59 Supervised Learning Jobs

About The Role Project Role : Software Development Lead Project Role Description : Develop and configure software systems either end-to-end or for a specific stage of product lifecycle. Apply knowledge of technologies, applications, methodologies, processes and tools to support a client, project or entity. Must have skills : Machine Learning Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Software Development Lead, you will be responsible for developing and configuring software systems, applying knowledge of technologies, methodologies, and tools to support projects or clients throughout the product lifecycle. Roles & Responsibilities:- Develop and implement advanced algorithms using MATLAB, Simulink and Python. -Develop models for a variety of use cases, including classification, regression, recommendation systems, time-series forecasting, and anomaly detection. -Apply advanced mathematical techniques to create robust solutions. -Participate in code reviews and provide constructive feedback to ensure code quality and adherence to best practices. -Document algorithms clearly and concisely, including design rationale, assumptions, and limitations. -Prototype and test new algorithms or methods that could be beneficial for the teams goals Professional & Technical Skills: - Strong experience in developing algorithms using MATLAB/Simulink and Python. -Proficiency in programming languages, particularly Python and R, and experience using Jupyter notebooks etc. for experimentation and model development.-Expert in supervised learning, unsupervised learning, reinforcement learning, deep learning. -Solid understanding of linear algebra, calculus, probability theory, and statistics, which are fundamental to ML algorithms. -Understanding of how to deploy ML models into production using tools like Docker, Kubernetes, and CI/CD pipelines. Additional Information:- The candidate should have a minimum of 5 years of experience in Machine Learning- This position is based at our Bengaluru office- A 15 years full time education is required Qualification 15 years full time education

Overview: Data is at the heart of our global financial network. In fact, the ability to consume, store, analyze and gain insight from data has become a key component of our competitive advantage. Our goal is to build and maintain a leading-edge data platform that provides highly available , consistent data of the highest quality for all users of the platform, including our customers, operations teams and data scientists. We focus on evolving our platform to deliver exponential scale to NCR Atleos , powering our future growth. Data & AI Engineers at NCR Atleos experience working at one of the largest and most recognized financial companies in the world, while being part of a software development team responsible for next generation technologies and solutions. Our engineers design and build large scale data storage, computation and distribution systems. They partner with data and AI experts to deliver high quality AI solutions and derived data to our consumers. We are looking for Data & AI Engineers who like to innovate and seek complex problems. We recognize that strength comes from diversity and will embrace your unique skills, curiosity, drive, and passion while giving you the opportunity to grow technically and as an individual. Engineers looking to work in the areas of orchestration, data modelling , data pipelines, APIs, storage, distribution, distributed computation, consumption and infrastructure are ideal candidates. Responsibilities As a Data Engineer, you will be joining a Data & AI team transforming our global financial network and improving the quality of our products and services we provide to our customers. and you will be responsible for designing, implementing, and maintaining data pipelines and systems to support the organization's data needs. Your role will involve collaborating with data scientists, analysts, and other stakeholders to ensure data accuracy, reliability, and accessibility. Key Responsibilities: Data Pipeline Development: Design, build, and maintain scalable and efficient data pipelines to collect, process, and store structured and unstructured data from various sources. Data Integration: Integrate data from multiple sources such as databases, APIs, flat files, and streaming platforms into centralized data repositories. Data Modeling: Develop and optimize data models and schemas to support analytical and operational requirements. Implement data transformation and aggregation processes as needed. Data Quality Assurance: Implement data validation and quality assurance processes to ensure the accuracy, completeness, and consistency of data throughout its lifecycle. Performance Optimization: Monitor and optimize data processing and storage systems for performance, reliability, and cost-effectiveness. Identify and resolve bottlenecks and inefficiencies in data pipelines and leverage Automation and AI to improve overall Operations. Infrastructure Management: