184 Regularization Jobs

Job Description Job responsibility Overall responsibility Supervise the team in handling all technical complaints& NT received through the contact center Ensure Service Recovery of Dissatisfied Customers Develop strategies to improve the resolution process and enhance customer satisfaction. Develop and maintain escalation procedures to ensure streamlined handling of escalated cases. Collaborate with other Stakeholders such as NOC, Switch, Technology, CPO to provide immediate resolution & for SIP. Monitor and analyse metrics related to technical complaint resolution, such as resolution time, resolution rates, and customer feedback. Identify and address any performance gaps. Work on repeat reduction of technical complaints along with cross functional teams. Collect and analyse feedback from customers regarding their experience with technical support. Use this feedback to drive continuous improvement in processes and service delivery. Manage the Virtual Service Manager Desk, tracking performance metrics such as CCI, MTTR, and repeat complaints. Implement strategies to improve NPS and enhance overall customer satisfaction. Optimize contact center operations for improved efficiency and performance. Lead, mentor, and support contact Center team, ensuring they meet performance goals and receive ongoing development. Oversee the management of the SA (Service Assurance) Base, ensuring accurate and up-to-date information. Responsible for updating and maintain the escalation matrix on the KYSM portal on time. Manage and track SA Reap processes, ensuring timely and accurate execution. Responsible for linear approval processes, ensuring compliance with company policies. Manage the Linear repository, maintaining accurate records and documentation, Coordinate with the Network team for regularization. Develop and manage the third-party scorecard to assess performance and compliance. Functional areas To ensure reduction in CCI [Customer complaint Index] To ensure SR and complaints tickets are cleared within the stipulated timelines Timely preparation of RCA and feed CFT’s to effectively work towards complaint reduction Vendor management Ensure error free solution CSAT/NPS Employee Engagement Monitor Performance Management and design Team Development Initiatives to enhance performance. Identify training needs and take necessary actions to develop the Contact Centre team with help of ASRM by arranging training sessions to new/existing partner teams on new products and solutions from product teams. Process Improvements Identify process gaps based on internal investigation and do process correction with Product & IT developments Monitor and Audit outsourced call centre partner performance on agreed deliverables. Create Knowledge database of different service complaints and their solutions for referral General Take necessary steps for increasing FTR and complaint reduction Monitor & Control dashboards publication for senior management Provide long-term inputs for IT strategy by specifying a business process framework Facilitate predictable, repeatable, and scalable implementation projects by using standard components Shift Working Normal Shift Key Customer External Customers / Business Partners Internal Technology Team Customer NOC Team Compliant Management team Relationship Management team Regional CSO teams Product Team Internal Necessary Preferred Skills Should have relevant knowledge and experience of - Good Process knowledge Email Centre Client Experience Team management Data efficiency System knowledge Sound Knowledge in Telecom or a similar role in any industry. Industry-Specific Knowledge – Domain Expertise Qualification Graduate . Overall Work Experience . Minimum 10 years of relevant experience preferably in Telecom Domain Behavioural Attributes Strong customer focus Good analytical skills Strong communication and interpersonal skills Inclination towards innovation Decision Making Client Orientation Relationship Management . About Us Transforming Businesses through Digitalization Tata Tele Business Services (TTBS), belonging to the prestigious Tata Group of Companies, is the country’s leading enabler of connectivity and communication solutions for businesses. With services ranging from connectivity, collaboration, cloud, security, IoT, and marketing solutions, TTBS offers the largest portfolio of ICT services for businesses in India. With an unwavering focus on customer-centricity and innovation, TTBS continues to garner recognition from customers and peers alike. Our People Shape Our Journey Ahead We are India’s leading enabler of digital connectivity and technology solutions for businesses - a feat possible only because we are fueled by the dedication and passion of our people. We welcome the finest talent and believe in nurturing and mentoring them to rise into leadership roles, while standing tall on our ethics and values.

Key Responsibilities 1. Attendance & Leave Management a) Maintain and monitor daily attendance, leave records, and shift schedules. b) Ensure accurate tracking of absenteeism and late coming. c) Coordinate with team leads/managers for regularization of attendance. 2. Payroll & Salary Processing a) Assist in monthly payroll processing with accuracy. b) Handle inputs such as attendance, overtime, incentives, deductions, and statutory compliance. c) Generate payslips and resolve salary-related queries of employees. 3. Talent Acquisition (Recruitment) a) Handle end-to-end recruitment process: sourcing, screening, scheduling interviews, and onboarding. b) Maintain candidate pipeline through job portals, social media, referrals, etc. c) Support campus drives and bulk hiring when required. 4. Induction & Training a) Conduct new employee induction/orientation programs. b) Assist in planning and coordinating training sessions. c) Ensure smooth onboarding experience for new hires. 5. Employee Engagement & HR Operations a) Support employee engagement initiatives and grievance handling. b) Maintain HR records and employee files as per compliance. c) Coordinate with departments for day-to-day HR operational activities. Required Skills & Qualifications l Bachelor’s/Master’s degree in HR, Business Administration, or related field. l 0–2 years of experience in HR functions (attendance, payroll, recruitment, induction). l Knowledge of HR software/tools (attendance management systems, payroll software, Excel). l Good communication, interpersonal, and organizational skills. l Basic understanding of statutory compliances (PF, ESIC, PT, etc.) preferred. What We Offer Ø Opportunity to grow within the HR domain. Ø Exposure to end-to-end HR functions in a dynamic environment. Ø Supportive team and professional development opportunities. Job Types: Full-time, Permanent Pay: ₹20,000.00 - ₹30,000.00 per month Benefits: Leave encashment Work Location: In person

This role is for one of our clients Industry: Technology, Information and Media Seniority level: Associate level Min Experience: 3 years Location: Gurugram, Delhi, Uttar Pradesh, NCR, NOIDA, Kanpur, Uttarakhand JobType: full-time We’re looking for a Machine Learning Engineer (3–5 years experience) who is passionate about turning complex data into intelligent, scalable solutions. In this role, you’ll design and deploy machine learning models, optimize algorithms for performance, and collaborate with cross-functional teams to bring AI-powered applications into production. If you thrive in solving challenging problems with real-world impact, this role is for you. What You’ll Do Model Design & Deployment Build and deploy machine learning models that solve business-critical problems. Implement and optimize classification, regression, clustering, and anomaly detection techniques. Ensure models are scalable, efficient, and production-ready. Data Preparation & Feature Engineering Work with structured and unstructured datasets, ensuring quality and usability. Apply feature engineering, dimensionality reduction, and transformation techniques. Perform exploratory data analysis (EDA) to uncover patterns and insights. Algorithm Optimization Experiment with a range of ML techniques — from Support Vector Machines to ensemble methods and deep learning. Fine-tune hyperparameters, validate models, and optimize performance. Apply cross-validation, regularization, and advanced optimization strategies. Collaboration & Integration Work closely with data scientists, engineers, and product teams to embed ML models into real-world applications. Develop APIs and reusable frameworks to simplify model deployment. Communicate findings and translate model outputs into actionable insights. Innovation & Growth Stay ahead of the curve on ML, AI, and deep learning advancements. Propose and implement new approaches to enhance system accuracy and efficiency. Contribute to building a strong foundation of reusable ML tools and best practices. What You’ll Bring Education: Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related field. Experience: 3–5 years in ML engineering, with hands-on model development and deployment. Core Skills: Strong experience with Support Vector Machines (SVM) and other supervised/unsupervised methods. Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Knowledge of statistics, probability, linear algebra, and optimization techniques. Tools & Platforms: Data visualization (Matplotlib, Seaborn, Plotly). Version control (Git). Cloud platforms (AWS, Azure, or GCP). Soft Skills: Analytical mindset, problem-solving, clear communication, and team collaboration. Bonus Points If You Have Experience in deep learning (CNNs, RNNs, Transformers). Exposure to NLP or computer vision projects. Familiarity with large-scale data processing frameworks (Spark, Hadoop).

