1112 Keras Jobs - Page 10

This role is for one of Weekday's clients Min Experience: 4 years JobType: full-time Requirements About the Role: We are looking for a skilled and driven Python Fullstack Developer to join our high-performing development team. In this role, you will be responsible for designing, developing, and maintaining end-to-end solutions with a strong emphasis on backend development and API integration. The ideal candidate should have deep expertise in Python along with experience in RESTful API development and proficiency in modern data science libraries such as NumPy , Pandas , TensorFlow , Keras , and Scikit-learn . As part of a dynamic product development team, you will play a key role in building scalable, reliable applications and intelligent systems that leverage machine learning and data-driven insights. You will also collaborate closely with front-end developers, data scientists, and DevOps engineers to deliver seamless user experiences and high-performance APIs. Key Responsibilities: Develop and maintain Python-based backend services, including the creation and management of RESTful APIs to serve front-end and client applications. Work closely with data scientists to integrate AI/ML models using frameworks like TensorFlow and Keras into production environments. Build robust and scalable data processing pipelines using libraries like NumPy, Pandas, and Scikit-learn. Design and implement full-stack solutions with clean, maintainable, and testable code. Optimize API performance and ensure secure and efficient data exchange between front-end and backend systems. Contribute to database schema design and optimize database queries for performance and scalability. Participate in code reviews, debugging, and troubleshooting across the stack. Collaborate with cross-functional teams including front-end developers, DevOps, and product managers to define and execute project deliverables. Stay up-to-date with industry trends and emerging technologies to ensure that our solutions are cutting-edge and competitive. Required Skills and Qualifications: 4+ years of experience as a Python Developer, with proven experience in fullstack or backend roles. Strong understanding of RESTful API design and best practices. Proficiency in Python, with in-depth knowledge of libraries such as NumPy, Pandas, TensorFlow, Keras, and Scikit-learn. Experience in developing applications that integrate data science models into production-grade systems. Familiarity with front-end technologies (HTML, CSS, JavaScript, React or similar frameworks) is a plus. Solid experience with version control tools such as Git and development workflows like Agile/Scrum. Experience working with cloud platforms such as AWS, Azure, or GCP is an advantage. Strong problem-solving skills and the ability to work independently and in a team environment. Excellent communication skills and a passion for building high-quality software.

We are on the hunt for a Lead Artificial Intelligence (AI) passionate about architecting, developing, and supporting advanced AI computing resources and AI-enabled services. The ideal candidate will lead the charge in implementing scalable, high-performance computing infrastructures for AI/ML, collaborating with cross-functional teams to bring innovative AI solutions from conception to deployment. Roles & Responsibilities Architect, design, and implement scalable AI/ML computing infrastructures and application stacks. Collaborate with project managers, analyst & business stakeholders to design and deploy AI solutions. Develop and demonstrate AI use-cases, conducting training sessions to foster AI adoption. Evaluate and implement best practices in AI/ML and analytics. Document architecture roadmaps, reference architectures, and standard operating procedures for AI solutions. Provide expert consultation on AI-related standards, best practices, and governance frameworks. Lead disaster recovery and business continuity planning for AI computing infrastructure. Stay updated with emerging technologies in AI and ML to enhance institutional capabilities. Eligibility Criteria Master’s degree in Computer Science or Data Science or Information Technology, 6+ years in high-level architecture design and solution development for large-scale AI/ML systems. Extensive experience with deep learning frameworks (e.g., TensorFlow, Keras, PyTorch), time series analysis, predictive modelling, and NLP. Preferred Skillsets Expertise in predictive analytics, machine learning, deep learning architectures, and text analytics with NLP. Proficiency in Python for AI/ML; experience with graph databases, neural networks, and MLOps. Knowledge of high-performance AI computing platforms, Linux, and shell scripting in AI computing environments. Exceptional communication skills to articulate technical solutions to both technical and non-technical audiences. Strategic thinking in systems capacity planning, hardware and software updates, and migration.

S enior Fullstack AI/ML Engineer Location: Delhi Experience: 3-5 years Mode: On-site About the Role We are seeking a highly skilled Senior AI/ML Engineer to join our dynamic team. The ideal candidate will have extensive experience in designing, building, and deploying machine learning models and AI solutions to solve real-world business challenges. You will collaborate with cross-functional teams to create and integrate AI/ML models into end-to-end applications, ensuring models are accessible through APIs or product interfaces for real-time usage. Responsibilities Lead the design, development, and deployment of machine learning models for various use cases such as recommendation systems, computer vision, natural language processing (NLP), and predictive analytics. Work with large datasets to build, train, and optimize models using techniques such as classification, regression, clustering, and neural networks. Fine-tune pre-trained models and develop custom models based on specific business needs. Collaborate with data engineers to build scalable data pipelines and ensure the smooth integration of models into production. Collaborate with frontend/backend engineers to build AI-driven features into products or platforms. Build proof-of-concept or production-grade AI applications and tools with intuitive UIs or workflows. Ensure scalability and performance of deployed AI solutions within the full application stack. Implement model monitoring and maintenance strategies to ensure performance, accuracy, and continuous improvement of deployed models. Design and implement APIs or services that expose machine learning models to frontend or other systems Internal Utilize cloud platforms (AWS, GCP, Azure) to deploy, manage, and scale AI/ML solutions. Stay up-to-date with the latest advancements in AI/ML research, and apply innovative techniques to improve existing systems. Communicate effectively with stakeholders to understand business requirements and translate them into AI/ML-driven solutions. Document processes, methodologies, and results for future reference and reproducibility. Required Skills & Qualifications Experience: 5+ years of experience in AI/ML engineering roles, with a proven track record of successfully delivering machine learning projects. AI/ML Expertise: Strong knowledge of machine learning algorithms (supervised, unsupervised, reinforcement learning) and AI techniques, including NLP, computer vision, and recommendation systems. Programming Languages: Proficient in Python and relevant ML libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras. Data Manipulation: Experience with data manipulation libraries such as Pandas, NumPy, and SQL for managing and processing large datasets. Model Development: Expertise in building, training, deploying, and fine-tuning machine learning models in production environments. Cloud Platforms: Experience with cloud platforms such as AWS, GCP, or Azure for the deployment and scaling of AI/ML models. MLOps: Knowledge of MLOps practices for model versioning, automation, and monitoring. Data Preprocessing: Proficient in data cleaning, feature engineering, and preparing datasets for model training. Strong experience building and deploying end-to-end AI-powered applications— not just models but full system integration. Hands-on experience with Flask, FastAPI, Django, or similar for building REST APIs for model serving. Understanding of system design and software architecture for integrating AI into production environments. Experience with frontend/backend integration (basic React/Next.js knowledge is a plus). Demonstrated projects where AI models were part of deployed user-facing applications. Internal NLP & Computer Vision: Hands-on experience with natural language processing or computer vision projects. Big Data: Familiarity with big data tools and frameworks (e.g., Apache Spark, Hadoop) is an advantage. Problem-Solving Skills: Strong analytical and problem-solving abilities, with a focus on delivering practical AI/ML solutions. Nice to Have Experience with deep learning architectures (CNNs, RNNs, GANs, etc.) and techniques. Knowledge of deployment strategies for AI models using APIs, Docker, or Kubernetes. Experience building full-stack applications powered by AI (e.g., chatbots, recommendation dashboards, AI assistants, etc.). Experience deploying AI/ML models in real-time environments using API gateways, microservices, or orchestration tools like Docker and Kubernetes. Solid understanding of statistics and probability. Experience working in Agile development environments. What You'll Gain Be part of a forward-thinking team working on cutting-edge AI/ML technologies. Collaborate with a diverse, highly skilled team in a fast-paced environment. Opportunity to work on impactful projects with real-world applications. Competitive salary and career growth opportunities Job Type: Full-time Pay: ₹1,000,000.00 - ₹1,200,000.00 per year Schedule: Day shift Fixed shift Work Location: In person