Manage and configure cloud-based or on-premises infrastructure components such as databases, data warehouses, compute clusters, and data processing frameworks. Collaboration: Collaborate with cross-functional teams including data scientists, analysts, software engineers, and business stakeholders to understand data requirements and deliver solutions that meet business objectives . Documentation and Best Practices: Document data pipelines, systems architecture, and best practices for data engineering. Share knowledge and provide guidance to colleagues on data engineering principles and techniques. Continuous Improvement: Stay updated with the latest technologies, tools, and trends in data engineering and recommend improvements to existing processes and systems. Qualifications and Skills: Bachelor's degree or higher in Computer Science, Engineering, or a related field. Proven experience in data engineering or related roles, with a strong understanding of data processing concepts and technologies. Mastery of programming languages such as Python, Java, or Scala. Knowledge of database systems such as SQL, NoSQL, and data warehousing solutions. Knowledge of stream processing technologies such as Kafka or Apache Beam. Experience with distributed computing frameworks such as Apache Spark, Hadoop, or Apache Flink . Experience deploying pipelines in cloud platforms such as AWS, Azure, or Google Cloud Platform. Experience in implementing enterprise systems in production setting for AI, natural language processing. Exposure to self-supervised learning, transfer learning, and reinforcement learning is a plus . Have full stack experience to build the best fit solutions leveraging Large Language Models (LLMs) and Generative AI solutions with focus on privacy, security, fairness. Have good engineering skills to design the output from the AI with nodes and nested nodes in JSON or array, HTML formats for as-is consumption and display on the dashboards/portals. Strong problem-solving skills and attention to detail. Excellent communication and teamwork abilities. Experience with containerization and orchestration tools such as Docker and Kubernetes. Familiarity with data visualization tools such as Tableau or Power BI.

Wipro Limited is a prominent technology services and consulting company dedicated to creating innovative solutions that cater to the most intricate digital transformation requirements of clients. With a comprehensive range of capabilities in consulting, design, engineering, and operations, we assist clients in achieving their most ambitious goals and establishing sustainable businesses for the future. Our global team of over 230,000 employees and business partners in 65 countries is committed to helping customers, colleagues, and communities thrive in an ever-evolving world. For more details, please visit our website at www.wipro.com. With a career spanning over 10 years, you have consistently focused on data science and have successfully implemented at least two production-grade Generative AI solutions. You possess hands-on experience with Agentic AI frameworks and are an expert in Robotics, encompassing Multiagent Systems, Automated Planning & Scheduling, Intelligence, and Orchestration. Your proficiency in AI & ML includes knowledge of Supervised and Unsupervised Learning, Neural Networks, Large Language Models (LLMs), as well as Full-stack Software Engineering and System Design. Your track record demonstrates the ability to leverage emerging technologies to tackle complex business challenges. Your technical expertise covers a wide range of tools and platforms including Python, FastAPI, Ollama, RDBMS (PostgreSQL), Message Brokers, UI Frameworks (Angular, Streamlit), Robot Operating System (ROS), AI/ML Python frameworks (scikit-learn, PyTorch, etc.), AWS, Azure, and Git. You are recognized as an authority in machine learning, Generative AI, LLMs, SLMS, and Agents, with a particular focus on computer vision, deep learning, and statistical modeling. Your leadership in innovative projects involving video analytics, face recognition, and retail analytics using tools such as OpenCV and Point Cloud Libraries is commendable. Your extensive knowledge encompasses various areas such as robot kinematics, navigation, planning, multi-agent orchestration, neural networks, software engineering, architecture, OOP, and the Git ecosystem. You bring a wealth of experience in techno-functional product and project management, contributing significantly to vital research and business decisions. Keeping abreast of the latest technological advancements is second nature to you, and your foundation in Computer Vision, AI, ML/DL, Generative AI, Large Language Models, and Agentic AI is solid. Having gained experience from product-based companies and being academically inclined from IIT, you possess a strong background in Machine Learning. With 8-10 years of experience, you are well-equipped to thrive in an environment that values reinvention and continuous evolution. At Wipro, we are reshaping the future by empowering individuals like you to redefine themselves, their careers, and their skills. Join us in building a modern Wipro and realize your aspirations. We welcome applications from individuals with disabilities.,