This role is for one of our clients Industry: Technology, Information and Media Seniority level: Associate level Min Experience: 3 years Location: Gurugram, Delhi, Uttar Pradesh, NCR, NOIDA, Kanpur, Uttarakhand JobType: full-time We’re looking for a Machine Learning Engineer (3–5 years experience) who is passionate about turning complex data into intelligent, scalable solutions. In this role, you’ll design and deploy machine learning models, optimize algorithms for performance, and collaborate with cross-functional teams to bring AI-powered applications into production. If you thrive in solving challenging problems with real-world impact, this role is for you. What You’ll Do Model Design & Deployment Build and deploy machine learning models that solve business-critical problems. Implement and optimize classification, regression, clustering, and anomaly detection techniques. Ensure models are scalable, efficient, and production-ready. Data Preparation & Feature Engineering Work with structured and unstructured datasets, ensuring quality and usability. Apply feature engineering, dimensionality reduction, and transformation techniques. Perform exploratory data analysis (EDA) to uncover patterns and insights. Algorithm Optimization Experiment with a range of ML techniques — from Support Vector Machines to ensemble methods and deep learning. Fine-tune hyperparameters, validate models, and optimize performance. Apply cross-validation, regularization, and advanced optimization strategies. Collaboration & Integration Work closely with data scientists, engineers, and product teams to embed ML models into real-world applications. Develop APIs and reusable frameworks to simplify model deployment. Communicate findings and translate model outputs into actionable insights. Innovation & Growth Stay ahead of the curve on ML, AI, and deep learning advancements. Propose and implement new approaches to enhance system accuracy and efficiency. Contribute to building a strong foundation of reusable ML tools and best practices. What You’ll Bring Education: Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related field. Experience: 3–5 years in ML engineering, with hands-on model development and deployment. Core Skills: Strong experience with Support Vector Machines (SVM) and other supervised/unsupervised methods. Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Knowledge of statistics, probability, linear algebra, and optimization techniques. Tools & Platforms: Data visualization (Matplotlib, Seaborn, Plotly). Version control (Git). Cloud platforms (AWS, Azure, or GCP). Soft Skills: Analytical mindset, problem-solving, clear communication, and team collaboration. Bonus Points If You Have Experience in deep learning (CNNs, RNNs, Transformers). Exposure to NLP or computer vision projects. Familiarity with large-scale data processing frameworks (Spark, Hadoop).

We are seeking a qualified and detail-oriented Company Secretary cum Legal Associate to join our team. The ideal candidate will be responsible for ensuring the company complies with statutory and regulatory requirements, maintaining corporate governance standards, and providing legal support across all business operations. Key Responsibilities: Incorporation of Companies and LLP from the stage of application and drafting of documents for incorporation till the stage of bringing the company/LLP into running operations; Conversion of Company into LLP, along with the liaising with the Banks, shareholders and the Registrar of Companies of India (hereinafter referred to as “ROC”) for the purpose of obtaining various approvals in the said matter; Inter corporate loan and investment by the companies and LLP and adherence of compliance related to the section 186 of the Companies Act, 2013; Creation of charge in the Company against Issue of Debentures and for general mortgage as per the statutory compliance of Companies Act 2013; Borrowing of loan, funds & advances by the company including advising and assisting Board of Directors and the Finance team for the adherence of the laws under section 180, 185 and section 73 of the Companies Act, 2013 along with Companies Acceptance of Deposit Rules, made thereunder; Complete ROC- Filing, Annual Filling for the companies and LLP for the annual and Quarterly basis compliance; Appointment, Resignation, Change of Designation and Regularization of Directors, KMPs, Auditors & Designated Partners; Amendments in Memorandum of Association, Article of Association & Addendum to LLP Agreement from the inception of the drafting of documents till the approval from the ROC for the said amendments; Taking minutes of Board & General Meeting, drafting resolutions, and filling of required E- forms with ROC; Drafting and Maintaining Statutory Registers of the companies, event base compliance and the documentations of the companies and LLP as per the relevant Law. Qualifications: Qualified Company Secretary (CS) from ICSI. LLB or equivalent legal degree (preferred or mandatory, depending on role). Experience: [2–5+] years of relevant experience in corporate secretarial and legal roles. Skills: Strong understanding of corporate law, regulatory compliance, and company secretarial functions. Excellent drafting, communication, and negotiation skills. Ability to manage multiple tasks and deadlines. Attention to detail with strong organizational skills. Proficient in MS Office and legal/compliance software. ( Our office timings are 10 am to 7pm , 6 days a week. Kindly note the shift is fixed ) Job Type: Full-time Pay: ₹35,000.00 - ₹50,000.00 per month Work Location: In person

This role is for one of our clients Industry: Technology, Information and Media Seniority level: Associate level Min Experience: 3 years Location: Gurugram, Delhi, Uttar Pradesh, NCR, NOIDA, Kanpur, Uttarakhand JobType: full-time We’re looking for a Machine Learning Engineer (3–5 years experience) who is passionate about turning complex data into intelligent, scalable solutions. In this role, you’ll design and deploy machine learning models, optimize algorithms for performance, and collaborate with cross-functional teams to bring AI-powered applications into production. If you thrive in solving challenging problems with real-world impact, this role is for you. What You’ll Do Model Design & Deployment Build and deploy machine learning models that solve business-critical problems. Implement and optimize classification, regression, clustering, and anomaly detection techniques. Ensure models are scalable, efficient, and production-ready. Data Preparation & Feature Engineering Work with structured and unstructured datasets, ensuring quality and usability. Apply feature engineering, dimensionality reduction, and transformation techniques. Perform exploratory data analysis (EDA) to uncover patterns and insights. Algorithm Optimization Experiment with a range of ML techniques — from Support Vector Machines to ensemble methods and deep learning. Fine-tune hyperparameters, validate models, and optimize performance. Apply cross-validation, regularization, and advanced optimization strategies. Collaboration & Integration Work closely with data scientists, engineers, and product teams to embed ML models into real-world applications. Develop APIs and reusable frameworks to simplify model deployment. Communicate findings and translate model outputs into actionable insights. Innovation & Growth Stay ahead of the curve on ML, AI, and deep learning advancements. Propose and implement new approaches to enhance system accuracy and efficiency. Contribute to building a strong foundation of reusable ML tools and best practices. What You’ll Bring Education: Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related field. Experience: 3–5 years in ML engineering, with hands-on model development and deployment. Core Skills: Strong experience with Support Vector Machines (SVM) and other supervised/unsupervised methods. Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Knowledge of statistics, probability, linear algebra, and optimization techniques. Tools & Platforms: Data visualization (Matplotlib, Seaborn, Plotly). Version control (Git). Cloud platforms (AWS, Azure, or GCP). Soft Skills: Analytical mindset, problem-solving, clear communication, and team collaboration. Bonus Points If You Have Experience in deep learning (CNNs, RNNs, Transformers). Exposure to NLP or computer vision projects. Familiarity with large-scale data processing frameworks (Spark, Hadoop).

