). Ability to work effectively in a fast-paced, collaborative environment. Experience working with large datasets, log analysis, and tools like Elastic and Domo (or similar) will be a significant advantage. Strong knowledge of AI/ML algorithms and frameworks (e.g., TensorFlow, PyTorch). Experience with anomaly detection techniques and tools. Accreditation / certifications / licenses Preferred: Advanced degree in data science or a related field. Experience in the telecom domain. Certification in data science or machine learning. Key Duties Responsibilities 1 AI/ML Model Development: Develop and implement AI/ML models to analyze system behavior, identify anomalies, and predict potential issues. 2 Collaborative Problem Solving: Work closely with SRE and DevOps teams to identify data logs, analyze system behavior, and develop AI/ML models to address issues. 3 Data Analysis and Modeling: Conduct in-depth analysis of large-scale datasets (SQL, NoSQL) to extract valuable insights and build predictive models. 4 Anomaly Detection: Develop robust anomaly detection algorithms to flag unusual system behavior and prevent potential disruptions. 5 Data-Driven Optimization: Optimize system performance and resource allocation based on data-driven insights and AI/ML recommendations. 6 ML Capability Utilization: Ensure effective integration and utilization of ML capabilities across the SRE team to enhance operational efficiency and reliability. 7 Telemetry Data Analysis: Analyze large datasets of telemetry data from various sources (e.g., call logs, performance metrics, system logs) to identify patterns, trends, and anomalies. 8 Alerting Optimization: Develop and refine alerting rules based on data-driven insights to ensure timely notification of critical issues and minimize alert fatigue. 9 Proactive Issue Identification: Leverage data analysis techniques and AI/ML models to proactively identify potential system issues or outages before they occur. 10 Root Cause Analysis: Investigate and analyze incidents to identify root causes and implement preventive measures. 11 Data Visualization: Create clear and informative visualizations to communicate findings to stakeholders and facilitate decision-making. Preferred Skills Preferred: Advanced degree in data science or a related field. Experience in the telecom domain. Certification in data science or machine learning. Required Skills 5+ years of experience in data analysis or data science, preferably in a technical or engineering environment. Telecom domain experience is good to have.

Looking for immediate to 15 days joiners and candidates should be currently located in Bangalore or Chennai. Total Experience : 7+ years Interview Mode : Virtual plus Face to Face Team Management experience in must. We are looking for a skilled and experienced Lead Data Scientist with a strong background in building AI-driven applications and solutions. In this role, you will play a critical role in advancing generative AI capabilities, creating solutions that streamline processes, and optimizing data insights across the organization. The ideal candidate will be highly analytical, with a deep understanding of machine learning algorithms, advanced data processing techniques, and hands-on experience with Azure Open AI services. Role & responsibilities AI Solution Development: Lead the development and enhancement of AI tools, including generative AI models, natural language processing (NLP) applications, and predictive analytics. Machine Learning & Deep Learning: Utilize supervised and unsupervised learning methods to address complex data science challenges. Apply advanced techniques, such as deep learning and neural networks, to optimize model performance. Data Engineering & Processing: Implement and improve data collection methods to ensure robust data pipelines. Focus on building systems that can efficiently process high volumes of data. Data Visualization: Design impactful visualizations using tools such as Power BI, making data insights accessible and actionable for stakeholders. Azure Open AI Expertise: Leverage Azures suite of AI tools, including LLMs and Custom Vision, for scalable, cloud-based deployment of AI solutions. Indexing & Document Optimization: Develop optimized indexing methods and document management strategies for high-volume data handling, especially within Azure Blob storage. Prompt Engineering: Apply prompt engineering techniques to improve the efficiency and accuracy of AI models, focusing on maximizing the effectiveness of LLM-based systems. Cross-functional Collaboration: Work with various teams to identify business challenges, translate them into data science projects, and implement data-driven solutions. Mentorship: Mentor junior data scientists, fostering an environment of growth and continuous learning. Preferred candidate profile Educational Background: Bachelors or Masters degree in computer science, Data Science, Engineering, or a related field. Experience: At least 9+ years of relevant experience in data science, with a focus on AI model deployment and application development in a cloud environment, specifically Azure Open AI with at least 2 of those years in a supervisory or leadership capacity. Technical Skills: Proficient in Python and SQL for data manipulation, model building, and analysis. o Extensive experience with large language models (LLMs) and RAG architecture. Advanced skills in machine learning algorithms, deep learning, and NLP. Familiarity with Azure Blob storage and optimization techniques for high-volume document processing. Strong data visualization abilities, with proficiency in tools such as Power BI, Tableau, or similar. Problem-Solving Skills: Strong analytical and debugging skills to identify, analyze, and solve complex data challenges. • Communication Skills: Ability to communicate complex technical concepts to non technical stakeholders effectively. If interested, Kindly revert with your updated resume at kritika_gupta@persolapac.com. Thanks & Regards Kritika Gupta Lead Consultant Persolkelly CONFIDENTIAL NOTE: By submitting your resume or personal data, you acknowledge reading and agreeing to our Privacy Policy . You hereby provide voluntary consent to the collection, use, processing, and disclosure of your data by us and our affiliates, in line with the Privacy Policy . and applicable laws. If you wish to withdraw your consent or have any concerns, you may submit a request to our designated consent manager, as outlined in our Privacy Policy . We prioritize your privacy. SECURITY NOTE: We at PERSOLKELLY India or our representatives, do not ask job seekers for fees, personal banking information, or payments through unofficial channels. Official communications will only come from @persolkelly.com. Report any suspicious activity to Contactus_in@persolkelly.com . Click here to find out how you can safeguard yourself from job scams.