As a Data Science Consultant with expertise in machine learning and Python, you will be responsible for understanding and implementing the end-to-end architecture of Data Science and machine learning projects. Your role will involve productionizing machine learning models, guiding the development team in implementing machine learning use cases, and providing technology consulting to define the right Data Science and ML use cases. Your key responsibilities will include data collection, profiling, exploratory data analysis, and data preparation. You will be involved in AI model development, tuning, and validation, as well as using visualization tools such as PowerBI and Tableau to present findings to business users and project management teams. Additionally, you will propose ML-based solution approaches, estimate new use cases, and contribute to AI-based modules in Infosys solutions development. It will be essential for you to continuously explore new advances in AI, execute Proof of Concepts (PoCs), and mentor and guide other team members in ML algorithms and AI domains such as NLP, speech, and computer vision. You should have experience with supervised, unsupervised, and reinforcement learning, as well as expertise in tools for data analysis, auto ML, model deployment, and scaling. Proficiency in programming languages like Python, knowledge of databases, and familiarity with cloud platforms such as Azure, AWS, and GCP will be essential for success in this role. If you have a passion for AI/ML solution architecture and design, and you are eager to contribute to cutting-edge projects in the field of Data Science and machine learning, we look forward to receiving your application.,

We are looking for a Data Analyst with over 5 years of experience to join our team at our new office in Infopark, Kochi. As a Data Analyst in our AdTech industry, you will play a crucial role in leveraging your expertise in programming, statistical modeling, and data visualization to extract valuable insights from complex datasets. Your contributions will directly impact our Indian operations" growth and success. Your responsibilities will include collecting, cleaning, and analyzing large datasets using SQL and Python. You will be tasked with building and implementing machine learning models, performing data segmentation, clustering, and predictive modeling to identify trends and business opportunities. Additionally, you will evaluate model performance using statistical and machine learning metrics, develop Power BI dashboards, and collaborate with cross-functional teams to translate data insights into actionable business strategies. To qualify for this role, you should hold a Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or a related field. Proficiency in Python (pandas, NumPy, scikit-learn, stats models) and advanced SQL skills are essential for data manipulation and modeling. Experience with supervised and unsupervised learning, segmentation, clustering methods, predictive modeling, and model evaluation metrics is required. Hands-on experience with Power BI for creating dashboards and strong analytical skills are also necessary. Joining our team means working in a fast-paced, data-driven environment with real impact on growth. You will be part of a new chapter in a fast-growing multinational company, enjoying a competitive salary, excellent benefits, and hybrid work options. Located in Infopark, Kochi, surrounded by top IT companies, this opportunity offers a chance to be part of something new and grow with us. If you meet the qualifications and are excited about this opportunity, apply now by sending your resume to careers@firstscreen.com or DM us for more details. Join us on this journey of growth and innovation!,

As an Analytics Associate Manager - Insights and Intelligence at Accenture, you will be part of the Insights & Intelligence vertical, responsible for generating insights using the latest Artificial Intelligence (AI) and Analytics techniques to deliver value to clients. Your expertise will be utilized in building top-notch solutions, solving business problems, and addressing technical challenges using AI Platforms and technologies. You will play a key role in creating architectural foundation and services necessary for AI applications, demonstrating your expertise through activities such as blogging, publishing research papers, and creating awareness in this emerging area. Your primary focus will be on working within the Marketing & Customer Analytics team to measure, manage, and analyze marketing activities, providing actionable insights and recommendations for optimizing ROI and performance efficiency in operations. Customer analytics will involve utilizing data from customer behavior to support key business decisions through market segmentation