Job description : ExcelR is seeking experienced AI and Machine Learning trainers to deliver a comprehensive AI and Machine Learning curriculum. The training program will span 40 working days, with daily classes of 5–6 hours, tentatively from August 20, 2025, to October 21, 2025. The role involves teaching theoretical concepts, guiding hands-on projects, and mentoring students on real-world AI/ML applications. Skills Required : Foundational ML: Logistic Regression, SVM, Decision Trees, Ensemble Methods (Bagging, Random Forests), Boosting (Gradient Boosting, AdaBoost, XGBoost, LightGBM), PCA, Clustering (K-means, Hierarchical, DBSCAN), Market Basket Analysis, and Recommendation Systems. Deep Learning: ANN, CNN, RNN, LSTM, GRU, Transformers, GANs, Autoencoders, Diffusion Models (Stable Diffusion), and LLMs (e.g., GPT, BERT). Data Preprocessing: Standardization, normalization, encoding, train-test split, cross-validation, regularization (Lasso, Ridge, ElasticNet), and feature engineering. Generative AI: Text-to-image/audio/video generation, chatbots, sentiment analysis, and Retrieval-Augmented Generation (RAG) with FAISS. Web & Cloud Deployment: Building and deploying RESTful APIs using Flask/FastAPI, cloud computing with AWS (EC2, S3, Lambda) and Azure (Blob, App Services), and Streamlit for project deployment. Mathematics: Calculus, vector algebra, probability. Prompt Engineering: Zero-shot, few-shot, prompt tuning, and designing effective prompts. Case Studies: Hands-on projects (e.g., Bangalore housing prices, Breast cancer classification, Sales dataset). Qualifications : Education: Bachelor’s/Master’s in Computer Science, AI, ML, or related fields. Experience: 3–5 years in Machine Learning, Deep Learning, and Full Stack AI development, with hands-on experience in: Python and libraries like scikit-learn, TensorFlow, Keras, PyTorch. Generative AI (GANs, Diffusion Models, LLMs like GPT-2, LLaMA). Web development (Flask, FastAPI) and cloud deployment (AWS EC2, Azure). Tools like Hugging Face, FAISS, LangChain, and Streamlit. Teaching Skills: Prior teaching/training experience preferred, with the ability to explain complex topics (e.g., attention mechanisms, PCA) to undergraduate students. Certifications: Relevant certifications in AI/ML (e.g., AWS Certified Machine Learning, Google Professional ML Engineer) are a plus.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Software Engineer II We are the global technology company behind the world’s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. The Mastercard Launch program is aimed at early career talent, to help you develop skills and gain cross-functional work experience. Over a period of 18 months, Launch participants will be assigned to a business unit, learn and develop skills, and gain valuable on the job experience. Mastercard has over 2 billion payment cards issued by 25,000+ banks across 190+ countries and territories, amassing over 10 petabytes of data. Millions of transactions are flowing to Mastercard in real-time providing an ideal environment to apply and leverage AI at scale. The AI team is responsible for building and deploying innovative AI solutions for all divisions within Mastercard securing a competitive advantage. Our objectives include achieving operational efficiency, improving customer experience, and ensuring robust value propositions of our core products (Credit, Debit, Prepaid) and services (recommendation engine, anti-money laundering, fraud risk management, cybersecurity) Role Gather relevant information to define the business problem Creative thinker capable of linking AI methodologies to identified business challenges Develop AI/ML applications leveraging the latest industry and academic advancements Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda All About You : Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Concentration in Computer Science Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Software Engineer II We are the global technology company behind the world’s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. The Mastercard Launch program is aimed at early career talent, to help you develop skills and gain cross-functional work experience. Over a period of 18 months, Launch participants will be assigned to a business unit, learn and develop skills, and gain valuable on the job experience. Mastercard has over 2 billion payment cards issued by 25,000+ banks across 190+ countries and territories, amassing over 10 petabytes of data. Millions of transactions are flowing to Mastercard in real-time providing an ideal environment to apply and leverage AI at scale. The AI team is responsible for building and deploying innovative AI solutions for all divisions within Mastercard securing a competitive advantage. Our objectives include achieving operational efficiency, improving customer experience, and ensuring robust value propositions of our core products (Credit, Debit, Prepaid) and services (recommendation engine, anti-money laundering, fraud risk management, cybersecurity) Role Gather relevant information to define the business problem Creative thinker capable of linking AI methodologies to identified business challenges Develop AI/ML applications leveraging the latest industry and academic advancements Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda All About You : Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Concentration in Computer Science Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

This role is for one of our clients Industry: Technology, Information and Media Seniority level: Associate level Min Experience: 3 years Location: Gurugram, Delhi, Uttar Pradesh, NCR, NOIDA, Kanpur, Uttarakhand JobType: full-time We’re looking for a Machine Learning Engineer (3–5 years experience) who is passionate about turning complex data into intelligent, scalable solutions. In this role, you’ll design and deploy machine learning models, optimize algorithms for performance, and collaborate with cross-functional teams to bring AI-powered applications into production. If you thrive in solving challenging problems with real-world impact, this role is for you. What You’ll Do Model Design & Deployment Build and deploy machine learning models that solve business-critical problems. Implement and optimize classification, regression, clustering, and anomaly detection techniques. Ensure models are scalable, efficient, and production-ready. Data Preparation & Feature Engineering Work with structured and unstructured datasets, ensuring quality and usability. Apply feature engineering, dimensionality reduction, and transformation techniques. Perform exploratory data analysis (EDA) to uncover patterns and insights. Algorithm Optimization Experiment with a range of ML techniques — from Support Vector Machines to ensemble methods and deep learning. Fine-tune hyperparameters, validate models, and optimize performance. Apply cross-validation, regularization, and advanced optimization strategies. Collaboration & Integration Work closely with data scientists, engineers, and product teams to embed ML models into real-world applications. Develop APIs and reusable frameworks to simplify model deployment. Communicate findings and translate model outputs into actionable insights. Innovation & Growth Stay ahead of the curve on ML, AI, and deep learning advancements. Propose and implement new approaches to enhance system accuracy and efficiency. Contribute to building a strong foundation of reusable ML tools and best practices. What You’ll Bring Education: Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related field. Experience: 3–5 years in ML engineering, with hands-on model development and deployment. Core Skills: Strong experience with Support Vector Machines (SVM) and other supervised/unsupervised methods. Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Knowledge of statistics, probability, linear algebra, and optimization techniques. Tools & Platforms: Data visualization (Matplotlib, Seaborn, Plotly). Version control (Git). Cloud platforms (AWS, Azure, or GCP). Soft Skills: Analytical mindset, problem-solving, clear communication, and team collaboration. Bonus Points If You Have Experience in deep learning (CNNs, RNNs, Transformers). Exposure to NLP or computer vision projects. Familiarity with large-scale data processing frameworks (Spark, Hadoop).