Primine Software Private Limited is looking for Machine Learning Engineer to join our dynamic team and embark on a rewarding career journeyA Machine Learning Engineer is responsible for designing, building, and maintaining systems that use artificial intelligence (AI) and machine learning (ML) algorithms to solve complex problems. 1.Developing and implementing ML algorithms: The Machine Learning Engineer develops and implements machine learning algorithms to solve specific problems, such as natural language processing, computer vision, or predictive modeling.2.Building data pipelines: The Machine Learning Engineer is responsible for building data pipelines that collect, store, and preprocess data used in machine learning algorithms.3.Creating and maintaining ML infrastructure: The Machine Learning Engineer is responsible for creating and maintaining ML infrastructure, including hardware, software, and cloud platforms, that support the development and deployment of ML models.4.Testing and validating ML models: The Machine Learning Engineer tests and validates ML models, ensuring that they are accurate, robust, and scalable.5.Troubleshooting ML systems: The Machine Learning Engineer troubleshoots ML systems, identifying and resolving issues related to performance, accuracy, and scalability.6.Deploying ML models: The Machine Learning Engineer deploys ML models in production environments, integrating them with other software systems and ensuring that they are reliable and scalable.

Responsibilities: Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress. Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability. Determine and refine machine learning objectives. Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models. Transforming data science prototypes and applying appropriate ML algorithms and tools. Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world Ensuring that algorithms generate accurate user recommendations. Verifying data quality, and/or ensuring it via data cleaning. Supervising the data acquisition process if more data is needed. Defining validation strategies. Defining the pre-processing or feature engineering to be done on a given dataset Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks. Developing ML algorithms to analyze huge volumes of historical data to make predictions. Running tests, performing statistical analysis, and interpreting test results. Deploying models to production. Documenting machine learning processes. Keeping abreast of developments in machine learning. Preferred candidate profile Bachelor's degree in computer science, data science, mathematics, or a related field. Knowledge as a machine learning engineer. Proficiency with a deep learning framework such as TensorFlow, XgBoost, Wavevnet, Keras, numpy. Advanced proficiency with Python, Java, and R code writing. Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas. Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture in ANN, CNN, RNN with LSTM. Ability to select hardware to run an ML model with the required latency In-depth knowledge of mathematics, statistics, and algorithms. Superb analytical and problem-solving abilities. Great communication and collaboration skills. Excellent time management and organizational abilities. Benefits of working with OptimEyes 1 . Remote work opportunity ( work from home)2. Work opportunity with a top-notch team, cutting-edge technology, and leadership of extremely successful experts.3. Monthly Bonus along with Salary4. Yearly Bonus Role & responsibilities Preferred candidate profile Role & responsibilities Preferred candidate profile

Job Title: Sr. Data Scientist Location: Office-Based (Ahmedabad, India) About Hitech Hitech is a leading provider of Data, Engineering Services, and Business Process Solutions. With robust delivery centers in India and global sales offices in the USA, UK, and the Netherlands, we enable digital transformation for clients across industries including Manufacturing, Real Estate, and e-Commerce. Our Data Solutions practice integrates automation, digitalization, and outsourcing to deliver measurable business outcomes. As we continue expanding, were looking for a skilled Lead Data Scientist to guide innovation, lead teams, and solve complex problems using advanced analytics and machine learning. Position Summary As a Lead Data Scientist, you will lead a team of data scientists, machine learning engineers, and big data specialists to design, develop, and deploy data-driven solutions. You will be responsible for identifying business opportunities, translating them into data strategies, and driving measurable outcomes. This role demands strong leadership, deep technical expertise, and a passion for continuous innovation. Key Responsibilities Manage a team of data scientists, machine learning engineers, and big data specialists. Lead data mining, data collection, and cleansing procedures. Ensure high standards of data quality and integrity across all projects. Interpret complex data sets to identify patterns, trends, and actionable insights. Conceive, plan, and prioritize data science initiatives aligned with business goals. Develop and deploy scalable analytics systems and predictive models. Test and validate data-driven products for performance and reliability. Create compelling visualizations and comprehensive reports for stakeholders. Experiment with emerging models and machine learning techniques for innovation. Qualifications & Experience 6-8 years of working experience in Image Processing using deep learning frameworks such as OpenCV, PyTorch, TensorFlow, Theano, and Caffe. Experience in Text Analytics using NLP tools and techniques on unstructured data. Proven track record in building, deploying, and scaling statistical and deep learning models. Experience with large-scale data (structured and unstructured), data management, parallel computing, and distributed systems. Ability to thrive with minimal supervision in a dynamic, fast-paced environment. Capability to understand diverse business processes and quickly contextualize data requirements. Strong problem-solving skills to translate business problems into actionable data strategies. Excellent communication skills (verbal and written) with a learning and innovation mindset. Strong passion for leveraging AI/ML to solve business problems and a proactive approach to experimentation. Hands-on experience with exploratory data analysis, machine learning, and advanced analytics methods. What We Offer Competitive compensation based on skills and experience. Leadership role in building and scaling AI/ML initiatives. Opportunity to work on high-impact global projects with cutting-edge technologies. Continuous learning, innovation, and professional development support. A collaborative, inclusive, and tech-driven workplace environment. If you're passionate about driving innovation through data and leading a dynamic team to solve real-world problems, wed love to hear from you. Anand Soni Hitech Digital Solutions

Job Summary Qualifications: Education: Must have Bachelor's or Master's degree Good to have Artificial Intelligence, Data Science, or a related field Experience: 10+ years of experience in AI/ML development and 2+ years of experience in Architecture Proven experience designing and implementing scalable AI solutions in a cloud environment (e g , AWS, Azure, GCP) Strong understanding of various AI/ML algorithms, techniques, and frameworks Skills: Technical Expertise: Deep understanding of AI/ML algorithms Proficiency in programming languages such as Python, Java, etc , Experience with cloud platforms (e g , AWS, Azure, GCP) and their AI/ML services Knowledge of data engineering principles and tools Understanding of software development methodologies (e g , Agile, Scrum) Soft Skills: Strong analytical and problem-solving skills Excellent communication, presentation, and interpersonal skills Ability to work independently and as part of a team Ability to lead and mentor others Strategic thinking and business acumen Bonus Points: Certifications in cloud platforms (e g , AWS Certified Machine Learning Specialist, Azure AI Engineer Associate, Google Cloud Professional Machine Learning Engineer) Publications or presentations in the field of AI/ML Experience with specific industry verticals relevant to the company's business