AI and Machine Learning Intern Company: INLIGHN TECH Location: Remote (100% Virtual) Duration: 3 Months Stipend for Top Interns: ₹15,000 Certificate Provided | Letter of Recommendation | Full-Time Offer Based on Performance About the Company: INLIGHN TECH empowers students and fresh graduates with real-world experience through hands-on, project-driven internships. The AI and Machine Learning Internship is crafted to provide practical exposure to building intelligent systems, enabling interns to bridge theoretical knowledge with real-world applications. Role Overview: As an AI and Machine Learning Intern, you will work on projects involving data preprocessing, model development, and performance evaluation. This internship will strengthen your skills in algorithm design, model optimization, and deploying AI solutions to solve real-world problems. Key Responsibilities: Collect, clean, and preprocess datasets for training machine learning models Implement machine learning algorithms for classification, regression, and clustering Develop deep learning models using frameworks like TensorFlow or PyTorch Evaluate model performance using metrics such as accuracy, precision, and recall Collaborate on AI-driven projects, such as chatbots, recommendation engines, or prediction systems Document code, methodologies, and results for reproducibility and knowledge sharing Qualifications: Pursuing or recently completed a degree in Computer Science, Data Science, Artificial Intelligence, or a related field Strong foundation in Python and understanding of libraries such as Scikit-learn, NumPy, Pandas, and Matplotlib Familiarity with machine learning concepts like supervised and unsupervised learning Experience or interest in deep learning frameworks (TensorFlow, Keras, PyTorch) Good problem-solving skills and a passion for AI innovation Eagerness to learn and contribute to real-world ML applications Internship Benefits: Hands-on experience with real-world AI and ML projects Certificate of Internship upon successful completion Letter of Recommendation for top performers Build a strong portfolio of AI models and machine learning solutions

We have Opening for + Frontend Skills + Generative AI with a Leading US Based (Product) IT Company. Work Mode: Permanent Remote Mandate Experience: Generative AI, VUE 3, Python, LLMs, AWS, AI Tools, HTML, CSS, & JavaScript. Experience: 5+ Years Responsibilities: Experience developing commercial application software with an emphasis on artificial intelligence and machine learning. Strong Python skills and familiarity with pertinent AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Keras). Familiarity with Large Language Models (LLMs), such as Claude from Anthropic, Google's Gemini, or OpenAI's GPT models. Familiarity with quick engineering methods to maximise LLM performance. Familiarity in web application development and API integration. Strong knowledge of cloud computing systems, such as Google Cloud, AWS, and Azure. Familiarity with orchestration tools like Kubernetes and containerisation technologies like Docker. Enthusiasm about generative AI and how it may revolutionise corporate procedures. Familiarity with AI-powered coding helpers such as GitHub Copilot, Replit, Cursor, or Windsurf by Codeium. Familiarity with testing and debugging tools powered by AI. Contributions to AI projects that are open source. Strong analytical and problem-solving abilities. Frontend Development Skills: Framework for component development: Web Components & Vue 2.x. Principle of application development: wiki, WYSIWYG. Markdown is the markup language. Language of the Template: Handlebars. YAML is the configuration language. JavaScript is the programming language. Web Socket, REST, and GraphQL are protocols for interacting with the backend. Qualifications: Bachelor's or master's degree in computer science, Artificial Intelligence, or a related field. Interested Candidates, Kindly Share CVs on Chandni@thepremierconsultants.com #GenerativeAI #ArtificialIntelligence #MachineLearning #DeepLearning #LargeLanguageModels #PromptEngineering #AIDevelopment #LLMApplications #AIInnovation#Python #TensorFlow #PyTorch #Keras #JavaScript #VueJS #WebComponents #APIDevelopment #Docker #Kubernetes #CloudComputing #AWS #Azure #GoogleCloud #YAML #Markdown #Handlebars #GraphQL #RESTAPI #WebSockets#GitHubCopilot #Codeium #Replit #AIAssistedDevelopment #AIForDevelopers

Job Title AI Engineer - I/II Job Description Your role: Experience in developing NLP algorithms, AI based Computer Vision applications Experience in NLP techniques for text representation (such as n-grams, bag of words, sentiment analysis etc), semantic extraction techniques, data structures and modeling Experience in using GenAI techniques like Auto encoders, Transformers, LLMs, RAG Architecture Experience and understanding of MLOps, AI algorithm inferencing and deployments on the Cloud (AWS, Azure or GCP) Excellent understanding of machine learning techniques and algorithms like k-NN, SVM, Random Forest, privacy models, etc. Experience in CV based Deep Learning models like Unet, YOLO etc Understanding exploratory data processing techniques such as cleaning and verifying the integrity of data used for analysis Understanding of state-of-the-art computer vision, NLP and AI for imaging algorithms You're the right fit if: 7-10 years experience in AI and Data Science field Master's in computers, electronics, electrical engineering or PhD in relevant streams Good applied statistics skills, such as distributions, statistical testing, regression, etc. Experience in building and optimizing reactive and predictive models with Machine Learning techniques Experience with one or more analytic software tools or languages like Python, R Experience with machine learning frameworks, like Keras or PyTorch and Deep Learning based libraries for imaging Strong analytical, problem solving and communication skills How We Work Together We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week. this role is an office role. About Philips We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others. Learn more about our business. Discover our rich and exciting history. Learn more about our purpose. If you’re interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our culture of impact with care here.

Develop and deploy advanced AI solutions using the latest Generative AI techniques including: - Retrieval-Augmented Generation (RAG) pipelines. - Designing and building Agentic AI systems to automate complex decision-making workflows. - Fine-tuning Foundation and Small Language Models (SLMs) tailored for domain specific content

S enior Fullstack AI/ML Engineer Location: Delhi Experience: 3-5 years Mode: On-site About the Role We are seeking a highly skilled Senior AI/ML Engineer to join our dynamic team. The ideal candidate will have extensive experience in designing, building, and deploying machine learning models and AI solutions to solve real-world business challenges. You will collaborate with cross-functional teams to create and integrate AI/ML models into end-to-end applications, ensuring models are accessible through APIs or product interfaces for real-time usage. Responsibilities Lead the design, development, and deployment of machine learning models for various use cases such as recommendation systems, computer vision, natural language processing (NLP), and predictive analytics. Work with large datasets to build, train, and optimize models using techniques such as classification, regression, clustering, and neural networks. Fine-tune pre-trained models and develop custom models based on specific business needs. Collaborate with data engineers to build scalable data pipelines and ensure the smooth integration of models into production. Collaborate with frontend/backend engineers to build AI-driven features into products or platforms. Build proof-of-concept or production-grade AI applications and tools with intuitive UIs or workflows. Ensure scalability and performance of deployed AI solutions within the full application stack. Implement model monitoring and maintenance strategies to ensure performance, accuracy, and continuous improvement of deployed models. Design and implement APIs or services that expose machine learning models to frontend or other systems Internal Utilize cloud platforms (AWS, GCP, Azure) to deploy, manage, and scale AI/ML solutions. Stay up-to-date with the latest advancements in AI/ML research, and apply innovative techniques to improve existing systems. Communicate effectively with stakeholders to understand business requirements and translate them into AI/ML-driven solutions. Document processes, methodologies, and results for future reference and reproducibility. Required Skills & Qualifications Experience: 5+ years of experience in AI/ML engineering roles, with a proven track record of successfully delivering machine learning projects. AI/ML Expertise: Strong knowledge of machine learning algorithms (supervised, unsupervised, reinforcement learning) and AI techniques, including NLP, computer vision, and recommendation systems. Programming Languages: Proficient in Python and relevant ML libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras. Data Manipulation: Experience with data manipulation libraries such as Pandas, NumPy, and SQL for managing and processing large datasets. Model Development: Expertise in building, training, deploying, and fine-tuning machine learning models in production environments. Cloud Platforms: Experience with cloud platforms such as AWS, GCP, or Azure for the deployment and scaling of AI/ML models. MLOps: Knowledge of MLOps practices for model versioning, automation, and monitoring. Data Preprocessing: Proficient in data cleaning, feature engineering, and preparing datasets for model training. Strong experience building and deploying end-to-end AI-powered applications— not just models but full system integration. Hands-on experience with Flask, FastAPI, Django, or similar for building REST APIs for model serving. Understanding of system design and software architecture for integrating AI into production environments. Experience with frontend/backend integration (basic React/Next.js knowledge is a plus). Demonstrated projects where AI models were part of deployed user-facing applications. Internal NLP & Computer Vision: Hands-on experience with natural language processing or computer vision projects. Big Data: Familiarity with big data tools and frameworks (e.g., Apache Spark, Hadoop) is an advantage. Problem-Solving Skills: Strong analytical and problem-solving abilities, with a focus on delivering practical AI/ML solutions. Nice to Have Experience with deep learning architectures (CNNs, RNNs, GANs, etc.) and techniques. Knowledge of deployment strategies for AI models using APIs, Docker, or Kubernetes. Experience building full-stack applications powered by AI (e.g., chatbots, recommendation dashboards, AI assistants, etc.). Experience deploying AI/ML models in real-time environments using API gateways, microservices, or orchestration tools like Docker and Kubernetes. Solid understanding of statistics and probability. Experience working in Agile development environments. What You'll Gain Be part of a forward-thinking team working on cutting-edge AI/ML technologies. Collaborate with a diverse, highly skilled team in a fast-paced environment. Opportunity to work on impactful projects with real-world applications. Competitive salary and career growth opportunities Job Type: Full-time Pay: ₹1,000,000.00 - ₹1,200,000.00 per year Schedule: Day shift Fixed shift Work Location: In person