This role is for one of our clients Industry: Technology, Information and Media Seniority level: Associate level Min Experience: 3 years Location: Gurugram, Delhi, Uttar Pradesh, NCR, NOIDA, Kanpur, Uttarakhand JobType: full-time We’re looking for a Machine Learning Engineer (3–5 years experience) who is passionate about turning complex data into intelligent, scalable solutions. In this role, you’ll design and deploy machine learning models, optimize algorithms for performance, and collaborate with cross-functional teams to bring AI-powered applications into production. If you thrive in solving challenging problems with real-world impact, this role is for you. What You’ll Do Model Design & Deployment Build and deploy machine learning models that solve business-critical problems. Implement and optimize classification, regression, clustering, and anomaly detection techniques. Ensure models are scalable, efficient, and production-ready. Data Preparation & Feature Engineering Work with structured and unstructured datasets, ensuring quality and usability. Apply feature engineering, dimensionality reduction, and transformation techniques. Perform exploratory data analysis (EDA) to uncover patterns and insights. Algorithm Optimization Experiment with a range of ML techniques — from Support Vector Machines to ensemble methods and deep learning. Fine-tune hyperparameters, validate models, and optimize performance. Apply cross-validation, regularization, and advanced optimization strategies. Collaboration & Integration Work closely with data scientists, engineers, and product teams to embed ML models into real-world applications. Develop APIs and reusable frameworks to simplify model deployment. Communicate findings and translate model outputs into actionable insights. Innovation & Growth Stay ahead of the curve on ML, AI, and deep learning advancements. Propose and implement new approaches to enhance system accuracy and efficiency. Contribute to building a strong foundation of reusable ML tools and best practices. What You’ll Bring Education: Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related field. Experience: 3–5 years in ML engineering, with hands-on model development and deployment. Core Skills: Strong experience with Support Vector Machines (SVM) and other supervised/unsupervised methods. Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Knowledge of statistics, probability, linear algebra, and optimization techniques. Tools & Platforms: Data visualization (Matplotlib, Seaborn, Plotly). Version control (Git). Cloud platforms (AWS, Azure, or GCP). Soft Skills: Analytical mindset, problem-solving, clear communication, and team collaboration. Bonus Points If You Have Experience in deep learning (CNNs, RNNs, Transformers). Exposure to NLP or computer vision projects. Familiarity with large-scale data processing frameworks (Spark, Hadoop).

This role is for one of our clients Industry: Technology, Information and Media Seniority level: Associate level Min Experience: 3 years Location: Gurugram, Delhi, Uttar Pradesh, NCR, NOIDA, Kanpur, Uttarakhand JobType: full-time We’re looking for a Machine Learning Engineer (3–5 years experience) who is passionate about turning complex data into intelligent, scalable solutions. In this role, you’ll design and deploy machine learning models, optimize algorithms for performance, and collaborate with cross-functional teams to bring AI-powered applications into production. If you thrive in solving challenging problems with real-world impact, this role is for you. What You’ll Do Model Design & Deployment Build and deploy machine learning models that solve business-critical problems. Implement and optimize classification, regression, clustering, and anomaly detection techniques. Ensure models are scalable, efficient, and production-ready. Data Preparation & Feature Engineering Work with structured and unstructured datasets, ensuring quality and usability. Apply feature engineering, dimensionality reduction, and transformation techniques. Perform exploratory data analysis (EDA) to uncover patterns and insights. Algorithm Optimization Experiment with a range of ML techniques — from Support Vector Machines to ensemble methods and deep learning. Fine-tune hyperparameters, validate models, and optimize performance. Apply cross-validation, regularization, and advanced optimization strategies. Collaboration & Integration Work closely with data scientists, engineers, and product teams to embed ML models into real-world applications. Develop APIs and reusable frameworks to simplify model deployment. Communicate findings and translate model outputs into actionable insights. Innovation & Growth Stay ahead of the curve on ML, AI, and deep learning advancements. Propose and implement new approaches to enhance system accuracy and efficiency. Contribute to building a strong foundation of reusable ML tools and best practices. What You’ll Bring Education: Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related field. Experience: 3–5 years in ML engineering, with hands-on model development and deployment. Core Skills: Strong experience with Support Vector Machines (SVM) and other supervised/unsupervised methods. Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Knowledge of statistics, probability, linear algebra, and optimization techniques. Tools & Platforms: Data visualization (Matplotlib, Seaborn, Plotly). Version control (Git). Cloud platforms (AWS, Azure, or GCP). Soft Skills: Analytical mindset, problem-solving, clear communication, and team collaboration. Bonus Points If You Have Experience in deep learning (CNNs, RNNs, Transformers). Exposure to NLP or computer vision projects. Familiarity with large-scale data processing frameworks (Spark, Hadoop).

This role is for one of our clients Industry: Technology, Information and Media Seniority level: Associate level Min Experience: 3 years Location: Gurugram, Delhi, Uttar Pradesh, NCR, NOIDA, Kanpur, Uttarakhand JobType: full-time We’re looking for a Machine Learning Engineer (3–5 years experience) who is passionate about turning complex data into intelligent, scalable solutions. In this role, you’ll design and deploy machine learning models, optimize algorithms for performance, and collaborate with cross-functional teams to bring AI-powered applications into production. If you thrive in solving challenging problems with real-world impact, this role is for you. What You’ll Do Model Design & Deployment Build and deploy machine learning models that solve business-critical problems. Implement and optimize classification, regression, clustering, and anomaly detection techniques. Ensure models are scalable, efficient, and production-ready. Data Preparation & Feature Engineering Work with structured and unstructured datasets, ensuring quality and usability. Apply feature engineering, dimensionality reduction, and transformation techniques. Perform exploratory data analysis (EDA) to uncover patterns and insights. Algorithm Optimization Experiment with a range of ML techniques — from Support Vector Machines to ensemble methods and deep learning. Fine-tune hyperparameters, validate models, and optimize performance. Apply cross-validation, regularization, and advanced optimization strategies. Collaboration & Integration Work closely with data scientists, engineers, and product teams to embed ML models into real-world applications. Develop APIs and reusable frameworks to simplify model deployment. Communicate findings and translate model outputs into actionable insights. Innovation & Growth Stay ahead of the curve on ML, AI, and deep learning advancements. Propose and implement new approaches to enhance system accuracy and efficiency. Contribute to building a strong foundation of reusable ML tools and best practices. What You’ll Bring Education: Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related field. Experience: 3–5 years in ML engineering, with hands-on model development and deployment. Core Skills: Strong experience with Support Vector Machines (SVM) and other supervised/unsupervised methods. Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Knowledge of statistics, probability, linear algebra, and optimization techniques. Tools & Platforms: Data visualization (Matplotlib, Seaborn, Plotly). Version control (Git). Cloud platforms (AWS, Azure, or GCP). Soft Skills: Analytical mindset, problem-solving, clear communication, and team collaboration. Bonus Points If You Have Experience in deep learning (CNNs, RNNs, Transformers). Exposure to NLP or computer vision projects. Familiarity with large-scale data processing frameworks (Spark, Hadoop).