Python and R for AI/ML Development, employing robust languages like JavaScript, HTML/CSS on the frontend, with a deep-seated expertise in Python and R on the backend, complemented by a practical exposure to Java backend Required Candidate profile Design, Devlop and deploy AI/ML models, machine learning algorithms using transformative principles of Artifical Intelligence, data analysis, manage datasets, employ machine learning alogorithms

Role Overview:As a Senior Principal Software Engineer, you will be a key technical leader responsible for shaping the design and development of scalable, reliable, and innovative AI/GenAI solutions. You will lead high priority projects, set technical direction for teams, and ensure alignment with organizational goals. Thisrole demands a high degree of technical expertise, strategic thinking, and the ability to collaborate effectively across diverse teams while mentoring and elevating others to meet a very high technical bar. Key Responsibilities: Strategic Technical Leadership : Define and drive the technical vision and roadmap for AI/GenAI systems, aligning with company objectives and future growth. Provide architectural leadership for complex, large-scale AI systems, ensuring scalability, performance, and maintainability. Act as a thought leader in AI technologies, influencing cross-functional technical decisions and long-term strategies. Advanced AI Product Development: Lead the development of state-of-the-art generative AI solutions, leveraging advanced techniques such as transformer models, diffusion models, and multi-modal architectures. Drive innovation by exploring and integrating emerging AI technologies and best practices. Mentorship & Team Growth: Mentor senior and junior engineers, fostering a culture of continuous learning and technical excellence. Elevate the team’s capabilities through coaching, training, and providing guidance on best practices and complex problem-solving. End-to-End Ownership: Take full ownership of high-impact projects, from ideation and design to implementation, deployment, and monitoring in production. Ensure the successful delivery of projects with a focus on quality, timelines, and alignment with organizational goals. Collaboration & Influence: Collaborate with cross-functional teams, including product managers, data scientists, and engineering leadership, to deliver cohesive and impactful solutions. Act as a trusted advisor to stakeholders, clearly articulating technical decisions and their business impact. Operational Excellence: Champion best practices for software development, CI/CD, and DevOps, ensuring robust and reliable systems. Monitor and improve the health of deployed services, conducting root cause analyses and driving preventive measures for long-term reliability. Innovation & Continuous Improvement: Advocate for and lead the adoption of new tools, frameworks, and methodologies to enhance team productivity and product capabilities. Stay at the forefront of AI/GenAI research, driving thought leadership and contributing to the AI community through publications or speaking engagements. Minimum Qualifications: Educational BackgroundBachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field; Ph.D. is preferred but not required. Experience10+ years of professional software development experience, including 5+ years in AI/ML or GenAI. Proven track record of designing and deploying scalable, production-grade AI solutions. Deep expertise in Python and frameworks such as TensorFlow, PyTorch, FastAPI, and LangChain. Advanced knowledge of AI/ML algorithms, generative models, and LLMs. Proficiency with cloud platforms (e.g., GCP, AWS, Azure) and modern DevOps practices. Strong understanding of distributed systems, microservices architecture, and database systems (SQL/NoSQL). Leadership Skills: Demonstrated ability to lead complex technical initiatives, influence cross functional teams, and mentor engineers at all levels. Problem-Solving Skills: Exceptional analytical and problem-solving skills, with a proven ability to navigate ambiguity and deliver impactful solutions. CollaborationExcellent communication and interpersonal skills, with the ability to engage and inspire both technical and non-technical stakeholders. Preferred Qualifications: AI/ML ExpertiseExperience with multi-modal models, reinforcement learning, and responsible AI principles. Cloud & InfrastructureAdvanced knowledge of GCP technologies such as VertexAI, BigQuery,GKE, and DataFlow. Thought LeadershipContributions to the AI/ML community through publications, open-source projects, or speaking engagements. Agile ExperienceFamiliarity with agile methodologies and working in a DevOps model. Disability Accommodation: UKGCareers@ukg.com.

Educational Bachelor of Engineering Service Line Quality Responsibilities Data Science Consultant with machine learning and Python experience. Knowledge on end-to-end architecture of Data Science and machine learning project. Experience in productionizing machine learning models and guide development team for implementing machine learning use cases. The candidate should provide technology consulting for defining right Data Science and ML use cases.Responsibilities: Data collection, profiling, EDA & data preparation AI Model development, tuning & validation Visualization tools (e.g., PowerBI, tableau) Present findings to business users & project management teams Propose ML based solution approaches and estimates for new use cases Contribute to AI based modules in Infosys solutions development Explore new advances in AI continuously and execute PoCs Mentoringguide other team members ML algorithms AI domainsNLP, speech, computer vision Supervised, Unsupervised, Reinforcement learning Tools for data analysis, auto ML, model deployment and scaling Knowledge of datasets ProgrammingPython Databases Knowledge of cloud platforms Azure/AWS/GCP. Preferred Skills: Technology-Artificial Intelligence-Artificial Intelligence - ALL