Company Overview At Motorola Solutions, we believe that everything starts with our people. We’re a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. Our critical communications, video security and command center technologies support public safety agencies and enterprises alike, enabling the coordination that’s critical for safer communities, safer schools, safer hospitals and safer businesses. Connect with a career that matters, and help us build a safer future. Department Overview The Design & Tools (D&T) team is a strategic component of Centralized Managed Support Operations (CMSO), responsible for providing exceptional Service Design & innovative technology solutions to enable and empower MSI Centralized Managed Support Operations to meet and exceed customer's expectations. In this role, you will fit in the AI & Architecture team within D&T. Job Description We are looking for a Senior Data Scientist who will also serve as a subject matter expert in the AI and ML domain, and build analytical and statistical machine learning models that will drive business decisions. In this role You will understand user requirements and translate them into AI solutions that turbocharge internal and external user experiences. Many of these AI solutions will be enabled within the core technologies used within CMSO, including Salesforce and ServiceNow. In other instances, you will also be responsible for building custom predictive and prescriptive ML models for preventative system health checks, system log analytics, automated root cause analysis etc. Responsibilities include: Drive requirements for AI related projects, work with internal customers and with ServiceNow and Salesforce Product Managers for features planning, prioritization and implementation Understand and apply various statistical methods for data analysis, EDA, hypothesis testing, and drawing meaningful conclusions. Apply GenAI, ML and DL concepts, NLP, computer vision, sentiment analysis, topic modeling and graph theory in real world applications to solve business problems Develop application-specific interfaces that leverage GenAI capabilities and LLMs to enhance the associate and customer experience. Design APIs for performance, real-time applications, scale, ease of use and governance automation. Leverage Python, PyTorch, NLTK etc. libraries and frameworks such as Langchain to build AI solutions. Training ML models to effectively communicate complex data insights through clear and informative visualizations Serves as thought leader in data science and applies deep expertise to drive novel customer experiences Adaptive and the desire to learn new technologies. Technical Experience Extensive knowledge of AI supervised, unsupervised and reinforcement methods, GenAI LLM and Python libraries to perform data analysis, building advanced machine learning models and data integrations with source systems and systems of record Experience with common data science tools such as Python, R, PyTorch, TensorFlow, Keras, NLTK, or spaCy Very good knowledge and experience with Databases like Postgres, Redshift, MSSQL Knowledge and experience in Cloud Environments (Azure, AWS, GCP) Experience to read data from multiple sources and cleanse, enhance and analyze the data. Ability to integrate data, sourcing data from several Sources including databases, files, API and Server logs. Preferred Qualifications Minimum of 4+ years experience in data analytics, data mining, machine learning, and has employed predictive, prescriptive, conversational or generative AI to solve business problems Minimum of 4+ years experience in hands-on design, coding, development and deployment using data science tools such as Python, Tensorflow etc. to build AI solutions Minimum 2+ years experience leading teams to deliver solutions and results Deep knowledge of ML streams, e.g., natural language processing, computer vision, statistical learning theory and their application in real world situations Knowledge of ServiceNow and Salesforce products and features Experience working with one of the leading public clouds (AWS, Google, Azure) Excellent written and oral communication skills. Be able to work under pressure Ability to Multitask, Prioritize and Manage time effectively. Strong interpersonal skills and ability to work effectively across teams, functional groups Basic Requirements Bachelor's degree in Data Science, Computer Science, or an IT related field Minimum of 4+ years experience in a Data Science related role Travel Requirements None Relocation Provided None Position Type Experienced Referral Payment Plan No EEO Statement Motorola Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion or belief, sex, sexual orientation, gender identity, national origin, disability, veteran status or any other legally-protected characteristic. We are proud of our people-first and community-focused culture, empowering every Motorolan to be their most authentic self and to do their best work to deliver on the promise of a safer world. If you’d like to join our team but feel that you don’t quite meet all of the preferred skills, we’d still love to hear why you think you’d be a great addition to our team.

Job Purpose This role includes designing and building AI/ML products at scale to improve customer Understanding & Sentiment analysis, recommend customer requirements, recommend optimal inputs, Improve efficiency of Process. This role will collaborate with product owners and business owners. Key Responsibilities Leading a team of junior and experienced data scientists Lead and participate in end-to-end ML projects deployments that require feasibility analysis, design, development, validation, and application of state-of-the art data science solutions. Push the state of the art in terms of the application of data mining, visualization, predictive modelling, statistics, trend analysis, and other data analysis techniques to solve complex business problems including lead classification, recommender systems, product life-cycle modelling, Design Optimization problems, Product cost & weigh optimization problems. Leverage and enhance applications utilizing NLP, LLM, OCR, image based models and Deep Learning Neural networks for use cases including text mining, speech and object recognition Identify future development needs, advance new emerging ML and AI technology, and set the strategy for the data science team Cultivate a product-centric, results-driven data science organization Write production ready code and deploy real time ML models; expose ML outputs through APIs Partner with data/ML engineers and vendor partners for input data pipes development and ML models automation Provide leadership to establish world-class ML lifecycle management processes Qualifications Job Requirements MTech / BE / BTech / MSc in CS or Stats or Maths Experience Over 10 years of Applied Machine learning experience in the fields of Machine Learning, Statistical Modelling, Predictive Modelling, Text Mining, Natural Language Processing (NLP), LLM, OCR, Image based models, Deep learning and Optimization Expert Python Programmer: SQL, C#, extremely proficient with the SciPy stack (e.g. numpy, pandas, sci-kit learn, matplotlib) Proficiency in work with open source deep learning platforms like TensorFlow, Keras, Pytorch Knowledge of the Big Data Ecosystem: (Apache Spark, Hadoop, Hive, EMR, MapReduce) Proficient in Cloud Technologies and Service (Azure Databricks, ADF, Databricks MLflow) Functional Competencies A demonstrated ability to mentor junior data scientists and proven experience in collaborative work environments with external customers Proficient in communicating technical findings to non-technical stakeholders Holding routine peer code review of ML work done by the team Experience in leading and / or collaborating with small to midsized teams Experienced in building scalable / highly available distribute systems in production Experienced in ML lifecycle mgmt. and ML Ops tools & frameworks