This role is for one of our clients Industry: Technology, Information and Media Seniority level: Associate level Min Experience: 3 years Location: Gurugram, Delhi, Uttar Pradesh, NCR, NOIDA, Kanpur, Uttarakhand JobType: full-time We’re looking for a Machine Learning Engineer (3–5 years experience) who is passionate about turning complex data into intelligent, scalable solutions. In this role, you’ll design and deploy machine learning models, optimize algorithms for performance, and collaborate with cross-functional teams to bring AI-powered applications into production. If you thrive in solving challenging problems with real-world impact, this role is for you. What You’ll Do Model Design & Deployment Build and deploy machine learning models that solve business-critical problems. Implement and optimize classification, regression, clustering, and anomaly detection techniques. Ensure models are scalable, efficient, and production-ready. Data Preparation & Feature Engineering Work with structured and unstructured datasets, ensuring quality and usability. Apply feature engineering, dimensionality reduction, and transformation techniques. Perform exploratory data analysis (EDA) to uncover patterns and insights. Algorithm Optimization Experiment with a range of ML techniques — from Support Vector Machines to ensemble methods and deep learning. Fine-tune hyperparameters, validate models, and optimize performance. Apply cross-validation, regularization, and advanced optimization strategies. Collaboration & Integration Work closely with data scientists, engineers, and product teams to embed ML models into real-world applications. Develop APIs and reusable frameworks to simplify model deployment. Communicate findings and translate model outputs into actionable insights. Innovation & Growth Stay ahead of the curve on ML, AI, and deep learning advancements. Propose and implement new approaches to enhance system accuracy and efficiency. Contribute to building a strong foundation of reusable ML tools and best practices. What You’ll Bring Education: Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related field. Experience: 3–5 years in ML engineering, with hands-on model development and deployment. Core Skills: Strong experience with Support Vector Machines (SVM) and other supervised/unsupervised methods. Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Knowledge of statistics, probability, linear algebra, and optimization techniques. Tools & Platforms: Data visualization (Matplotlib, Seaborn, Plotly). Version control (Git). Cloud platforms (AWS, Azure, or GCP). Soft Skills: Analytical mindset, problem-solving, clear communication, and team collaboration. Bonus Points If You Have Experience in deep learning (CNNs, RNNs, Transformers). Exposure to NLP or computer vision projects. Familiarity with large-scale data processing frameworks (Spark, Hadoop).

This role is for one of our clients Industry: Technology, Information and Media Seniority level: Associate level Min Experience: 3 years Location: Gurugram, Delhi, Uttar Pradesh, NCR, NOIDA, Kanpur, Uttarakhand JobType: full-time We’re looking for a Machine Learning Engineer (3–5 years experience) who is passionate about turning complex data into intelligent, scalable solutions. In this role, you’ll design and deploy machine learning models, optimize algorithms for performance, and collaborate with cross-functional teams to bring AI-powered applications into production. If you thrive in solving challenging problems with real-world impact, this role is for you. What You’ll Do Model Design & Deployment Build and deploy machine learning models that solve business-critical problems. Implement and optimize classification, regression, clustering, and anomaly detection techniques. Ensure models are scalable, efficient, and production-ready. Data Preparation & Feature Engineering Work with structured and unstructured datasets, ensuring quality and usability. Apply feature engineering, dimensionality reduction, and transformation techniques. Perform exploratory data analysis (EDA) to uncover patterns and insights. Algorithm Optimization Experiment with a range of ML techniques — from Support Vector Machines to ensemble methods and deep learning. Fine-tune hyperparameters, validate models, and optimize performance. Apply cross-validation, regularization, and advanced optimization strategies. Collaboration & Integration Work closely with data scientists, engineers, and product teams to embed ML models into real-world applications. Develop APIs and reusable frameworks to simplify model deployment. Communicate findings and translate model outputs into actionable insights. Innovation & Growth Stay ahead of the curve on ML, AI, and deep learning advancements. Propose and implement new approaches to enhance system accuracy and efficiency. Contribute to building a strong foundation of reusable ML tools and best practices. What You’ll Bring Education: Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related field. Experience: 3–5 years in ML engineering, with hands-on model development and deployment. Core Skills: Strong experience with Support Vector Machines (SVM) and other supervised/unsupervised methods. Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Knowledge of statistics, probability, linear algebra, and optimization techniques. Tools & Platforms: Data visualization (Matplotlib, Seaborn, Plotly). Version control (Git). Cloud platforms (AWS, Azure, or GCP). Soft Skills: Analytical mindset, problem-solving, clear communication, and team collaboration. Bonus Points If You Have Experience in deep learning (CNNs, RNNs, Transformers). Exposure to NLP or computer vision projects. Familiarity with large-scale data processing frameworks (Spark, Hadoop).

This role is for one of our clients Industry: Technology, Information and Media Seniority level: Associate level Min Experience: 3 years Location: Gurugram, Delhi, Uttar Pradesh, NCR, NOIDA, Kanpur, Uttarakhand JobType: full-time We’re looking for a Machine Learning Engineer (3–5 years experience) who is passionate about turning complex data into intelligent, scalable solutions. In this role, you’ll design and deploy machine learning models, optimize algorithms for performance, and collaborate with cross-functional teams to bring AI-powered applications into production. If you thrive in solving challenging problems with real-world impact, this role is for you. What You’ll Do Model Design & Deployment Build and deploy machine learning models that solve business-critical problems. Implement and optimize classification, regression, clustering, and anomaly detection techniques. Ensure models are scalable, efficient, and production-ready. Data Preparation & Feature Engineering Work with structured and unstructured datasets, ensuring quality and usability. Apply feature engineering, dimensionality reduction, and transformation techniques. Perform exploratory data analysis (EDA) to uncover patterns and insights. Algorithm Optimization Experiment with a range of ML techniques — from Support Vector Machines to ensemble methods and deep learning. Fine-tune hyperparameters, validate models, and optimize performance. Apply cross-validation, regularization, and advanced optimization strategies. Collaboration & Integration Work closely with data scientists, engineers, and product teams to embed ML models into real-world applications. Develop APIs and reusable frameworks to simplify model deployment. Communicate findings and translate model outputs into actionable insights. Innovation & Growth Stay ahead of the curve on ML, AI, and deep learning advancements. Propose and implement new approaches to enhance system accuracy and efficiency. Contribute to building a strong foundation of reusable ML tools and best practices. What You’ll Bring Education: Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related field. Experience: 3–5 years in ML engineering, with hands-on model development and deployment. Core Skills: Strong experience with Support Vector Machines (SVM) and other supervised/unsupervised methods. Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Knowledge of statistics, probability, linear algebra, and optimization techniques. Tools & Platforms: Data visualization (Matplotlib, Seaborn, Plotly). Version control (Git). Cloud platforms (AWS, Azure, or GCP). Soft Skills: Analytical mindset, problem-solving, clear communication, and team collaboration. Bonus Points If You Have Experience in deep learning (CNNs, RNNs, Transformers). Exposure to NLP or computer vision projects. Familiarity with large-scale data processing frameworks (Spark, Hadoop).