Educational Bachelor of Engineering Service Line AI & Automation Service Line Responsibilities Technical skills ProgrammingPython, R, SQL ML algorithms Statistical ML algorithms Deep Neural Network architectures Model ensembling Generative AI models ML for Responsible AI AI domains - NLP, speech, computer vision, structured data Learning patterns – supervised, unsupervised, reinforcement learning Tools for data analysis, auto ML, model deployment & scaling, model fine tuning Knowledge of different Model fine tuning approaches for Large models Knowledge of datasets, pre-built models available in open community and 3rd party providers Knowledge of software development & architectures Knowledge of hyperscalers & their AI capabilities – Azure, AWS, GCP Knowledge of Model Quantization and Pruning Past experience playing a Data Scientist role Technical and Professional : Technical skills ProgrammingPython, R, SQL ML algorithms Statistical ML algorithms Deep Neural Network architectures Model ensembling Generative AI models ML for Responsible AI AI domains - NLP, speech, computer vision, structured data Learning patterns – supervised, unsupervised, reinforcement learning Tools for data analysis, auto ML, model deployment & scaling, model fine tuning Knowledge of different Model fine tuning approaches for Large models Knowledge of datasets, pre-built models available in open community and 3rd party providers Knowledge of software development & architectures Knowledge of hyperscalers & their AI capabilities – Azure, AWS, GCP Knowledge of Model Quantization and Pruning Past experience playing a Data Scientist role Preferred Skills: Technology-Machine learning-data science Technology-Machine Learning-Python Technology-Machine Learning-Generative AI

Educational Bachelor of Engineering Service Line AI & Automation Service Line Responsibilities Technical skills ProgrammingPython, R, SQL ML algorithms Statistical ML algorithms Deep Neural Network architectures Model ensembling Generative AI models ML for Responsible AI AI domains - NLP, speech, computer vision, structured data Learning patterns – supervised, unsupervised, reinforcement learning Tools for data analysis, auto ML, model deployment & scaling, model fine tuning Knowledge of different Model fine tuning approaches for Large models Knowledge of datasets, pre-built models available in open community and 3rd party providers Knowledge of software development & architectures Knowledge of hyperscalers & their AI capabilities – Azure, AWS, GCP Knowledge of Model Quantization and Pruning Past experience playing a Data Scientist role Technical and Professional : Technical skills ProgrammingPython, R, SQL ML algorithms Statistical ML algorithms Deep Neural Network architectures Model ensembling Generative AI models ML for Responsible AI AI domains - NLP, speech, computer vision, structured data Learning patterns – supervised, unsupervised, reinforcement learning Tools for data analysis, auto ML, model deployment & scaling, model fine tuning Knowledge of different Model fine tuning approaches for Large models Knowledge of datasets, pre-built models available in open community and 3rd party providers Knowledge of software development & architectures Knowledge of hyperscalers & their AI capabilities – Azure, AWS, GCP Knowledge of Model Quantization and Pruning Past experience playing a Data Scientist role Preferred Skills: Technology-Machine learning-data science Technology-Machine Learning-Python Technology-Machine Learning-Generative AI

Job Description: We are seeking a highly skilled and experienced Senior Machine Learning Developer to join our dynamic team. The ideal candidate will have a strong background in machine learning (ML), deep learning (DL), and large language models (LLMs). They should be proficient in Python and possess expertise in conventional ML algorithms, DL techniques, LLM and prompt engineering. Desire Skills 1. RAG-Based Domain-Specific Q&A System Should have built a chatbot that answers questions from custom documents (e.g., legal contracts, company policies) using LLM + Vector DB (RAG). 2. Agentic AI Workflow Assistant (Multi-Step Planner) Should have created an LLM agent that performs tasks like Book my flight + hotel + calendar block” via API tools using LangGraph or AutoGen. 3. Multimodal RAG for Image + Text Search Worked on system that allows users to ask questions like “Find me the slide where person X talks about success in life” in a YouTube video or PDF deck. 4. Document Parsing Using OCR + Transformers Extract structured data from messy PDFs using Tesseract + LayoutLM or Donut Responsibilities: Machine Learning Development: Design, develop, and implement ML models and algorithms to solve complex problems. Work on various ML projects involving data preprocessing, feature engineering, model selection, and evaluation. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Deep Learning: Develop and deploy DL models using frameworks like TensorFlow, PyTorch, or Keras. Optimize DL models for performance and scalability. Stay updated with the latest advancements in DL and apply them to improve existing models. Large Language Models: Develop and fine-tune large language models for various NLP tasks. Implement prompt engineering techniques to enhance model performance and accuracy. Experiment with state-of-the-art LLM architectures and methodologies. Software Development: Write clean, maintainable, and efficient code in Python. Conduct code reviews and ensure adherence to best practices and coding standards. Implement version control using Git and collaborate with the development team through GitHub or similar platforms. Data Handling: Work with large datasets and perform data preprocessing, cleaning, and augmentation. Implement data pipelines and ensure data integrity and quality throughout the ML lifecycle. Research and Innovation: Stay abreast of the latest research and developments in the field of ML, DL, and LLMs. Propose and explore innovative solutions to improve model performance and address new challenges. Mentorship: Mentor and guide junior ML engineers and team members. Share knowledge and best practices within the team to foster a collaborative and learning environment.