Bangalore,Karnataka,India Job ID 768837 Join our Team About this opportunity: Ericsson Enterprise Wireless Solutions (BEWS) is responsible for driving Ericsson’s Enterprise Networking and Security business. Our expanding product portfolio covers wide area networks, local area networks, and enterprise security. We are the #1 global market leader in Wireless-WAN enterprise connectivity and are rapidly growing in enterprise Private 5G networks and Secure Access Services Edge (SASE) solutions. What Will You Do: Define the Data sourcing strategy and works with partners to procure data. Supply to IP creation for Ericsson in AI/ML. Research studies and creative usage of new and/or existing data sources. Work with Data Architects to use existing data models and build new ones as needed. Work with new technologies and be the ambassador for them in MI Communities within Ericsson, nurturing the communities and mentoring junior data scientists. Engage with external ecosystem (academia, technology leaders, open source etc.) to develop the skills and technology portfolio for MI’s needs Present and be prominent in MI related forums and conferences, e.g., publishing patents, presenting papers, organizing sessions etc. To be successful in the role you must have: Total 6 - 9 yrs of experience with proven skills of implementing a variety of Machine Learning techniques. Solid programming skills (R/Python) with proficiency in at least one. Proven track record of leading AI/ML projects end-to-end with complete ownership. Experience in Generative AI, conversation Assistant systems. Proven skills in building AI/ML based solutions using frameworks such as Python, R, H2O, Keras, TensorFlow, Spark ML etc. Experience in implementing new algorithms and methodologies from leading open source initiatives and research papers. Hands-on experience in designing and building AI models using Deep Neural Networks for applicable scenarios. Able to build and deploy AI models into production with focus on scaling, monitoring and performance. Sound knowledge of building explainable models (XAI) and prescriptive analytics.

Location Bangalore, Karnataka, India Category Digital Technology Job ID: R148691 Posted: Jun 20th 2025 Senior Data Scientist Do you like working in collaborative teams and solving technical problems? Are you a Senior Data Scientist looking for a new challenge? Join our innovative Engineering Team! Our Industrial and Energy Technology (IET) operates across 120 countries, serving the entire energy value chain and the industrial sector. We hold an extensive portfolio of rotating equipment, process flow, transmission technology and lifecycle services. Our Engineering Transformation team works to improve the quality of our Engineering processes. Partner with the best As a Senior Data Scientist, you will collaborate within a data science or cross-functional team alongside partners at Baker Hughes. Key focus areas include Automatic Defect Recognition (ADR) and Remote Monitoring & Diagnostics (RM&D) in Non-Destructive Testing (NDT) industrial sectors. You will lead customer engagements and develop analytics aligned with business objectives to address specific needs and opportunities. As a Senior Data Scientist, you will be responsible for: Engaging with stakeholders to define analytical goals. Designing and implementing ML/computer vision models for industrial use cases. Developing reusable components for scalable solutions. Building defect detection models for visual, ultrasound, and CT/X-ray images. Using TensorFlow/PyTorch for image classification, detection, and segmentation. Applying transfer learning to enhance model performance. Building and deploying ML pipelines using Flask, FastAPI, Streamlit, Docker, etc. Using time series and predictive maintenance to forecast equipment failures. Deploying solutions on edge or cloud platforms. Documenting results in technical and validation reports. Fuel your passion To be successful in this role, you will: Have a Bachelor's, Master’s, or PhD in Computer Science or a STEM field, with 3+ years of experience in developing computer vision solutions for industrial applications. Have at least 4 years of hands-on experience with machine learning and computer vision algorithms for tasks such as object detection, recognition, tracking, and segmentation. Have proficiency in deep learning and ML libraries such as TensorFlow, PyTorch, Keras, scikit-learn, and OpenCV. Have good knowledge of Convolutional Networks and Deep Learning algorithms Have solid programming skills with Python and/or non-scripting languages Have experience in data cleansing, data quality assessment, and applying analytics on industrial datasets Have practical knowledge of time series analysis and predictive maintenance for forecasting equipment health and optimising maintenance. Have good communication skills to collaborate with stakeholders and explain technical concepts to non-technical audiences. Have experience with Docker containers & cloud deployment is a plus Have prior exposure to NDT inspection data (e.g., CT/X-ray images) is a plus. Work in a way that works for you We recognise that everyone is different and that the way in which people want to work and deliver at their best is different for everyone too. In this role, we can offer the following flexible working patterns: Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive Working with us Our people are at the heart of what we do at Baker Hughes. We know we are better when all of our people are developed, engaged and able to bring their whole authentic selves to work. We invest in the health and well-being of our workforce, train and reward talent and develop leaders at all levels to bring out the best in each other. Working for you Our inventions have revolutionised energy for over a century. But to keep going forward tomorrow, we know we have to push the boundaries today. We prioritise rewarding those who embrace change with a package that reflects how much we value their input. Join us, and you can expect: Contemporary work-life balance policies and wellbeing activities Comprehensive private medical care options Safety net of life insurance and disability programs Tailored financial programs Additional elected or voluntary benefits About Us: We are an energy technology company that provides solutions to energy and industrial customers worldwide. Built on a century of experience and conducting business in over 120 countries, our innovative technologies and services are taking energy forward – making it safer, cleaner and more efficient for people and the planet. Join Us: Are you seeking an opportunity to make a real difference in a company that values innovation and progress? Join us and become part of a team of people who will challenge and inspire you! Let’s come together and take energy forward. Baker Hughes Company is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.

Title : Lead Data Scientist/ML Engineer (5+ years & above) Required Technical Skillset : (GenAI) Language : Python Framework : Scikit-learn, TensorFlow, Keras, PyTorch, Libraries : NumPy, Pandas, Matplotlib, SciPy, Scikit-learn - DataFrame, Numpy, boto3 Database : Relational Database(Postgres), NoSQL Database (MongoDB) Cloud : AWS cloud platforms Other Tools : Jenkins, Bitbucket, JIRA, Confluence A machine learning engineer is responsible for designing, implementing, and maintaining machine learning systems and algorithms that allow computers to learn from and make predictions or decisions based on data. The role typically involves working with data scientists and software engineers to build and deploy machine learning models in a variety of applications such as natural language processing, computer vision, and recommendation systems. The key responsibilities of a machine learning engineer includes : Collecting and preprocessing large volumes of data, cleaning it up, and transforming it into a format that can be used by machine learning models. Model building which includes Designing and building machine learning models and algorithms using techniques such as supervised and unsupervised learning, deep learning, and reinforcement learning. Evaluating the model performance of machine learning models using metrics such as accuracy, precision, recall, and F1 score. Deploying machine learning models in production environments and integrating them into existing systems using CI/CD Pipelines, AWS Sagemaker Monitoring the performance of machine learning models and making adjustments as needed to improve their accuracy and efficiency. Working closely with software engineers, product managers and other stakeholders to ensure that machine learning models meet business requirements and deliver value to the organization. Requirements And Skills Mathematics and Statistics : A strong foundation in mathematics and statistics is essential. They need to be familiar with linear algebra, calculus, probability, and statistics to understand the underlying principles of machine learning algorithms. Programming Skills Should be proficient in programming languages such as Python. The candidate should be able to write efficient, scalable, and maintainable code to develop machine learning models and algorithms. Machine Learning Techniques Should have a deep understanding of various machine learning techniques, such as supervised learning, unsupervised learning, and reinforcement learning and should also be familiar with different types of models such as decision trees, random forests, neural networks, and deep learning. Data Analysis And Visualization Should be able to analyze and manipulate large data sets. The candidate should be familiar with data cleaning, transformation, and visualization techniques to identify patterns and insights in the data. Deep Learning Frameworks Should be familiar with deep learning frameworks such as TensorFlow, PyTorch, and Keras and should be able to build and train deep neural networks for various applications. Big Data Technologies A machine learning engineer should have experience working with big data technologies such as Hadoop, Spark, and NoSQL databases. They should be familiar with distributed computing and parallel processing to handle large data sets. Software Engineering A machine learning engineer should have a good understanding of software engineering principles such as version control, testing, and debugging. They should be able to work with software development tools such as Git, Jenkins, and Docker. Communication And Collaboration A machine learning engineer should have good communication and collaboration skills to work effectively with cross-functional teams such as data scientists, software developers, and business stakeholders. (ref:hirist.tech)

