7 Knn Jobs

As a Machine Learning Engineer, you will play a key role in developing and enhancing a Telecom Artificial Intelligence Product. This role requires a strong background in machine learning and deep learning, along with extensive experience in implementing advanced algorithms and models to solve complex problems. You will be working on cutting-edge technologies to develop solutions for anomaly detection, forecasting, event correlation, and fraud detection. Your responsibilities will include developing production-ready implementations of proposed solutions using various machine learning and deep learning algorithms. You will test these solutions on live customer data to ensure efficacy and robustness. Additionally, you will research and test novel machine learning approaches for large-scale distributed computing applications. In this role, you will be responsible for implementing and managing the full machine learning operations lifecycle using tools such as Kubeflow, MLflow, AutoML, and Kserve for model deployment. You will develop and deploy machine learning models using PyTorch and TensorFlow to ensure high performance and scalability. Furthermore, you will run and manage PySpark and Kafka on distributed systems with large-scale, non-linear network elements. To excel in this position, you should be proficient in Python programming and experienced with machine learning libraries such as Scikit-Learn and NumPy. Experience in time series analysis, data mining, text mining, and creating data architectures will be beneficial. You should also be able to utilize batch processing and incremental approaches to manage and analyze large datasets. As a Machine Learning Engineer, you will experiment with multiple algorithms, optimizing hyperparameters to identify the best-performing models. You will execute machine learning algorithms in cloud environments, leveraging cloud resources effectively. Continuous feedback gathering, model retraining, and updating will be essential to maintain and improve model performance. Moreover, you should have expertise in network characteristics, transformer architectures, GAN AI techniques, and end-to-end machine learning projects. Experience with leading supervised and unsupervised machine learning methods and familiarity with Python packages like Pandas, Numpy, and DL frameworks like Keras, TensorFlow, PyTorch are required. Knowledge of Big Data tools and environments, as well as MySQL/NoSQL databases, will be advantageous. You will collaborate with cross-functional teams of data scientists, software engineers, and stakeholders to integrate implemented systems into the SaaS platform. Your innovative thinking and creative ideas will contribute to improving the overall platform. Additionally, you will create use cases specific to the domain to solve business problems effectively. Ideally, you should have a Bachelor's degree in Science/IT/Computing or equivalent with at least 4 years of experience in a QA Engineering role. Strong quantitative and applied mathematical skills are essential, along with certification courses in Data Science/ML. In-depth knowledge of statistical techniques, machine learning techniques, and experience with Telecom Product development are preferred. Experience in MLOps is a plus for deploying developed models, and familiarity with scalable SaaS platforms is advantageous for this role.,

As a candidate for this position, you will be responsible for analysis, design, coding, and integration using C/C++, Python. You should have experience in shadow removal techniques and be familiar with machine learning algorithms such as KNN, SVM, and text search. Additionally, familiarity with tools like QGIS and libraries like OpenCV is expected. The ideal candidate will hold a Master's degree in Machine Learning, Computer Vision, or Deep Learning with GIS knowledge as an add-on qualification. You should possess excellent written and verbal communication skills and be a self-starter with the ability to actively collaborate in a cross-functional team. A problem-solving mindset, along with a passion for technology, creativity, innovation, and resourcefulness, are essential for this role. We are looking for individuals who are eager to learn and innovate in a fast-paced and evolving market. Adaptability to change, a proactive attitude, and a willingness to take on challenges are key attributes we value in our team members. If you are someone who is ready to roll up your sleeves and get things done, we encourage you to apply for this exciting opportunity.,