The Role and Responsibilities We have open positions ranging from Data Scientist to Director, providing talented and motivated professionals with excellent career and growth opportunities. We seek individuals with relevant prior experience in quantitatively intense areas to join our team. Youll be working with varied and diverse teams to deliver unique and unprecedented solutions across all industries. In the data scientist track, you will be primarily responsible for managing and delivering analytics projects and helping teams design analytics solutions and models that consistently drive scalable high-quality solutions. Your responsibilities will include Working alongside Oliver Wyman consulting teams and partners, engaging directly with global clients to understand their business challenges Exploring large-scale data and crafting models to answer core business problems Working with partners and principals to shape proposals that showcase our data science and analytics capabilities Explaining, refining, and crafting model insights and architecture to guide stakeholders through the journey of model building Advocating best practices in modelling and code hygiene Leading the development of proprietary statistical techniques, ML algorithms, assets, and analytical tools on varied projects Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them Keeping up with emerging state-of-the-art modelling and data science techniques in your domain Your Attributes, Experience & Qualifications Bachelor's or Masters degree in a quantitative discipline from a top academic program (Data Science, Mathematics, Statistics, Computer Science, Informatics, and Engineering) Prior experience in data science, machine learning, and analytics Passion for problem-solving through big-data and analytics Pragmatic and methodical approach to solutions and delivery with a focus on impact Independent worker with the ability to manage workload and meet deadlines in a fast-paced environment Impactful presentation skills that succinctly and efficiently convey findings, results, strategic insights, and implications Excellent verbal and written communication skills and complete command of English Willingness to travel Collaborative team player Respect for confidentiality Technical Background Proficiency in modern programming languages (Python is mandatory; SQL, R, SAS desired) and machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Prior experience in designing and deploying large-scale technical solutions leveraging analytics Solid foundational knowledge of the mathematical and statistical principles of data science Familiarity with cloud storage, handling big data, and computational frameworks Valued but not required: Compelling side projects or contributions to the Open-Source community Experience presenting at data science conferences and connections within the data science community Interest/background in Financial Services in particular, as well as other sectors where Oliver Wyman has a strategic presence

The Role and Responsibilities We have open positions ranging from Associate Data Scientist to Director, providing talented and motivated professionals with excellent career and growth opportunities. We seek individuals with relevant prior experience in quantitatively intense areas to join our team. Youll be working with varied and diverse teams to deliver unique and unprecedented solutions across all industries. In the data scientist track, you will be primarily responsible for managing and delivering analytics projects and helping teams design analytics solutions and models that consistently drive scalable high-quality solutions. Your responsibilities will include Working alongside Oliver Wyman consulting teams and partners, engaging directly with global clients to understand their business challenges Exploring large-scale data and crafting models to answer core business problems Working with partners and principals to shape proposals that showcase our data science and analytics capabilities Explaining, refining, and crafting model insights and architecture to guide stakeholders through the journey of model building Advocating best practices in modelling and code hygiene Leading the development of proprietary statistical techniques, ML algorithms, assets, and analytical tools on varied projects Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them Keeping up with emerging state-of-the-art modelling and data science techniques in your domain Your Attributes, Experience & Qualifications Bachelor's or Masters degree in a quantitative discipline from a top academic program (Data Science, Mathematics, Statistics, Computer Science, Informatics, and Engineering) Prior experience in data science, machine learning, and analytics Passion for problem-solving through big-data and analytics Pragmatic and methodical approach to solutions and delivery with a focus on impact Independent worker with the ability to manage workload and meet deadlines in a fast-paced environment Impactful presentation skills that succinctly and efficiently convey findings, results, strategic insights, and implications Excellent verbal and written communication skills and complete command of English Willingness to travel Collaborative team player Respect for confidentiality Technical Background Proficiency in modern programming languages (Python is mandatory; SQL, R, SAS desired) and machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Prior experience in designing and deploying large-scale technical solutions leveraging analytics Solid foundational knowledge of the mathematical and statistical principles of data science Familiarity with cloud storage, handling big data, and computational frameworks Valued but not required: Compelling side projects or contributions to the Open-Source community Experience presenting at data science conferences and connections within the data science community Interest/background in Financial Services in particular, as well as other sectors where Oliver Wyman has a strategic presence

description 5+ years with Azure (ML pipeline components), Azure Databricks, Azure DevOps. Proven experience of design and deployment of end-to-end ML pipelines. Experience with building infrastructure for classic DS models and/or LLM/SLMs. 2+ years with orchestration (e.g., Kubeflow, Airflow, Azure Data Factory) and CI/CD for ML. Experience deploying containerized ML solutions (e.g. Docker/Kubernetes). Knowledge of model and data versioning (e.g. MLflow, DVC). Knowledge of MLSecOps (security in the context of MLOps) Experience with Infrastructure as a Code (e.g., Terraform, CloudFormation). Essential functions List of identified areas for improvements for existing PepsiCo project Recommendation on: MLOps practice MLSecOps Sample templates and pipelines Recommendation on the infrastructure for: Classic DS models LLM solution, primarily focused on fine tuning SLM by domain Recommendation on Data Strategy: JIT access to data for the period of training with security guardrails (access, data masking, etc.) Qualifications Azure Databricks, Azure DevOps. ML Ops ML SecOps Classic DS Model Would be a plus Knowledge of MLOps for LLM/SLM Experience in ML system/architecture design (load balancing, caching, failover). Knowledge in building scalable, resilient ML architectures. Cross-team collaboration experience (data science, engineering, DevOps). Experience with monitoring/logging for production models (e.g. Prometheus, Grafana, ELK stack).