Responsibilities Build and fine-tune models for NLP, computer vision, predictions, and more. Engineer intelligent pipelines that are used in production. Collaborate across teams to bring AI solutions to life (not just in Jupyter Notebooks). Embrace MLOps with tools like MLflow, Docker, and Kubernetes. Stay on the AI cutting edge and share what you learnmentorship mindset is a big plus. Champion code quality and contribute to a future-focused dev culture. Requirements 3-4 years in hardcore AI/ML or applied data science. Pro-level Python skills (R is cool too, but Python is king here). Mastery over ML frameworks: scikit-learn, XGBoost, LightGBM, TensorFlow/Keras, PyTorch. Hands-on with real-world data wrangling, feature engineering, and model deployment. DevOps-savvy: Docker, REST APIs, Git, and maybe even some MLOps sparkle. Cloud comfort: AWS, GCP, or Azure - take your pick. Solid grasp of Agile, good debugging instincts, and a hunger for optimization. (ref:hirist.tech)

Job Description Generative AI Expert and Lead – band B2/C1 Location: India (Hybrid) Role And Responsibilities SME for clients: Serve as the primary point of contact for clients in Gen AI needs, including senior executives, to understand their needs and deliver tailored generative AI solutions. Project Leadership: Lead multiple generative AI projects, ensuring timely delivery and high-quality outcomes. Define project deliverables, timelines, and methodologies. Team Management: Manage and mentor a team of AI specialists, fostering a collaborative and innovative environment. Solution Design: Architect and implement advanced generative AI models, including GANs, VAEs, and transformer-based models, to solve complex business problems. Thought Leadership: Provide strategic insights and thought leadership in generative AI, driving innovation and best practices within the organization. Technical Expertise: Stay abreast of the latest advancements in generative AI and machine learning, integrating cutting-edge technologies into projects. Qualifications Educational Background: Master's or PhD in computer science, engineering, mathematics, or related fields from top-tier institutions. Experience: 8+ years of experience in AI and machine learning, with a focus on generative AI, deep learning, and NLP. Proven track record in delivering generative AI projects. Technical Skills: Proficiency in Python, TensorFlow, PyTorch, Keras, and cloud platforms (AWS, Azure, GCP). Experience with large-scale data processing and model deployment. Certifications: Relevant certifications in AI and machine learning, such as TensorFlow Developer Certificate, AWS Certified Machine Learning – Specialty, or similar. (Preferred not mandatory) Leadership: Demonstrable leadership ability, with experience managing and mentoring teams. Problem-Solving: Superior problem-solving skills, with a track record of delivering innovative generative AI solutions. Communication: Excellent communication and presentation skills, with the ability to articulate complex technical concepts to non-technical stakeholders. Industry Knowledge: Deep understanding of industry trends and challenges in generative AI and machine learning.

Job Description Generative AI Expert and Lead – band C1/C2 Location: India (Hybrid) Role And Responsibilities SME for clients: Serve as the primary point of contact for clients in Gen AI needs, including senior executives, to understand their needs and deliver tailored generative AI solutions. Project Leadership: Lead multiple generative AI projects, ensuring timely delivery and high-quality outcomes. Define project deliverables, timelines, and methodologies. Team Management: Manage and mentor a team of AI specialists, fostering a collaborative and innovative environment. Solution Design: Architect and implement advanced generative AI models, including GANs, VAEs, and transformer-based models, to solve complex business problems. Thought Leadership: Provide strategic insights and thought leadership in generative AI, driving innovation and best practices within the organization. Technical Expertise: Stay abreast of the latest advancements in generative AI and machine learning, integrating cutting-edge technologies into projects. Qualifications Educational Background: Master's or PhD in computer science, engineering, mathematics, or related fields from top-tier institutions. Experience: 8+ years of experience in AI and machine learning, with a focus on generative AI, deep learning, and NLP. Proven track record in delivering generative AI projects. Technical Skills: Proficiency in Python, TensorFlow, PyTorch, Keras, and cloud platforms (AWS, Azure, GCP). Experience with large-scale data processing and model deployment. Certifications: Relevant certifications in AI and machine learning, such as TensorFlow Developer Certificate, AWS Certified Machine Learning – Specialty, or similar. (Preferred not mandatory) Leadership: Demonstrable leadership ability, with experience managing and mentoring teams. Problem-Solving: Superior problem-solving skills, with a track record of delivering innovative generative AI solutions. Communication: Excellent communication and presentation skills, with the ability to articulate complex technical concepts to non-technical stakeholders. Industry Knowledge: Deep understanding of industry trends and challenges in generative AI and machine learning.

PwC AC is hiring for Data scientist Apply and get a chance to work with one of the Big4 companies #PwC AC. Job Tit le : Data scientist Years of Experienc e: 4+ years Shift Timin gs: 2PM-11PM Qualificati on: Graduate and above(Full time) About PwC CTIO – AI Engineering PwC’s Commercial Technology and Innovation Office (CTIO) is at the forefront of emerging technology, focused on building transformative AI-powered products and driving enterprise innovation. The AI Engineering team within CTIO is dedicated to researching, developing, and operationalizing cutting-edge technologies such as Generative AI, Large Language Models (LLMs), AI Agents, and more. Our mission is to continuously explore what's next—enabling business transformation through scalable AI/ML solutions while remaining grounded in research, experimentation, and engineering excellence. Role Overview We are seeking a Senior Associate – Data Science/ML/DL/GenAI to join our high-impact, entrepreneurial team. This individual will play a key role in designing and delivering scalable AI applications, conducting applied research in GenAI and deep learning, and contributing to the team’s innovation agenda. This is a hands-on, technical role ideal for professionals passionate about AI-driven transformation. Key Responsibilities Design, develop, and deploy machine learning, deep learning, and Generative AI solutions tailored to business use cases. Build scalable pipelines using Python (and frameworks such as Flask/FastAPI) to operationalize data science models in production environments. Prototype and implement solutions using state-of-the-art LLM frameworks such as LangChain, LlamaIndex, LangGraph, or similar. Also developing applications in streamlit/chainlit for demo purposes. Design advanced prompts and develop agentic LLM applications that autonomously interact with tools and APIs. Fine-tune and pre-train LLMs (HuggingFace and similar libraries) to align with business objectives. Collaborate in a cross-functional setup with ML engineers, architects, and product teams to co-develop AI solutions. Conduct R&D in NLP, CV, and multi-modal tasks, and evaluate model performance with production-grade metrics. Stay current with AI research and industry trends; continuously upskill to integrate the latest tools and methods into the team’s work. Required Skills & Experience 4 to 9 years of experience in Data Science/ML/AI roles. Bachelor’s degree in Computer Science, Engineering, or equivalent technical discipline (BE/BTech/MCA). Proficiency in Python and related data science libraries: Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, PyTorch, Keras, etc. Hands-on experience with Generative AI , including prompt engineering, LLM fine-tuning, and deployment. Experience with Agentic LLMs and task orchestration using tools like LangGraph or AutoGPT-like flows. Strong knowledge of NLP techniques, transformer architectures, and text analysis. Proven experience working with cloud platforms (preferably Azure; AWS/GCP also considered). Understanding of production-level AI systems including CI/CD, model monitoring, and cloud-native architecture. (Need not develop from scratch) Familiarity with ML algorithms: XGBoost, GBM, k-NN, SVM, Decision Forests, Naive Bayes, Neural Networks, etc. Exposure to deploying AI models via APIs and integration into larger data ecosystems. Strong understanding of model operationalization and lifecycle management. Good to Have Experience with Docker, Kubernetes, and containerized deployments for ML workloads. Use of MLOps tooling and pipelines (e.g., MLflow, Azure ML, SageMaker, etc.). Experience in full-stack AI applications, including visualization (e.g., PowerBI, D3.js). Demonstrated track record of delivering AI-driven solutions as part of large-scale systems. Soft Skills & Team Expectations Strong written and verbal communication; able to explain complex models to business stakeholders. Ability to independently document work, manage requirements, and self-drive technical discovery. Desire to innovate, improve, and automate existing processes and solutions. Active contributor to team knowledge sharing, technical forums, and innovation drives. Strong interpersonal skills to build relationships across cross-functional teams. A mindset of continuous learning and technical curiosity. Preferred Certifications (at least two are preferred) Certifications in Machine Learning, Deep Learning, or Natural Language Processing. Python programming certifications (e.g., PCEP/PCAP). Cloud certifications (Azure/AWS/GCP) such as Azure AI Engineer, AWS ML Specialty, etc. Why Join PwC CTIO? Be part of a mission-driven AI innovation team tackling industry-wide transformation challenges. Gain exposure to bleeding-edge GenAI research, rapid prototyping, and product development. Contribute to a diverse portfolio of AI solutions spanning pharma, finance, and core business domains. Operate in a startup-like environment within the safety and structure of a global enterprise. Accelerate your career as a deep tech leader in an AI-first future.