Company Description Blend is building a scalable Media Mix Optimization (MMO) solution designed to help clients maximize the impact of their marketing investments. We are seeking a Data Scientist with strong expertise in media mix modeling, statistical modeling, and interactive application development to join our advanced analytics team. This role goes beyond model building you will design, implement, and productionize end-to-end solutions that integrate statistical rigor with business impact. The ideal candidate will have deep knowledge of marketing analytics, advanced Python skills, and hands-on experience with Streamlit or similar frameworks for interactive data applications. You will be central in creating robust pipelines, experimentation frameworks, and client-facing tools that directly inform media allocation decisions. Job Description Our MMO platform is an in-house initiative designed to empower clients with data-driven decision-making in marketing strategy. By applying Bayesian and frequentist approaches to media mix modeling , we are able to quantify channel-level ROI, measure incrementality, and simulate outcomes under varying spend scenarios. Key Components Of The Project Include Data Integration: Combining client first-party, third-party, and campaign-level data across digital, offline, and emerging channels into a unified modeling framework. Model Development: Building and validating media mix models (MMM) using advanced statistical and machine learning techniques such as hierarchical Bayesian regression, regularized regression (Ridge/Lasso), and time-series modeling. Scenario Simulation: Enabling stakeholders to forecast outcomes under different budget allocations through simulation and optimization algorithms. Deployment & Visualization: Using Streamlit to build interactive, client-facing dashboards for model exploration, scenario planning, and actionable recommendation delivery. Scalability: Engineering the system to support multiple clients across industries with varying data volumes, refresh cycles, and modeling complexities. Responsibilities Develop, validate, and maintain media mix models to evaluate cross-channel marketing effectiveness and return on investment. Engineer and optimize end-to-end data pipelines for ingesting, cleaning, and structuring large, heterogeneous datasets from multiple marketing and business sources. Design, build, and deploy Streamlit-based interactive dashboards and applications for scenario testing, optimization, and reporting. Conduct exploratory data analysis (EDA) and advanced feature engineering to identify drivers of performance. Apply Bayesian methods, regularization, and time-series analysis to improve model accuracy, stability, and interpretability. Implement optimization and scenario-planning algorithms to recommend budget allocation strategies that maximize business outcomes. Collaborate closely with product, engineering, and client teams to align technical solutions with business objectives. Present insights and recommendations to senior stakeholders in both technical and non- technical language. Stay current with emerging tools, techniques, and best practices in media mix modeling, causal inference, and marketing science. Qualifications Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Applied Mathematics, or related field. Proven hands-on experience in media mix modeling, marketing analytics, or econometrics. Strong proficiency in Python and key data science libraries (pandas, NumPy, scikit-learn, statsmodels, PyMC or similar Bayesian frameworks). Experience with Streamlit or equivalent frameworks (Dash, Shiny) for building data- driven applications. Proficiency in SQL for querying, joining, and optimizing large-scale datasets. Solid foundation in statistical modeling, regression techniques, and machine learning. Strong problem-solving skills with the ability to structure ambiguous business problems into data-driven solutions. Excellent verbal and written communication skills to translate technical outputs into business decisions. Preferred Qualifications Experience with Bayesian hierarchical models, time-series decomposition, and marketing attribution approaches. Familiarity with cloud-based platforms (AWS, GCP, Azure) for data processing, model training, and deployment. Experience with data visualization tools beyond Streamlit (Tableau, Power BI, D3.js, Plotly). Exposure to big data ecosystems (Spark, Hadoop) for large-scale data processing. Knowledge of causal inference techniques (propensity scoring, uplift modeling, geo- experiments).

This role is for one of the Weekday's clients Min Experience: 3 years Location: Gurugram, Delhi, Uttar Pradesh, NCR, NOIDA, Kanpur, Uttarakhand JobType: full-time We are seeking a highly skilled and motivated Machine Learning Engineer with 3-5 years of hands-on experience to join our growing team. The ideal candidate will have strong expertise in designing, developing, and deploying machine learning models, with a particular focus on Support Vector Machines (SVM) and other supervised and unsupervised learning techniques. This role involves working on large-scale datasets, building predictive models, optimizing algorithms, and collaborating with cross-functional teams to deliver cutting-edge AI-driven solutions. Requirements Key Responsibilities Model Development & Deployment: Design, build, and deploy machine learning models tailored to real-world business problems. Implement and optimize Support Vector Machine (SVM) algorithms for classification, regression, and anomaly detection tasks. Ensure scalability and performance of deployed models in production environments. Data Management & Preprocessing: Work with structured and unstructured datasets to prepare clean, usable data for training. Apply feature engineering, dimensionality reduction, and data transformation techniques to improve model accuracy and efficiency. Conduct exploratory data analysis (EDA) to identify patterns, trends, and data insights. Algorithm Optimization: Experiment with various machine learning algorithms beyond SVM, including decision trees, ensemble methods, clustering, and neural networks. Fine-tune hyperparameters, optimize model performance, and validate results using rigorous statistical methods. Leverage techniques such as cross-validation, regularization, and kernel methods to enhance accuracy. Collaboration & Integration: Partner with data scientists, software engineers, and product teams to integrate machine learning solutions into business applications. Translate complex machine learning outputs into actionable insights for stakeholders. Support the creation of APIs and frameworks for easy deployment of ML models. Continuous Improvement: Stay updated with the latest advancements in machine learning, deep learning, and AI research. Explore novel approaches to enhance existing systems and processes. Contribute to building reusable ML components and maintaining best practices. Required Skills & Qualifications Education: Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or related field. Experience: 3-5 years of professional experience in machine learning engineering. Core Expertise: Strong understanding and practical experience with Support Vector Machines (SVM). Solid knowledge of supervised and unsupervised learning techniques, classification, regression, and clustering. Programming & Tools: Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, etc.). Experience with data visualization tools (Matplotlib, Seaborn, Plotly). Familiarity with version control systems (Git) and cloud platforms (AWS, Azure, or GCP). Analytical Skills: Strong background in statistics, linear algebra, probability, and optimization techniques. Soft Skills: Excellent problem-solving abilities, analytical thinking, communication, and teamwork. Preferred Qualifications Experience with deep learning frameworks. Exposure to natural language processing (NLP) or computer vision projects. Familiarity with large-scale data processing frameworks like Spark or Hadoop