Entity :- Accenture Strategy & Consulting Team :- Global Network Data & AI Practice :- AI Managed Services Title: - AI LLM Technology Architecture Consultant Role :- ML Engineering Consultant Job Location:- Hyderabad Accenture Global Network - Data & AI practice help our clients grow their business in entirely new ways.Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition As part of our Data & AI practice, you will join a worldwide network of smart and driven colleagues experienced in leading AI/ML/Statistical tools, methods and applications. From data to analytics and insights to actions, our forward-thinking consultants provide analytically-informed, issue-based insights at scale to help our clients improve outcomes and achieve high performance. WHATS IN IT FOR YOU An opportunity to work on high-visibility projects with top clients around the globe. Potential to Co-create with leaders in strategy, industry experts, enterprise function practitioners, and business intelligence professionals to shape and recommend innovative solutions that leverage emerging technologies. Ability to embed responsible business into everythingfrom how you service your clients to how you operate as a responsible professional. Personalized training modules to develop your strategy & consulting acumen to grow your skills, industry knowledge, and capabilities. Opportunity to thrive in a culture that is committed to accelerating equality for all. Engage in boundaryless collaboration across the entire organization. What you would do in this role Hands on experience on ML Services of AWS or Azure or Google. Develop, train, and deploy machine learning models for real-world applications. Design and implement data pipelines for model training and inference. Conduct model evaluation, testing, and validation to ensure robustness and accuracy. Work with large-scale datasets to build and improve predictive models. Optimize and fine-tune ML algorithms for performance, scalability, and efficiency. Collaborate with data scientists, software engineers, and product teams to integrate ML solutions into production systems. Stay up-to-date with the latest trends and advancements in machine learning and AI. Write clean, maintainable, and well-documented code. Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law. Qualification Who are we looking for Bachelors or Masters degree in any engineering stream or MCA. Experience/Education on Statistics, Data Science, Applied Mathematics, Business Analytics, Computer Science, Information Systems is preferable. Proven experience (5+ years) in working as per the above job description is required. Exposure to Retail, Banking, Healthcare projects is added advantage. Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. Strong understanding of algorithms, statistical modeling, and data structures. Experience with cloud platforms (AWS, GCP, Azure) and ML deployment tools (Docker, Kubernetes, MLflow, etc.). Knowledge of SQL and NoSQL databases for data handling. Familiarity with MLOps best practices for continuous integration and deployment of ML models. Excellent problem-solving skills and ability to work in a collaborative team environment. Ability to solve complex business problems and deliver client delight. Strong writing skills to build points of view on current industry trends. Good Client handling skills; able to demonstrate thought leadership & problem-solving skills.

: Kotak811 is a completely digital, in-your-phone, mobile bank. It was founded in 2016 to help India adapt, evolve, and eventually overcome the barrier of digital banking and make it accessible to all. Our sole aim is to bring you the excitement and ease of digital banking with the trust and reassurance of Kotak Mahindra Bank’s experience and legacy. Incubated by Kotak Mahindra Bank, Kotak811 is where innovation meets banking to offer the user the most seamless banking experience there has ever been. (Kotak 811 is a digital zero balance savings account that can be opened online by everyone (Indian residents only) which acts as a one-stop solution for all your financial needs and day to-day transactions.) Equal Employment OpportunityAll employment decisions shall be made without regard to age, race, creed, colour, religion, sex, national origin, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by the state, or local law. Kotak 811, is committed to providing equal employment opportunities RoleData Scientist 2 Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 1- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 2- Have worked across end to end in model design, development, validation, documentation & deployment. 3- Create great data stories with expertise in robust EDA and statistical inference

Should have knowledge in the regression and classification algorithm such as but not limited to Gradient Decent , Linear Regression , RandonForest , Support Vector Machine , K-nearest , Neural Networks DBSCAN , Principal Component Analysis , LDA and Autoencoders , Loss minimization function such as MSE , RMSE , Hinge Loss ect. We are seeking a data science or machine learning professional with strong expertise in both regression and classification algorithms. The ideal candidate should have hands-on experience with a wide range of techniques including, but not limited to: Supervised Learning Algorithms : Gradient Descent, Linear Regression, Random Forest, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), and Neural Networks. Unsupervised Learning Techniques : DBSCAN, Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Autoencoders. Loss Functions and Optimization : Proficient in implementing and optimizing loss functions such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Hinge Loss for model performance improvement.

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Google Cloud Platform Architecture Good to have skills : Google Cloud Machine Learning ServicesMinimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI/ML lead, you will be responsible for developing applications and systems that utilize AI tools and Cloud AI services. Your typical day will involve applying CCAI and Gen AI models as part of the solution, utilizing deep learning, neural networks and chatbots. Should have hands-on experience in creating, deploying, and optimizing chatbots and voice applications using Google Conversational Agents and other tools. Roles & Responsibilities:- Solutioning and designing CCAI applications and systems utilizing Google Cloud Machine Learning Services, dialogue flow CX, agent assist, conversational AI.- Design, develop, and maintain intelligent chatbots and voice applications using Google Dialogflow CX.- Integrate Dialogflow agents with various platforms, such as Google Assistant, Facebook Messenger, Slack, and websites. Hands-on experience with IVR integration and telephony systems such as Twilio, Genesys, Avaya- Integrate with IVR systems and Proficiency in webhook setup and API integration.- Develop Dialogflow CX - flows, pages, webhook as well as playbook and integration of tool into playbooks.- Creation of agents in Agent builder and integrating them into end end to pipeline using python.- Apply GenAI-Vertex AI models as part of the solution, utilizing deep learning, neural networks, chatbots, and image processing.- Work with Google Vertex AI for building, training and deploying custom AI models to enhance chatbot capabilities- Implement and integrate backend services (using Google Cloud Functions or other APIs) to fulfill user queries and actions.- Document technical designs, processes, and setup for various integrations.- Experience with programming languages such as Python/Node.js Professional & Technical Skills: - Must Have Skills: CCAI/Dialogflow CX hands on experience and generative AI understanding.- Good To Have Skills: Cloud Data Architecture, Cloud ML/PCA/PDE Certification, - Strong understanding of AI/ML algorithms, NLP and techniques.- Experience with chatbot, generative AI models, prompt Engineering.- Experience with cloud or on-prem application pipeline with production-ready quality. Additional Information:- The candidate should have a minimum of 10 years of experience in Google Cloud Machine Learning Services/Gen AI/Vertex AI/CCAI.- The ideal candidate will possess a strong educational background in computer science, mathematics, or a related field, along with a proven track record of delivering impactful data-driven solutions.- A 15-year full time education is required Qualification 15 years full time education