Objectives of this role Design and develop machine learning algorithms and deep learning applications and systems for Inturai Solve complex problems with real time digital signal data processing (DSP), and optimize existing machine learning libraries and frameworks. Collaborate with product, data scientists, architects, engineers, and SME in integrating and deploying models in production systems. Identify differences in data distribution, operating environment that could potentially affect model performance in real-world applications. Test and Ensure algorithms generate predictable outcomes. Stay up to date with developments in the machine learning industry Responsibilities Study and transform DSP, data science prototypes and apply appropriate machine learning algorithms and tools to create ML models. Run machine learning tests and experiments, and document findings and results Train/retrain, and monitor machine learning systems and models as needed Construct optimized data pipelines to feed machine learning models Consult with managers, SMEs to determine and refine machine learning objectives Extend existing machine learning libraries and frameworks Skills and qualifications Computer programming skills together with understanding of Signal Processing (RF and WiFi Channel State Information). Good math with a deep understanding of probability, statistics, and ML algorithms. In-depth knowledge of machine learning frameworks based on like Keras/Tensorflow/SenseFi/PyTorch. Experience in working with RF/WiFi enabled SBC hardware. Familiarity with data structures, data modeling, and software architecture Impeccable analytical and problem-solving skills Excellent time management and organizational skills Desire to learn Preferred qualifications Bachelors degree (or equivalent) in Electronics, Computer Science, or related field. Proven experience as a machine learning engineer or similar role Experience with Tensor, Python, Java, and R based implementations Experience with Digital signal processing Experience in building and consuming APIs Excellent communication and collaboration skills General knowledge of building machine learning systems Innovative mind with a passion for continuous learning

In the IBM Chief Information Office,you wi be part of a dynamic team driving the future of AI and data science in arge-scae enterprise transformations. We offer a coaborative environment where your technica expertise wi be vaued, and your professiona deveopment wi be supported. Join us to work on chaenging projects, everage the atest technoogies, and make a tangibe impact on eading organisations. As a Data Scientist within IBM's Chief Information Office, you wi support AI-driven projects across the enterprise. You wi appy your technica skis in AI, machine earning, and data anaytics to assist in impementing data-driven soutions that aign with business goas. This roe invoves working with team members to transate data insights into actionabe recommendations. Key Responsibiities: Technica Execution and Leadership: Deveop and depoy AI modes and data anaytics soutions. Support the impementation and optimisation of AI-driven strategies per business stakehoder requirements. Hep refine data-driven methodoogies for transformation projects. Data Science and AI: Design and impement machine earning soutions and statistica modes, from probem formuation through depoyment, to anayse compex datasets and generate actionabe insights. Learn and utiise coud patforms to ensure the scaabiity of AI soutions. Leverage reusabe assets and appy IBM standards for data science and deveopment. Project Support: Lead and contribute to various stages of AI and data science projects, from data exporation to mode deveopment. Monitor project timeines and hep resove technica chaenges. Design and impement measurement frameworks to benchmark AI soutions, quantifying business impact through KPIs. Coaboration: Ensure aignment to stakehoders strategic direction and tactica needs. Work with data engineers, software deveopers, and other team members to integrate AI soutions into existing systems. Contribute technica expertise to cross-functiona teams. Required education Bacheor's Degree Preferred education Master's Degree Required technica and professiona expertise Bacheors or Masters in Computer Science, Data Science, Statistics, or a reated fied is required; an advanced degree is strongy preferred Experience: 5+ yearsof experience in data science, AI, or anaytics with a focus on impementing data-driven soutions Experience with data ceaning, data anaysis, A/B testing, and data visuaization Experience with AI technoogies through coursework or projects Technica Skis: Proficiency in SQL and Python for performing data anaysis and deveoping machine earning modes Knowedge of common machine earning agorithms and frameworksinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neura networks, and deep earning frameworks such as TensorFow and PyTorch Experience with coud-based patforms and data processing frameworks Understanding of arge anguage modes (LLMs) Famiiarity with IBMs watsonx product suite Famiiarity with object-oriented programming Anaytica Skis: Strong probem-soving abiities and eagerness to earn

Work with broader team to buid, anayze and improve the AI soutions. You wi aso work with our software deveopers in consuming different enterprise appications Required education Bacheor's Degree Preferred education Master's Degree Required technica and professiona expertise Resource shoud have 5-7 years of experience. Sound knowedge of Python and shoud know how to use the ML reated services. Proficient in Python with focus on Data Anaytics Packages. Strategy Anayse arge, compex data sets and provide actionabe insights to inform business decisions. Strategy Design and impementing data modes that hep in identifying patterns and trends. Coaboration Work with data engineers to optimize and maintain data pipeines. Perform quantitative anayses that transate data into actionabe insights and provide anaytica, data-driven decision-making. Identify and recommend process improvements to enhance the efficiency of the data patform. Deveop and maintain data modes, agorithms, and statistica modes Preferred technica and professiona experience Experience with conversation anaytics. Experience with coud technoogies Experience with data exporation toos such as Tabeu

Job Purpose This role includes designing and building AI/ML products at scale to improve customer Understanding & Sentiment analysis, recommend customer requirements, recommend optimal inputs, Improve efficiency of Process. This role will collaborate with product owners and business owners. Key Responsibilities Leading a team of junior and experienced data scientists Lead and participate in end-to-end ML projects deployments that require feasibility analysis, design, development, validation, and application of state-of-the art data science solutions. Push the state of the art in terms of the application of data mining, visualization, predictive modelling, statistics, trend analysis, and other data analysis techniques to solve complex business problems including lead classification, recommender systems, product life-cycle modelling, Design Optimization problems, Product cost & weigh optimization problems. Leverage and enhance applications utilizing NLP, LLM, OCR, image based models and Deep Learning Neural networks for use cases including text mining, speech and object recognition Identify future development needs, advance new emerging ML and AI technology, and set the strategy for the data science team Cultivate a product-centric, results-driven data science organization Write production ready code and deploy real time ML models; expose ML outputs through APIs Partner with data/ML engineers and vendor partners for input data pipes development and ML models automation Provide leadership to establish world-class ML lifecycle management processes Job Requirements Qualifications MTech / BE / BTech / MSc in CS or Stats or Maths Experience Over 10 years of Applied Machine learning experience in the fields of Machine Learning, Statistical Modelling, Predictive Modelling, Text Mining, Natural Language Processing (NLP), LLM, OCR, Image based models, Deep learning and Optimization Expert Python Programmer: SQL, C#, extremely proficient with the SciPy stack (e.g. numpy, pandas, sci-kit learn, matplotlib) Proficiency in work with open source deep learning platforms like TensorFlow, Keras, Pytorch Knowledge of the Big Data Ecosystem: (Apache Spark, Hadoop, Hive, EMR, MapReduce) Proficient in Cloud Technologies and Service (Azure Databricks, ADF, Databricks MLflow) Functional Competencies A demonstrated ability to mentor junior data scientists and proven experience in collaborative work environments with external customers Proficient in communicating technical findings to non-technical stakeholders Holding routine peer code review of ML work done by the team Experience in leading and / or collaborating with small to midsized teams Experienced in building scalable / highly available distribute systems in production Experienced in ML lifecycle mgmt. and ML Ops tools & frameworks