This role is for one of the Weekday's clients Min Experience: 3 years Location: Gurugram, Delhi, Uttar Pradesh, NCR, NOIDA, Kanpur, Uttarakhand JobType: full-time We are seeking a highly skilled and motivated Machine Learning Engineer with 3-5 years of hands-on experience to join our growing team. The ideal candidate will have strong expertise in designing, developing, and deploying machine learning models, with a particular focus on Support Vector Machines (SVM) and other supervised and unsupervised learning techniques. This role involves working on large-scale datasets, building predictive models, optimizing algorithms, and collaborating with cross-functional teams to deliver cutting-edge AI-driven solutions. Requirements Key Responsibilities Model Development & Deployment: Design, build, and deploy machine learning models tailored to real-world business problems. Implement and optimize Support Vector Machine (SVM) algorithms for classification, regression, and anomaly detection tasks. Ensure scalability and performance of deployed models in production environments. Data Management & Preprocessing: Work with structured and unstructured datasets to prepare clean, usable data for training. Apply feature engineering, dimensionality reduction, and data transformation techniques to improve model accuracy and efficiency. Conduct exploratory data analysis (EDA) to identify patterns, trends, and data insights. Algorithm Optimization: Experiment with various machine learning algorithms beyond SVM, including decision trees, ensemble methods, clustering, and neural networks. Fine-tune hyperparameters, optimize model performance, and validate results using rigorous statistical methods. Leverage techniques such as cross-validation, regularization, and kernel methods to enhance accuracy. Collaboration & Integration: Partner with data scientists, software engineers, and product teams to integrate machine learning solutions into business applications. Translate complex machine learning outputs into actionable insights for stakeholders. Support the creation of APIs and frameworks for easy deployment of ML models. Continuous Improvement: Stay updated with the latest advancements in machine learning, deep learning, and AI research. Explore novel approaches to enhance existing systems and processes. Contribute to building reusable ML components and maintaining best practices. Required Skills & Qualifications Education: Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or related field. Experience: 3-5 years of professional experience in machine learning engineering. Core Expertise: Strong understanding and practical experience with Support Vector Machines (SVM). Solid knowledge of supervised and unsupervised learning techniques, classification, regression, and clustering. Programming & Tools: Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, etc.). Experience with data visualization tools (Matplotlib, Seaborn, Plotly). Familiarity with version control systems (Git) and cloud platforms (AWS, Azure, or GCP). Analytical Skills: Strong background in statistics, linear algebra, probability, and optimization techniques. Soft Skills: Excellent problem-solving abilities, analytical thinking, communication, and teamwork. Preferred Qualifications Experience with deep learning frameworks. Exposure to natural language processing (NLP) or computer vision projects. Familiarity with large-scale data processing frameworks like Spark or Hadoop

This role is for one of the Weekday's clients Min Experience: 3 years Location: Gurugram, Delhi, Uttar Pradesh, NCR, NOIDA, Kanpur, Uttarakhand JobType: full-time We are seeking a highly skilled and motivated Machine Learning Engineer with 3-5 years of hands-on experience to join our growing team. The ideal candidate will have strong expertise in designing, developing, and deploying machine learning models, with a particular focus on Support Vector Machines (SVM) and other supervised and unsupervised learning techniques. This role involves working on large-scale datasets, building predictive models, optimizing algorithms, and collaborating with cross-functional teams to deliver cutting-edge AI-driven solutions. Requirements Key Responsibilities Model Development & Deployment: Design, build, and deploy machine learning models tailored to real-world business problems. Implement and optimize Support Vector Machine (SVM) algorithms for classification, regression, and anomaly detection tasks. Ensure scalability and performance of deployed models in production environments. Data Management & Preprocessing: Work with structured and unstructured datasets to prepare clean, usable data for training. Apply feature engineering, dimensionality reduction, and data transformation techniques to improve model accuracy and efficiency. Conduct exploratory data analysis (EDA) to identify patterns, trends, and data insights. Algorithm Optimization: Experiment with various machine learning algorithms beyond SVM, including decision trees, ensemble methods, clustering, and neural networks. Fine-tune hyperparameters, optimize model performance, and validate results using rigorous statistical methods. Leverage techniques such as cross-validation, regularization, and kernel methods to enhance accuracy. Collaboration & Integration: Partner with data scientists, software engineers, and product teams to integrate machine learning solutions into business applications. Translate complex machine learning outputs into actionable insights for stakeholders. Support the creation of APIs and frameworks for easy deployment of ML models. Continuous Improvement: Stay updated with the latest advancements in machine learning, deep learning, and AI research. Explore novel approaches to enhance existing systems and processes. Contribute to building reusable ML components and maintaining best practices. Required Skills & Qualifications Education: Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or related field. Experience: 3-5 years of professional experience in machine learning engineering. Core Expertise: Strong understanding and practical experience with Support Vector Machines (SVM). Solid knowledge of supervised and unsupervised learning techniques, classification, regression, and clustering. Programming & Tools: Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, etc.). Experience with data visualization tools (Matplotlib, Seaborn, Plotly). Familiarity with version control systems (Git) and cloud platforms (AWS, Azure, or GCP). Analytical Skills: Strong background in statistics, linear algebra, probability, and optimization techniques. Soft Skills: Excellent problem-solving abilities, analytical thinking, communication, and teamwork. Preferred Qualifications Experience with deep learning frameworks. Exposure to natural language processing (NLP) or computer vision projects. Familiarity with large-scale data processing frameworks like Spark or Hadoop

This role is for one of the Weekday's clients Min Experience: 3 years Location: Gurugram, Delhi, Uttar Pradesh, NCR, NOIDA, Kanpur, Uttarakhand JobType: full-time We are seeking a highly skilled and motivated Machine Learning Engineer with 3-5 years of hands-on experience to join our growing team. The ideal candidate will have strong expertise in designing, developing, and deploying machine learning models, with a particular focus on Support Vector Machines (SVM) and other supervised and unsupervised learning techniques. This role involves working on large-scale datasets, building predictive models, optimizing algorithms, and collaborating with cross-functional teams to deliver cutting-edge AI-driven solutions. Requirements Key Responsibilities Model Development & Deployment: Design, build, and deploy machine learning models tailored to real-world business problems. Implement and optimize Support Vector Machine (SVM) algorithms for classification, regression, and anomaly detection tasks. Ensure scalability and performance of deployed models in production environments. Data Management & Preprocessing: Work with structured and unstructured datasets to prepare clean, usable data for training. Apply feature engineering, dimensionality reduction, and data transformation techniques to improve model accuracy and efficiency. Conduct exploratory data analysis (EDA) to identify patterns, trends, and data insights. Algorithm Optimization: Experiment with various machine learning algorithms beyond SVM, including decision trees, ensemble methods, clustering, and neural networks. Fine-tune hyperparameters, optimize model performance, and validate results using rigorous statistical methods. Leverage techniques such as cross-validation, regularization, and kernel methods to enhance accuracy. Collaboration & Integration: Partner with data scientists, software engineers, and product teams to integrate machine learning solutions into business applications. Translate complex machine learning outputs into actionable insights for stakeholders. Support the creation of APIs and frameworks for easy deployment of ML models. Continuous Improvement: Stay updated with the latest advancements in machine learning, deep learning, and AI research. Explore novel approaches to enhance existing systems and processes. Contribute to building reusable ML components and maintaining best practices. Required Skills & Qualifications Education: Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or related field. Experience: 3-5 years of professional experience in machine learning engineering. Core Expertise: Strong understanding and practical experience with Support Vector Machines (SVM). Solid knowledge of supervised and unsupervised learning techniques, classification, regression, and clustering. Programming & Tools: Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, etc.). Experience with data visualization tools (Matplotlib, Seaborn, Plotly). Familiarity with version control systems (Git) and cloud platforms (AWS, Azure, or GCP). Analytical Skills: Strong background in statistics, linear algebra, probability, and optimization techniques. Soft Skills: Excellent problem-solving abilities, analytical thinking, communication, and teamwork. Preferred Qualifications Experience with deep learning frameworks. Exposure to natural language processing (NLP) or computer vision projects. Familiarity with large-scale data processing frameworks like Spark or Hadoop