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Google Cloud Platform Architecture Good to have skills : Google Cloud Machine Learning ServicesMinimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI/ML technical lead, you will be responsible for developing applications and systems that utilize AI tools and Cloud AI services. Your typical day will involve applying CCAI and GenAI models as part of the solution, utilizing deep learning, neural networks and chatbots. Roles & Responsibilities:- Design and develop CCAI applications and systems utilizing Google Cloud Machine Learning Services, dialogue flow CX, agent assist.- Develop and implement chatbot solutions that integrate seamlessly with CCAI and other Cloud services- Integrate Dialogflow agents with various platforms, such as Google Assistant, Facebook Messenger, Slack, and websites. Hands-on experience with IVR integration and telephony systems such as Twilio, Genesys, Avaya- Integrate with IVR systems and Proficiency in webhook setup and API integration.- Develop Dialogflow CX - flows, pages, webhook as well as playbook and integration of tool into playbooks.- Creation of agents in Agent builder and integrating them into end end to pipeline using python.- Apply GenAI-Vertex AI models as part of the solution, utilizing deep learning, neural networks, chatbots, and image processing.- Work with Google Vertex AI for building, training and deploying custom AI models to enhance chatbot capabilities- Implement and integrate backend services (using Google Cloud Functions or other APIs) to fulfill user queries and actions.- Document technical designs, processes, and setup for various integrations.- Experience with programming languages such as Python/Node.js Professional & Technical Skills: - Must To Have Skills: CCAI/Dialogflow CX hands on experience and generative AI understanding.- Good To Have Skills: Cloud Data Architecture, Cloud ML/PCA/PDE Certification, - Strong understanding of AI/ML algorithms and techniques.- Experience with chatbot , generative AI models, prompt Engineering- Experience with cloud or on-prem application pipeline with production-ready quality. Additional Information:- The candidate should have a minimum of 5 years of experience in Google Cloud Machine Learning Services/Gen AI/Vertex AI/CCAI.- The ideal candidate will possess a strong educational background in computer science, mathematics, or a related field, along with a proven track record of delivering impactful data-driven solutions.- A 15-year full time education is required Qualification 15 years full time education

Project Role : Technology Architect Project Role Description : Design and deliver technology architecture for a platform, product, or engagement. Define solutions to meet performance, capability, and scalability needs. Must have skills : Google Cloud Platform Architecture Good to have skills : Google Cloud Machine Learning ServicesMinimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI/ML lead, you will be responsible for developing applications and systems that utilize AI tools and Cloud AI services. Your typical day will involve applying CCAI and Gen AI models as part of the solution, utilizing deep learning, neural networks and chatbots. Should have hands-on experience in creating, deploying, and optimizing chatbots and voice applications using Google Conversational Agents and other tools. Roles & Responsibilities:I.Solutioning and designing CCAI applications and systems utilizing Google Cloud Machine Learning Services, dialogue flow CX, agent assist, conversational AI.II.Design, develop, and maintain intelligent chatbots and voice applications using Google Dialogflow CX.III.Integrate Dialogflow agents with various platforms, such as Google Assistant, Facebook Messenger, Slack, and websites. Hands-on experience with IVR integration and telephony systems such as Twilio, Genesys, AvayaIV.Integrate with IVR systems and Proficiency in webhook setup and API integration.V.Develop Dialogflow CX - flows, pages, webhook as well as playbook and integration of tool into playbooks.VI.Creation of agents in Agent builder and integrating them into end end to pipeline using python.VII.Apply GenAI-Vertex AI models as part of the solution, utilizing deep learning, neural networks, chatbots, and image processing.VIII.Work with Google Vertex AI for building, training and deploying custom AI models to enhance chatbot capabilitiesIX.Implement and integrate backend services (using Google Cloud Functions or other APIs) to fulfill user queries and actions.X.Document technical designs, processes, and setup for various integrations.XI.Experience with programming languages such as Python/Node.js Professional & Technical Skills: - Must To Have Skills: CCAI/Dialogflow CX hands on experience and generative AI understanding.- Good To Have Skills: Cloud Data Architecture, Cloud ML/PCA/PDE Certification, - Strong understanding of AI/ML algorithms, NLP and techniques.- Experience with chatbot , generative AI models, prompt Engineering.- Experience with cloud or on-prem application pipeline with production-ready quality. Additional Information:1 The candidate should have a minimum of 10 years of experience in Google Cloud Machine Learning Services/Gen AI/Vertex AI/CCAI.2 The ideal candidate will possess a strong educational background in computer science, mathematics, or a related field, along with a proven track record of delivering impactful data-driven solutions. Qualification 15 years full time education

Project Role : Data Architect Project Role Description : Define the data requirements and structure for the application. Model and design the application data structure, storage and integration. Must have skills : Google Cloud Platform Architecture Good to have skills : Google Cloud Machine Learning ServicesMinimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :We are seeking a highly skilled and visionary AI/ML Manager to lead the development of advanced AI-driven applications and solutions using Google Cloud's Conversational AI (CCAI) platform and Gen AI models. In this role, you will architect, design, and deploy scalable AI solutions that leverage deep learning, neural networks, and advanced chatbot/voice bot technologies. You should have strong hands-on experience in building and optimizing conversational experiences using Google Dialogflow CX, Agent Assist, and other Google Cloud AI services. Roles & Responsibilities:- Lead end-to-end solutioning, design, and implementation of AI/ML-powered applications using Google CCAI tools and GCP services.- Architect scalable conversational AI solutions including chatbots and voice bots using Dialogflow CX, Agent Assist, and Gen AI APIs.- Collaborate with cross-functional teams including UX, data science, and engineering to deliver impactful AI products.- Drive innovation by integrating advanced models such as LLMs, NLP, and neural networks to elevate conversational capabilities.- Oversee performance tuning, testing, and optimization of AI solutions in real-world production environments.- Stay current with Google AI/ML advancements and incorporate best practices into the solution lifecycle.- Proven experience in designing and deploying AI/ML and conversational AI systems on Google Cloud Platform.- Expertise in Dialogflow CX, Agent Assist, and other CCAI tools.- Solid understanding of Gen AI technologies, NLP techniques, and machine learning frameworks.- Strong architecture and solution design experience within GCP ecosystem.- Hands-on experience in building and optimizing production-ready chatbots and voice applications.- Excellent problem-solving, communication, and leadership skills.- Experience with programming languages such as Python/Node.js Professional & Technical Skills: Must To Have Skills: CCAI/Dialogflow CX hands on experience and generative AI understanding.Good To Have Skills: Cloud Data Architecture, Cloud ML/PCA/PDE Certification, Strong understanding of AI/ML algorithms, NLP and techniques. Experience with chatbot, generative AI models, prompt Engineering.Experience with cloud or on-prem application pipeline with production-ready quality. Additional Information:- The candidate should have a minimum of 15+ years of experience in Google Cloud Machine Learning Services/Gen AI/Vertex AI/CCAI.- The ideal candidate will possess a strong educational background in computer science, mathematics, or a related field, along with a proven track record of delivering impactful data-driven solutions.- A 15 year full time education is required Qualification 15 years full time education