Overview: Dozee Health AI is a pioneer in Contactless Remote Patient Monitoring (RPM), proven to drive transformation at scale Headquartered in Bengaluru, India, Dozee has emerged as Indias no 1 RPM Company, We are seeking visionary individuals to help us in this very exciting journey As a part of our dynamic team, youll have the opportunity to collaborate with top healthcare providers in the country, applying AI-powered RPM solutions to tackle some of the most pressing challenges in healthcare enhancing staff efficiency, improving patient outcomes, and pioneering the next generation of care models, Responsibilities To initiate, develop and optimize algorithms to solve healthcare problems To ensure a constant flow of case studies/publications from acquired health datasets To extract feedback for product and marketing in order to improve and optimize their functions To optimize and upgrade existing pipelines and processesTo ensure performance on par with business requirements To keep the software stack and implementation up to date with the latest advancements in the industry Requirement 5+ years of relevant work experienceStrong fundamentals in statistics and machine learning Excellent scripting and programming skills with Python(preferred), Julia or R Experience of working with Time series data Experience of mining, handling and analyzing big datasets Experience of working with TensorFlow/Keras/Pytorch Experience of working with Spark/Hadoop and help setup pipelines Excellent data communication, sharp analytical abilities with proven design skills along with ability to think critically of the current system and existing projects Vision & Mission Save Million lives with Health AI Dozee is Indias leading AI-Powered contactless Remote Patient Monitoring (RPM) and Early Warning System (EWS) A solution that continuously monitors patients and provides early warnings of clinical deterioration, enabling timely interventions and enhancing patient safety in hospitals, nursing facilities and patient homes A "Made in India for the World" solution, Dozee has pioneered the worlds first non-contact blood pressure monitoring system Trusted by leading healthcare providers in India, the USA, and Africa, Dozee is transforming patient safety and care by enhancing outcomes and reducing costs, Dozee is adopted by 300+ hospitals and monitors 16000+ beds across 4 countries Dozee has monitored over 1 Mn Patients, Delivered 35000+ Life Saving Alerts and Saved 10 Mn+ Nursing Hours, Videos Science Behind Dozee : Ballistocardiography & Artificial Intelligence 100 Dozee deliver 144 life saving alerts and INR 2 7 Cr of saving Sattva Study Dozee saves life of a mother at home Leading Healthcare Game changers work with Dozee I I ntroducing Dozee VS Dozee Shravan A clinical grade RPM service Dozee In News Bloomberg Oct 21, 2024 From AI Beds to Remote ICUs, Startups are plugging India's health Gaps News18Oct 26, 2024 Now, You Can Remotely Monitor Your Loved Ones in Hospital With Bengaluru Start-Up's 'Shravan' Analytics India MagazineOct 29, 2024 Dozee Harness AI for Personalised Patient Care ET HealthWorldSep 16, 2024 We trust AI everyday From Google Maps to Smartphones, So why not use it to enhance patient safety in healthcare BW healthcareworldOct 29, 2024 Dozee's AI-Powered System Predicts Patient Deterioration 16 Hours in Advance A tertiary care hospital study published in JMIR , validated Dozees Early Warning System (EWS), showing it identified 97% of deteriorating patients, provided alerts ~19 hours in advance , and generated 5x fewer alerts, reducing alarm fatigue and improving patient outcomes, A study at King George Medical University, Lucknow, and published in Frontiers in Medical Technology demonstrated that Dozees automation can potentially save 2 5 hours of nursing time per shift , improving workflow efficiency and allowing more focus on patient care, A study on remote patient monitoring in general wards published in Cureus found that 90%+ of healthcare providers reported improved care and patient safety, 74% of patients felt safer , and there was a 43% increase in time for direct patient care, Research by Sattva , an independent consulting firm, demonstrates Dozee's substantial impact: for every 100 Dozee-connected beds, it can save approximately 144 lives , reduce nursestime for vital checks by 80% , and decrease ICU average length of stay by 1 3 days, Key Highlights Founded : October, 2015 Founders : Mudit Dandwate, Gaurav Parchani Headquarters : Bangalore, India | Houston, USA | Dubai, UAE Key Investors & Backers : Prime Ventures, 3one4 Capital, YourNest Capital, Gokul Rajaram, BIRAC (Department of Biotechnology, State Bank of India, and Dinesh Mody Ventures, Temasek Foundation, Horizons Ventures Stage : Series A+ Team Strength : 280+ Business : Providing Continuum of care with AI-powered contactless Remote Patient Monitoring (RPM) and Early Warning System (EWS) for Hospitals and Home, Certifications & Accreditations : ISO13485:2016 Certified, ISO27001:2022 Certified, CDSCO Registered, FDA510K Cleared for the flagship product Dozee Vitals Signs (VS) measurement system and SOC2 Type II Certified Achievements Forbes India 30 under 30 Forbes Asia 100 to Watch Times Network India Health Awards 2024 for AI innovation in Bharat Healthcare tech BML Munjal Award for Business Excellence using Learning and Development FICCI Digital Innovation in Healthcare Award Anjani Mashelkar Inclusive Innovation Award Marico Innovation For India Award, To know more about life@dozee, click here , Disclaimer: Dozee is an equal opportunity employer We celebrate diversity and are committed to creating an inclusive environment for all employees ? Dozee does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law All employment is decided on the basis of qualifications, merit, and business need Dozee will not tolerate discrimination or harassment based on any of these characteristics

Education and Work Experience Requirements: · 5 to 8 years of experience as Data Science Architect · 2 to 3 years of experience in Generative AI solution development · Proven track record and experience with with GenAI technologies o Open source LLMs like Llama, Gemma, Mixtral etc o Closed source LLMs such as Open AI GPT, Azure Open AI, Claude, Gemini etc o Prompt Engineering/Tuning, RAG, RAFT, LLM finetuning such as PEFT(LoRA, QLoRA ..) o Understanding of SLMs such as Phi3,QWEN, BERT and Transformer architecture o Vector databases like Pinecone, Qdrant etc. · Good knowledge of advanced statistical methods. Experience working with Text Data using transformer-based model · Expertise with the following scripting languages: o Python, R, Tensorflow, Keras, Pytorch o OpenNLP, CoreNLP, WordNet, NLTK, SpaCy, Gensim, Large Language Models, Knowledge Graphs · Design and implement end-to-end Generative AI solutions, ensuring seamless integration with enterprise applications and workflows. · Lead technical evaluations and POCs (Proof of Concepts) to assess new AI models, frameworks, and vector databases for RAG solutions. · Develop scalable indexing and retrieval strategies to optimize search and generation performance in large-scale AI systems. · Implement hybrid search techniques, including dense and sparse retrieval, for enhanced information retrieval accuracy. · Define and enforce architectural standards, coding best practices, and performance benchmarks for RAG-based applications. · Collaborate with business leaders to identify AI-driven opportunities and develop strategic roadmaps for AI product evolution. · Drive the adoption of domain-specific AI solutions by tailoring RAG architectures to industry-specific requirements. · Establish feedback loops and model monitoring mechanisms to ensure continuous improvement of AI-generated outputs. · Utilize MLOps best practices to automate model deployment, monitoring, and retraining pipelines for Generative AI solutions. · Optimize knowledge graphs and vector embeddings to enhance contextual awareness in Graph RAG implementations. · Develop strategies for handling long-context retrieval and efficient chunking mechanisms for better AI response quality. · Leverage fine-tuning and reinforcement learning with human feedback (RLHF) to improve generative AI model performance. · Explore and integrate federated learning techniques to enable privacy-preserving AI model training and inference. · Conduct AI ethics assessments and bias mitigation strategies to ensure responsible AI development and deployment. · Engage with open-source AI communities and contribute to research publications or technical blogs on RAG advancements. · Participate in technical panels, conferences, and industry events to showcase AI expertise and thought leadership. · Support sales and pre-sales teams by providing technical guidance, solution demonstrations, and AI-driven business value assessments. · Establish AI Centers of Excellence (CoE) within the organization to drive innovation, knowledge sharing, and AI capability building. · Ensure compliance with enterprise security policies, data governance regulations, and responsible AI guidelines. · Develop multi-modal AI capabilities that integrate NLP, Computer Vision, and Speech Recognition for advanced generative applications. · Prior experience working on Mobility, Manufacturing or Healthcare domain will be a plus. Mandatory Skills: · Design, develop, test, and deploy Machine Learning models using state-of-the-art algorithms with a strong focus on language models. · Strong understanding of LLMs, and asso Educational qualification: BE/BTech or MCA Experience : 10-15 years