Job description : ExcelR is seeking experienced AI and Machine Learning trainers to deliver a comprehensive AI and Machine Learning curriculum. The training program will span 40 working days, with daily classes of 5–6 hours, tentatively from August 20, 2025, to October 21, 2025. The role involves teaching theoretical concepts, guiding hands-on projects, and mentoring students on real-world AI/ML applications. Skills Required : Foundational ML: Logistic Regression, SVM, Decision Trees, Ensemble Methods (Bagging, Random Forests), Boosting (Gradient Boosting, AdaBoost, XGBoost, LightGBM), PCA, Clustering (K-means, Hierarchical, DBSCAN), Market Basket Analysis, and Recommendation Systems. Deep Learning: ANN, CNN, RNN, LSTM, GRU, Transformers, GANs, Autoencoders, Diffusion Models (Stable Diffusion), and LLMs (e.g., GPT, BERT). Data Preprocessing: Standardization, normalization, encoding, train-test split, cross-validation, regularization (Lasso, Ridge, ElasticNet), and feature engineering. Generative AI: Text-to-image/audio/video generation, chatbots, sentiment analysis, and Retrieval-Augmented Generation (RAG) with FAISS. Web & Cloud Deployment: Building and deploying RESTful APIs using Flask/FastAPI, cloud computing with AWS (EC2, S3, Lambda) and Azure (Blob, App Services), and Streamlit for project deployment. Mathematics: Calculus, vector algebra, probability. Prompt Engineering: Zero-shot, few-shot, prompt tuning, and designing effective prompts. Case Studies: Hands-on projects (e.g., Bangalore housing prices, Breast cancer classification, Sales dataset). Qualifications : Education: Bachelor’s/Master’s in Computer Science, AI, ML, or related fields. Experience: 3–5 years in Machine Learning, Deep Learning, and Full Stack AI development, with hands-on experience in: Python and libraries like scikit-learn, TensorFlow, Keras, PyTorch. Generative AI (GANs, Diffusion Models, LLMs like GPT-2, LLaMA). Web development (Flask, FastAPI) and cloud deployment (AWS EC2, Azure). Tools like Hugging Face, FAISS, LangChain, and Streamlit. Teaching Skills: Prior teaching/training experience preferred, with the ability to explain complex topics (e.g., attention mechanisms, PCA) to undergraduate students. Certifications: Relevant certifications in AI/ML (e.g., AWS Certified Machine Learning, Google Professional ML Engineer) are a plus.

Product benchmarking and application development for existing product, modified product and new product related to Paints, construction & coatings product portfolio. Benchmarking of competition products in lab for finding USP of Archroma product for value selling. Replication of lab results in customer trials for product approval and commercialization Brainstorming on product related issues to satisfy customer and regularization of product supply. Vendor development as and when require for new materials with procurement team. Lab development and commissioning of the new equipment and their maintenance by following safety

About GITAA: GITAA, an IIT Madras incubated company, is founded by experienced academics from the Indian Institute of Technology, Madras. Our founders bring in a wealth of expertise and knowledge in data science and engineering disciplines. GITAA is a leading provider of edtech solutions, training and technology consulting services. At GITAA , we design and deliver industry-grade AI/ML programs. Trainers teach using applied cases, hands-on labs, and capstones aligned to real project execution—while collaborating with our consultancy team that ships end-to-end AI/ML solutions. We teach teams at the CAG (Comptroller and Auditor General of India), ministries, and MNCs, and have developed training materials across multiple domains. Delivery formats include online, in-person, workshops, and certified offerings; learners range from corporate cohorts and government officials to students. Job Description: We are looking for a Junior Python and Data Science Trainer with a strong foundation in Python, and a genuine interest in Data Science and Machine Learning. In this role, you will contribute to the development of training content, support the facilitation of training sessions, and assist in coordinating all related training activities. Responsibilities: Conduct engaging training sessions in Python programming, data science, and machine learning topics. Develop training content including case studies, assignments, and assessments. Manage and update content on the LMS platform. Maintain effective communication with students and training stakeholders. Track and report learner progress and feedback to the management team. Stay up to date with developments in the data science domain. Qualifications: M.Sc. in Data Science, or B.E. with a strong foundation in Python and machine learning. Minimum of 1–2 years of experience as a Data Science Trainer (referrals preferred). Required Skills: Proficiency in Python, ML algorithms, and data visualization tools like Tableau or Power BI. Strong foundational in statistics, linear algebra, and ML techniques. Effective verbal and written communication and presentation skills. Good interpersonal skills; ability to connect with students and motivate them. Basic LMS familiarity (publishing content, tracking cohorts) and comfort with version control (Git) is a plus. LLM/GenAI: prompts, embeddings, RAG, fine-tuning/PEFT, evaluation & safety. AI algorithms & foundations beyond the basics: regularization, ensembles, search/optimization heuristics. Willingness to travel and take on new challenges as required. What We Offer: Hands-on opportunities to train learners in Python programming, data science, and machine learning. Opportunity to collaborate with and learn from IITM professors and domain experts in data science and AI. Involvement in curriculum design, content development, and innovative tech-driven learning solutions. Salary: To be determined based on experience and qualifications. Interested candidates may send their resume to: 📧admin@gitaa.in 📧shreenithiya@gitaa.in To know more about us, visit gitaa.in

Job description : ExcelR is seeking experienced AI and Machine Learning trainers to deliver a comprehensive AI and Machine Learning curriculum. The training program will span 40 working days, with daily classes of 5–6 hours, tentatively from August 20, 2025, to October 21, 2025. The role involves teaching theoretical concepts, guiding hands-on projects, and mentoring students on real-world AI/ML applications. Skills Required : Foundational ML: Logistic Regression, SVM, Decision Trees, Ensemble Methods (Bagging, Random Forests), Boosting (Gradient Boosting, AdaBoost, XGBoost, LightGBM), PCA, Clustering (K-means, Hierarchical, DBSCAN), Market Basket Analysis, and Recommendation Systems. Deep Learning: ANN, CNN, RNN, LSTM, GRU, Transformers, GANs, Autoencoders, Diffusion Models (Stable Diffusion), and LLMs (e.g., GPT, BERT). Data Preprocessing: Standardization, normalization, encoding, train-test split, cross-validation, regularization (Lasso, Ridge, ElasticNet), and feature engineering. Generative AI: Text-to-image/audio/video generation, chatbots, sentiment analysis, and Retrieval-Augmented Generation (RAG) with FAISS. Web & Cloud Deployment: Building and deploying RESTful APIs using Flask/FastAPI, cloud computing with AWS (EC2, S3, Lambda) and Azure (Blob, App Services), and Streamlit for project deployment. Mathematics: Calculus, vector algebra, probability. Prompt Engineering: Zero-shot, few-shot, prompt tuning, and designing effective prompts. Case Studies: Hands-on projects (e.g., Bangalore housing prices, Breast cancer classification, Sales dataset). Qualifications : Education: Bachelor’s/Master’s in Computer Science, AI, ML, or related fields. Experience: 3–5 years in Machine Learning, Deep Learning, and Full Stack AI development, with hands-on experience in: Python and libraries like scikit-learn, TensorFlow, Keras, PyTorch. Generative AI (GANs, Diffusion Models, LLMs like GPT-2, LLaMA). Web development (Flask, FastAPI) and cloud deployment (AWS EC2, Azure). Tools like Hugging Face, FAISS, LangChain, and Streamlit. Teaching Skills: Prior teaching/training experience preferred, with the ability to explain complex topics (e.g., attention mechanisms, PCA) to undergraduate students. Certifications: Relevant certifications in AI/ML (e.g., AWS Certified Machine Learning, Google Professional ML Engineer) are a plus.