Project Role : Technology Architect Project Role Description : Design and deliver technology architecture for a platform, product, or engagement. Define solutions to meet performance, capability, and scalability needs. Must have skills : Google Cloud Platform Architecture Good to have skills : Google Cloud Machine Learning ServicesMinimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI/ML lead, you will be responsible for developing applications and systems that utilize AI tools and Cloud AI services. Your typical day will involve applying CCAI and Gen AI models as part of the solution, utilizing deep learning, neural networks and chatbots. Should have hands-on experience in creating, deploying, and optimizing chatbots and voice applications using Google Conversational Agents and other tools. Roles & Responsibilities:I.Solutioning and designing CCAI applications and systems utilizing Google Cloud Machine Learning Services, dialogue flow CX, agent assist, conversational AI.II.Design, develop, and maintain intelligent chatbots and voice applications using Google Dialogflow CX.III.Integrate Dialogflow agents with various platforms, such as Google Assistant, Facebook Messenger, Slack, and websites. Hands-on experience with IVR integration and telephony systems such as Twilio, Genesys, AvayaIV.Integrate with IVR systems and Proficiency in webhook setup and API integration.V.Develop Dialogflow CX - flows, pages, webhook as well as playbook and integration of tool into playbooks.VI.Creation of agents in Agent builder and integrating them into end end to pipeline using python.VII.Apply GenAI-Vertex AI models as part of the solution, utilizing deep learning, neural networks, chatbots, and image processing.VIII.Work with Google Vertex AI for building, training and deploying custom AI models to enhance chatbot capabilitiesIX.Implement and integrate backend services (using Google Cloud Functions or other APIs) to fulfill user queries and actions.X.Document technical designs, processes, and setup for various integrations.XI.Experience with programming languages such as Python/Node.js Professional & Technical Skills: - Must To Have Skills: CCAI/Dialogflow CX hands on experience and generative AI understanding.- Good To Have Skills: Cloud Data Architecture, Cloud ML/PCA/PDE Certification, - Strong understanding of AI/ML algorithms, NLP and techniques.- Experience with chatbot , generative AI models, prompt Engineering.- Experience with cloud or on-prem application pipeline with production-ready quality. Additional Information:I.The candidate should have a minimum of 10 years of experience in Google Cloud Machine Learning Services/Gen AI/Vertex AI/CCAI.II.The ideal candidate will possess a strong educational background in computer science, mathematics, or a related field, along with a proven track record of delivering impactful data-driven solutions. Qualification 15 years full time education

Project Role : Data Platform Architect Project Role Description : Architects the data platform blueprint and implements the design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models. Must have skills : Google Cloud Platform Architecture Good to have skills : Google Cloud Machine Learning ServicesMinimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI/ML lead, you will be responsible for developing applications and systems that utilize AI tools and Cloud AI services. Your typical day will involve applying CCAI and Gen AI models as part of the solution, utilizing deep learning, neural networks and chatbots. Should have hands-on experience in creating, deploying, and optimizing chatbots and voice applications using Google Conversational Agents and other tools. Roles & Responsibilities:- Solutioning and designing CCAI applications and systems utilizing Google Cloud Machine Learning Services, dialogue flow CX, agent assist, conversational AI.- Design, develop, and maintain intelligent chatbots and voice applications using Google Dialogflow CX.- Integrate Dialogflow agents with various platforms, such as Google Assistant, Facebook Messenger, Slack, and websites. Hands-on experience with IVR integration and telephony systems such as Twilio, Genesys, Avaya- Integrate with IVR systems and Proficiency in webhook setup and API integration.- Develop Dialogflow CX - flows, pages, webhook as well as playbook and integration of tool into playbooks.- Creation of agents in Agent builder and integrating them into end end to pipeline using python.- Apply GenAI-Vertex AI models as part of the solution, utilizing deep learning, neural networks, chatbots, and image processing.- Work with Google Vertex AI for building, training and deploying custom AI models to enhance chatbot capabilities- Implement and integrate backend services (using Google Cloud Functions or other APIs) to fulfill user queries and actions.- Document technical designs, processes, and setup for various integrations.- Experience with programming languages such as Python/Node.js Professional & Technical Skills: - Must To Have Skills: CCAI/Dialogflow CX hands on experience and generative AI understanding.- Good To Have Skills: Cloud Data Architecture, Cloud ML/PCA/PDE Certification, - Strong understanding of AI/ML algorithms, NLP and techniques.- Experience with chatbot , generative AI models, prompt Engineering.- Experience with cloud or on-prem application pipeline with production-ready quality. Additional Information:- The candidate should have a minimum of 10 years of experience in Google Cloud Machine Learning Services/Gen AI/Vertex AI/CCAI.- The ideal candidate will possess a strong educational background in computer science, mathematics, or a related field, along with a proven track record of delivering impactful data-driven solutions.- A 15-year full time education is required Qualification 15 years full time education