Education and Work Experience Requirements: · 5 to 8 years of experience as Data Scientist · 2 to 3 years of experience in Generative AI solution development · Strong understanding of AI agent collaboration, negotiation, and autonomous decision-making. · Experience in developing and deploying AI agents that operate independently or collaboratively in complex environments. · Deep knowledge of agentic AI principles, including self-improving, self-organizing, and goal-driven agents. · Proficiency in multi-agent frameworks such as AutoGen, LangGraph, LangChain, and CrewAI for orchestrating AI workflows. · Hands-on experience integrating LLMs (GPT, LLaMA, Mistral, etc.) with agentic frameworks to enhance automation and reasoning. · Expertise in hierarchical agent frameworks, distributed agent coordination, and decentralized AI governance. · Strong grasp of memory architectures, tool use, and action planning within AI agents. · Autonomy Score: Measures the degree of independence in decision-making. · Collaboration Efficiency: Evaluates the ability of agents to work together and share information. · Task Completion Rate: Tracks the percentage of tasks successfully executed by agents. · Response Time: Measures the latency in agent decision-making and execution. · Adaptability Index: Assesses how well agents adjust to dynamic changes in the environment. · Resource Utilization Efficiency: Evaluates computational and memory usage for optimization. · Explainability & Interpretability Score: Ensures transparency in agent reasoning and outputs. · Error Rate & Recovery Time: Tracks failures and the system’s ability to self-correct. · Knowledge Retention & Utilization: Measures how effectively agents recall and apply information. · Hands-on experience with LLMs such as GPT, BERT, LLaMA, Mistral, Claude, Gemini, etc. · Proven expertise in both open-source (LLaMA, Gemma, Mixtral) and closed-source (OpenAI GPT, Azure OpenAI, Claude, Gemini) LLMs. · Advanced skills in prompt engineering, tuning, retrieval-augmented generation (RAG), reinforcement learning (RAFT), and LLM fine-tuning (PEFT, LoRA, QLoRA). · Strong understanding of small language models (SLMs) like Phi-3 and BERT, along with Transformer architectures. · Experience working with text-to-image models such as Stable Diffusion, DALL·E, and Midjourney. · Proficiency in vector databases such as Pinecone, Qdrant for knowledge retrieval in agentic AI systems. · Deep understanding of Human-Machine Interaction (HMI) frameworks within cloud and on-prem environments. · Strong grasp of deep learning architectures, including CNNs, RNNs, Transformers, GANs, and VAEs. · Expertise in Python, R, TensorFlow, Keras, and PyTorch. · Hands-on experience with NLP tools and libraries: OpenNLP, CoreNLP, WordNet, NLTK, SpaCy, Gensim, Knowledge Graphs, and LLM-based applications. · Proficiency in advanced statistical methods and transformer-based text processing. · Experience in reinforcement learning and planning techniques for autonomous agent behavior. Mandatory Skills: · Design, develop, test, and deploy Machine Learning models using state-of-the-art algorithms with a strong focus on language models. · Strong understanding of LLMs, and associated technologies like RAG, Agents, VectorDB and Guardrails · Hand-on experience in GenAI frameworks like LlamaIndex, Langchain, Autogen, etc. · Experience in cloud services like Azure, GCP and AWS · Multi-agent frameworks: AutoGen, LangGraph, LangChain, CrewAI · Large Language Models (LLMs): GPT, Educational qualification: BE,BTECH or PHD

TECHNICAL ARCHITECT Key Responsibilities 1. Designing technology systems: Plan and design the structure of technology solutions, and work with design and development teams to assist with the process. 2. Communicating: Communicate system requirements to software development teams, and explain plans to developers and designers. They also communicate the value of a solution to stakeholders and clients. 3. Managing Stakeholders: Work with clients and stakeholders to understand their vision for the systems. Should also manage stakeholder expectations. 4. Architectural Oversight: Develop and implement robust architectures for AI/ML and data science solutions, ensuring scalability, security, and performance. Oversee architecture for data-driven web applications and data science projects, providing guidance on best practices in data processing, model deployment, and end-to-end workflows. 5. Problem Solving: Identify and troubleshoot technical problems in existing or new systems. Assist with solving technical problems when they arise. 6. Ensuring Quality: Ensure if systems meet security and quality standards. Monitor systems to ensure they meet both user needs and business goals. 7. Project management: Break down project requirements into manageable pieces of work, and organise the workloads of technical teams. 8. Tool & Framework Expertise: Utilise relevant tools and technologies, including but not limited to LLMs, TensorFlow, PyTorch, Apache Spark, cloud platforms (AWS, Azure, GCP), Web App development frameworks and DevOps practices. 9. Continuous Improvement: Stay current on emerging technologies and methods in AI, ML, data science, and web applications, bringing insights back to the team to foster continuous improvement. Technical Skills 1. Proficiency in AI/ML frameworks such as TensorFlow, PyTorch, Keras, and scikit-learn for developing machine learning and deep learning models. 2. Knowledge or experience working with self-hosted or managed LLMs. 3. Knowledge or experience with NLP tools and libraries (e.g., SpaCy, NLTK, Hugging Face Transformers) and familiarity with Computer Vision frameworks like OpenCV and related libraries for image processing and object recognition. 4. Experience or knowledge in back-end frameworks (e.g., Django, Spring Boot, Node.js, Express etc.) and building RESTful and GraphQL APIs. 5. Familiarity with microservices, serverless, and event-driven architectures. Strong understanding of design patterns (e.g., Factory, Singleton, Observer) to ensure code scalability and reusability. 6. Proficiency in modern front-end frameworks such as React, Angular, or Vue.js, with an understanding of responsive design, UX/UI principles, and state management (e.g., Redux) 7. In-depth knowledge of SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra), as well as caching solutions (e.g., Redis, Memcached). 8. Expertise in tools such as Apache Spark, Hadoop, Pandas, and Dask for large-scale data processing. 9. Understanding of data warehouses and ETL tools (e.g., Snowflake, BigQuery, Redshift, Airflow) to manage large datasets. 10. Familiarity with visualisation tools (e.g., Tableau, Power BI, Plotly) for building dashboards and conveying insights. 11. Knowledge of deploying models with TensorFlow Serving, Flask, FastAPI, or cloud-native services (e.g., AWS SageMaker, Google AI Platform). 12. Familiarity with MLOps tools and practices for versioning, monitoring, and scaling models (e.g., MLflow, Kubeflow, TFX). 13. Knowledge or experience in CI/CD, IaC and Cloud Native toolchains. 14. Understanding of security principles, including firewalls, VPC, IAM, and TLS/SSL for secure communication. 15. Knowledge of API Gateway, service mesh (e.g., Istio), and NGINX for API security, rate limiting, and traffic management. Experience Required Technical Architect with 7 - 12 years of experience Salary 22-25 LPA Job Types: Full-time, Permanent Pay: ₹2,200,000.00 - ₹2,500,000.00 per year Experience: total work: 1 year (Preferred) Work Location: In person