and predictive analytics. You should have exposure to digital marketing, A/B testing, MVT, Google Analytics/Site Catalyst. As a core member of Accenture Operations global Applied Intelligence group, you will collaborate with a strategic and high-impact team to innovate and transform the Accenture Operations business using machine learning and advanced analytics. Your responsibilities will include leading data scientists to build and deploy data science models, refining models based on feedback and evolving business needs, and analyzing data to enhance brand equity, improve retail margins, achieve profitable growth, and expand market share for clients. In this role, we are looking for candidates with extensive experience in leading Data Science and Advanced Analytics delivery teams, strong statistical programming skills in Python, R, SAS, S-plus, MATLAB, STATA, or SPSS, experience with large data sets and big data tools like Snowflake, AWS, Spark, etc. Additionally, solid knowledge in areas such as Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling, Multivariate Statistics, and more is required. Experience in business domains like CPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, and Supply Chain is preferred. The ideal candidate will have extensive experience in client engagement and business development, the ability to work in a global collaborative team environment, and manage medium-small sized teams or work efforts. You should be comfortable working on moderately complex problems, creating new solutions, and adapting existing methods and procedures as needed. This role may require working in rotational shifts. Join us at Accenture and be part of a global professional services company where you can leverage your skills and expertise to drive meaningful change and create value for clients across various industries.,

As an Analytics and Modeling Analyst at Accenture, you will be part of our growing Insights and Analytics team. You will be responsible for developing and implementing machine learning models using supervised and unsupervised techniques. Your role will involve applying appropriate machine learning algorithms for prediction tasks and data segmentation based on project requirements. Additionally, you will perform data preprocessing, feature engineering, and model evaluation to ensure the accuracy and efficiency of the models. The ideal candidate for this position should have a Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field, along with 2 to 3 years of experience in applied machine learning and data science projects. You should have a solid understanding of model training, validation, and deployment workflows, as well as experience working with version control and collaborative development environments. Familiarity with tools that automate and manage the process of building, testing, and deploying machine learning models, as well as a basic understanding of cloud-based architecture and APIs, would be beneficial. In this role, you will collaborate with data engineers, analysts, and product teams to translate business problems into machine learning solutions. You will use Python libraries such as scikit-learn, TensorFlow, and others to build and test models, and analyze and manipulate structured datasets using notebooks like Jupyter. Your responsibilities will also include documenting model performance, data flows, and process pipelines to ensure transparency and reproducibility of the work. If you are a Machine Learning Data Scientist with a passion for building ML models using cutting-edge techniques and technologies, we invite you to join our team at Accenture and contribute to creating value and shared success for our clients, people, and communities.,

We are seeking a highly skilled and motivated Senior DS/ML engineer to join our team. The role is critical to the development of a cutting-edge reporting platform designed to measure and optimize online marketing campaigns. We are seeking a highly skilled Data Scientist / ML Engineer with a strong foundation in data engineering (ELT, data pipelines) and advanced machine learning to develop and deploy sophisticated models. The role focuses on building scalable data pipelines, developing ML models, and deploying solutions in production to support a cutting-edge reporting, insights, and recommendations platform for measuring and optimizing online marketing campaigns. The ideal candidate should be comfortable working across data engineering, ML model lifecycle, and cloud-native technologies. Job Description: Key Responsibilities: Data Engineering & Pipeline Development Build, and maintain scalable ELT pipelines for ingesting, transforming, and processing large-scale marketing campaign data. Ensure high data quality, integrity, and governance using orchestration tools like Apache Airflow, Google Cloud Composer, or Prefect. Optimize data storage, retrieval, and processing using BigQuery, Dataflow, and Spark for both batch and real-time workloads. Implement data modeling and feature