You are an experienced professional with 5 to 12 years of experience, looking for a Full-Time opportunity as an Azure Generative AI Engineer. Your primary skills include Data Science, Machine Learning, Python, AI, and Azure. You will be responsible for designing, developing, and deploying Generative AI applications using Python, FastAPI, Azure Durable Functions, and Azure OpenAI Services. You must build and implement Retrieval-Augmented Generation (RAG) pipelines for enterprise AI applications and work on end-to-end Generative AI projects. Your role involves integrating AI/ML search and data services such as Azure Cognitive Search, Cosmos DB, and other Azure-native tools. Automation of key components of the RAG workflow for ensuring production-grade performance and scalability is crucial. You will be evaluating, validating, and fine-tuning the outputs of Generative AI models for accuracy and relevance, implementing monitoring, observability, and guardrails to ensure responsible and secure use of AI technologies, and collaborating with cross-functional teams to deliver innovative AI solutions. To qualify for this role, you must have strong programming experience in Python, including frameworks like FastAPI and Flask. A deep understanding of Generative AI, LLMs, and RAG methodologies is essential. Proficiency in Azure cloud services, especially Azure OpenAI, Functions, AI Search, and Cosmos DB is required. Hands-on experience with machine learning, deep learning, and natural language processing (NLP) is a must. Familiarity with ML/DL frameworks such as TensorFlow, PyTorch, and libraries like scikit-learn, spaCy, etc., is expected. You should possess solid knowledge of machine learning algorithms, including GPTs, CNNs, RNNs, k-NN, Naive Bayes, SVM, and Decision Forests, along with experience in evaluating and fine-tuning LLM performance and implementing responsible AI practices. Preferred qualifications include certifications in Azure AI Engineer Associate or related fields. Experience working with managed LLMs beyond Azure OpenAI (e.g., OpenAI API, Anthropic, Cohere, etc.) and knowledge of DevOps, CI/CD, and infrastructure automation for AI pipelines are considered advantageous.,

At American Express, the culture is built on a 175-year history of innovation, shared values, and Leadership Behaviors, with an unwavering commitment to support customers, communities, and colleagues. As a part of Team Amex, you will experience comprehensive support for your holistic well-being and numerous opportunities to learn new skills, develop as a leader, and advance your career. Your voice and ideas will be valued, your work will have an impact, and together, we will shape the future of American Express. The AIM (Analytics, Investment & Marketing Enablement) team, a part of GCS Marketing, serves as the analytical engine that drives the Global Commercial business portfolio of American Express. The team's primary objectives include accelerating growth momentum, increasing profitability, and enhancing the value proposition. By providing actionable insights to drive business strategy and growth, the team enables GCS Marketing to achieve its goals. As an Analyst (Band 30) in Gurgaon, India, your role will focus on driving sentinel measurement Analytics across channels and product offerings at Amex. Your key responsibilities will include supporting business partners with campaign measurements, ROI analysis, and actionable data-driven insights for acquisition & engagement treatments in GCS. You will develop analytical solutions by gathering requirements, performing data analysis, and delivering timely reporting for marketing & sales leadership. Additionally, you will collaborate with stakeholders, assess business needs, ensure data integrity, and provide actionable recommendations in times of change. Minimum Qualifications: - Degree in a quantitative field preferred (e.g., B.Tech, BSc/MSc Statistics, Economics) - Knowledge of Hive, Python, PySpark, SQL for data manipulation and statistical modeling - Strong analytical aptitude, technical skills, and project management abilities - Excellent communication skills to present results & methodologies clearly - Ability to work in high-pressure situations with minimal errors and a growth mindset - Strong problem-solving skills, ability to work independently, and challenge the status quo - Comfortable with flexible shift timings to support Global Partners Preferred Qualifications: - 1-2 years of relevant experience with skills in Python, SQL, and Advanced Excel - Knowledge of statistical techniques like hypothesis testing, regression, KNN, t-test, chi-square test - Experience in campaign measurement/marketing analytics is a plus American Express provides benefits to support your holistic well-being, including competitive base salaries, bonus incentives, financial well-being support, comprehensive medical benefits, flexible working arrangements, parental leave policies, access to wellness centers, counseling support, and career development opportunities. Employment with American Express is subject to the successful completion of a background verification check.,