engineering for ML use cases. Machine Learning Model Development & Validation Develop and validate predictive and prescriptive ML models to enhance marketing campaign measurement and optimization. Experiment with different algorithms (regression, classification, clustering, reinforcement learning) to drive insights and recommendations. Leverage NLP, time-series forecasting, and causal inference models to improve campaign attribution and performance analysis. Optimize models for scalability, efficiency, and interpretability. MLOps & Model Deployment Deploy and monitor ML models in production using tools such as Vertex AI, MLflow, Kubeflow, or TensorFlow Serving. Implement CI/CD pipelines for ML models, ensuring seamless updates and retraining. Develop real-time inference solutions and integrate ML models into BI dashboards and reporting platforms. Cloud & Infrastructure Optimization Design cloud-native data processing solutions on Google Cloud Platform (GCP), leveraging services such as BigQuery, Cloud Storage, Cloud Functions, Pub/Sub, and Dataflow. Work on containerized deployment (Docker, Kubernetes) for scalable model inference. Implement cost-efficient, serverless data solutions where applicable. Business Impact & Cross-functional Collaboration Work closely with data analysts, marketing teams, and software engineers to align ML and data solutions with business objectives. Translate complex model insights into actionable business recommendations. Present findings and performance metrics to both technical and non-technical stakeholders. Qualifications & Skills: Educational Qualifications: Bachelors or Masters degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, or a related field. Certifications in Google Cloud (Professional Data Engineer, ML Engineer) is a plus. Must-Have Skills: Experience: 3 -5 years with the mentioned skillset & relevant hands-on experience Data Engineering: Experience with ETL/ELT pipelines, data ingestion, transformation, and orchestration (Airflow, Dataflow, Composer). ML Model Development: Strong grasp of statistical modeling, supervised/unsupervised learning, time-series forecasting, and NLP. Programming: Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL for large-scale data processing. Cloud & Infrastructure: Expertise in GCP (BigQuery, Vertex AI, Dataflow, Pub/Sub, Cloud Storage) or equivalent cloud platforms. MLOps & Deployment: Hands-on experience with CI/CD pipelines, model monitoring, and version control (MLflow, Kubeflow, Vertex AI, or similar tools). Data Warehousing & Real-time Processing: Strong knowledge of modern data platforms for batch and streaming data processing. Nice-to-Have Skills: Experience with Graph ML, reinforcement learning, or causal inference modeling. Working knowledge of BI tools (Looker, Tableau, Power BI) for integrating ML insights into dashboards. Familiarity with marketing analytics, attribution modeling, and A/B testing methodologies. Experience with distributed computing frameworks (Spark, Dask, Ray). Location: Bengaluru Brand: Merkle Time Type: Full time Contract Type: Permanent Show more Show less

We are seeking a highly skilled and motivated Senior DS/ML engineer to join our team. The role is critical to the development of a cutting-edge reporting platform designed to measure and optimize online marketing campaigns. We are seeking a highly skilled Data Scientist / ML Engineer with a strong foundation in data engineering (ELT, data pipelines) and advanced machine learning to develop and deploy sophisticated models. The role focuses on building scalable data pipelines, developing ML models, and deploying solutions in production to support a cutting-edge reporting, insights, and recommendations platform for measuring and optimizing online marketing campaigns. The ideal candidate should be comfortable working across data engineering, ML model lifecycle, and cloud-native technologies. Job Description: Key Responsibilities: Data Engineering & Pipeline Development Build, and maintain scalable ELT pipelines for ingesting, transforming, and processing large-scale marketing campaign data. Ensure high data quality, integrity, and governance using orchestration tools like Apache Airflow, Google Cloud Composer, or Prefect. Optimize data storage, retrieval, and processing using BigQuery, Dataflow, and Spark for both batch and real-time workloads. Implement data modeling and feature engineering for ML use cases. Machine Learning Model Development & Validation Develop and validate predictive and prescriptive ML models to enhance marketing campaign measurement and optimization. Experiment with different algorithms (regression, classification, clustering, reinforcement learning) to drive insights and recommendations. Leverage NLP, time-series forecasting, and causal inference models to improve campaign attribution and performance analysis. Optimize models for scalability, efficiency, and interpretability. MLOps & Model Deployment Deploy and monitor ML models in production using tools such as Vertex AI, MLflow, Kubeflow, or