Job Role: Lead Data Scientist. Location: Bengaluru, Karnataka. Mode : Work from Office Notice Period: Immediate to 20 days. Job Description The incumbent will be part of the Predictive Analytics, Digital Analytics, Data Sciences, Advanced Visualization, Insights & Experimentation team and will report to the Manager/Senior Manager. He/she will be an individual contributor working on multiple data sciences, advanced visualization and data management initiatives across multiple companies and industries leveraging traditional and big data. The incumbent will have the unique opportunity to witness the application of analytics across multiple industry verticals. Close partnership with business and the senior leadership of multiple Tata Companies will enable a clear understanding of the business perspectives and the application of analytics for solving real business problems. Key Responsibilities: • Apply AI| ML , Deep Learning, Computer Vision, Data Mining/ Data Analysis methods using a variety of data tools, building and implementing models using algorithms and creating/ running simulations to drive optimisation and improvement across business functions • Assess accuracy of new data sources and data gathering techniques • Perform Exploratory Data Analysis, detailed analysis of business problems and technical environments in designing the solution • Apply Supervised, Unsupervised, Reinforcement Learning and Deep Learning algorithms • Apply advanced Machine Learning Algorithms and Statistics: o Regression, Simulation, Scenario Analysis o Time Series Modelling o Classification - Logistic Regression, Decision Trees, SVM, KNN, Naive Bayes o Clustering, K-Means, Apriopri o Ensemble Models - Random Forest, Boosting, Bagging o Neural Networks • Lead and manage Proof of Concepts and demonstrate the outcomes quickly • Document use cases, solutions and recommendations • Work analytically in a problem-solving environment • Work in a fast-paced agile development environment • Coordinate with different functional teams to implement models and monitor outcomes • Work with stakeholders throughout the organization to identify opportunities for leveraging organisation data and apply Predictive Modelling techniques to gain insights across business functions - Operations, Products, Sales, Marketing, HR and Finance teams • Help program and project managers in the design, planning and governance of implementing Data Science solutions Experience and Skills: • 8+ years of professional working experience in Analytics • Experience in Leading Team and Guiding through Project End to End Delivery. - Experience in Retail, Financial Services and Manufacturing • Experience using statistical packages of R, Python and Spark ML to work with data and draw insights from large data sets • Experience with distributed data/ computing tools: Hadoop, Hive, Spark, Python • Experience with SQL • Experience visualizing/ presenting data for stakeholders using matplot, ggplot or Excel or Tableau • Excellent written and verbal communication skills for coordinating across teams Education qualification: • Bachelors/ Masters in a quantitative discipline (Statistics, Econometrics, Mathematics, Engineering and Science)

AI/ML Engineer to join our fast-growing. The ideal candidate will be responsible for designing, developing, and deploying machine learning models and AI-driven applications that deliver business value and customer impact. Key Responsibilities Research and develop machine learning models using supervised, unsupervised, or reinforcement learning techniques. Deploy models into production using MLOps best practices (e.g., containerization, CI/CD, model monitoring). Work on datasets involving structured and unstructured data (e.g., text, image, video, time-series). Collaborate with data engineers, product managers, and other stakeholders to define problem statements and deliver solutions. Continuously improve model performance and scalability using experimentation and model evaluation techniques. Stay updated with the latest trends and breakthroughs in AI/ML (e.g., LLMs, transformers, generative AI). Required Qualifications Bachelors/Masters/Ph.D. in Computer Science, Artificial Intelligence, Data Science, or a related field. Strong coding skills in Python (must), with knowledge of libraries like scikit-learn, PyTorch, TensorFlow, Hugging Face, OpenCV , etc. Experience building and tuning ML models from scratch. Solid understanding of ML lifecycle, from data preprocessing to model deployment. Hands-on with SQL , data manipulation tools ( Pandas , NumPy ), and visualization tools ( Matplotlib , Seaborn , Plotly ). Experience with cloud platforms (AWS/GCP/Azure) and tools like Docker, Kubernetes, MLflow is a plus. Preferred Skills Exposure to NLP , LLMs , chatbots , speech processing , or computer vision applications. Experience with GenAI models like GPT, DALL•E, or stable diffusion. Knowledge of prompt engineering, vector databases (like FAISS, Pinecone ), or LangChain is a bonus. Publications or participation in AI/ML competitions (e.g., Kaggle, NeurIPS, CVPR) is a strong plus.

Strong proficiency in Python and/or R for data analysis and modeling. Advanced SQL skills for data querying and transformation. Hands-on experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Solid understanding of statistics, hypothesis testing, regression analysis, and data mining. Familiarity with cloud platforms (AWS, Azure, or GCP) and big data tools (Spark, Hadoop) is a plus. Excellent problem-solving skills and attention to detail.