TensorFlow Serving. Implement CI/CD pipelines for ML models, ensuring seamless updates and retraining. Develop real-time inference solutions and integrate ML models into BI dashboards and reporting platforms. Cloud & Infrastructure Optimization Design cloud-native data processing solutions on Google Cloud Platform (GCP), leveraging services such as BigQuery, Cloud Storage, Cloud Functions, Pub/Sub, and Dataflow. Work on containerized deployment (Docker, Kubernetes) for scalable model inference. Implement cost-efficient, serverless data solutions where applicable. Business Impact & Cross-functional Collaboration Work closely with data analysts, marketing teams, and software engineers to align ML and data solutions with business objectives. Translate complex model insights into actionable business recommendations. Present findings and performance metrics to both technical and non-technical stakeholders. Qualifications & Skills: Educational Qualifications: Bachelors or Masters degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, or a related field. Certifications in Google Cloud (Professional Data Engineer, ML Engineer) is a plus. Must-Have Skills: Experience: 3 -5 years with the mentioned skillset & relevant hands-on experience Data Engineering: Experience with ETL/ELT pipelines, data ingestion, transformation, and orchestration (Airflow, Dataflow, Composer). ML Model Development: Strong grasp of statistical modeling, supervised/unsupervised learning, time-series forecasting, and NLP. Programming: Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL for large-scale data processing. Cloud & Infrastructure: Expertise in GCP (BigQuery, Vertex AI, Dataflow, Pub/Sub, Cloud Storage) or equivalent cloud platforms. MLOps & Deployment: Hands-on experience with CI/CD pipelines, model monitoring, and version control (MLflow, Kubeflow, Vertex AI, or similar tools). Data Warehousing & Real-time Processing: Strong knowledge of modern data platforms for batch and streaming data processing. Nice-to-Have Skills: Experience with Graph ML, reinforcement learning, or causal inference modeling. Working knowledge of BI tools (Looker, Tableau, Power BI) for integrating ML insights into dashboards. Familiarity with marketing analytics, attribution modeling, and A/B testing methodologies. Experience with distributed computing frameworks (Spark, Dask, Ray). Location: Bengaluru Brand: Merkle Time Type: Full time Contract Type: Permanent Show more Show less

The role aims to establish the strategic direction for the team, assuming responsibility for the overall Insights and analysis discipline in the market. You will collaborate with various channels to ensure an integrated response to people-based marketing objectives. We are in search of an experienced Advanced Analytics Senior Manager to become a part of our dynamic team. This position is dedicated to utilizing advanced analytics techniques, which include machine learning algorithms, Generative AI (GenAI), and large language models (LLMs), to facilitate data-driven decision-making within the retail/CPG domain. The ideal candidate should have a solid quantitative background, a keen interest in translating complex data into actionable insights, significant experience in leading mid-to-large sized teams, and the capability to design, evaluate, and implement RFPs, POCs, approaches, and frameworks. Responsibilities: - Develop, implement, and manage advanced analytical models leveraging machine learning algorithms and GenAI applications. - Apply various advanced analytics techniques to reveal trends, patterns, and insights from extensive and intricate datasets. - Work closely with cross-functional teams to identify business requirements and provide data-driven solutions. - Design visually appealing dashboards and reports to communicate findings to stakeholders. - Continuously assess and enhance existing analytics methodologies and models for improved accuracy and performance. - Keep updated on industry trends and advancements in analytics and machine learning to foster innovation within the team. - Mentor junior team members and contribute to knowledge sharing across the organization. Basic Qualifications: - Bachelor's or Master's degree in Data Science, Business Analytics, Mathematics, Statistics, or a related field. - Over 10 years of experience in advanced analytics, data science, machine learning, Generative AI, or a related field. - Profound experience in quantitative modeling, predictive analytics, text analytics, and forecasting methodologies. - Proficiency in SQL (or Google BigQuery), Python, and visualization tools such as Tableau/PowerBI. - Familiarity with the Retail/CPG/Tech industry and exposure to product, transaction, and customer-level data. - Excellent communication skills, both verbal and written, with the ability to convey complex concepts to non-technical stakeholders. - Strong analytical and problem-solving skills, coupled with an inquisitive mindset. Desired Skills: - Proficiency in various advanced analytics techniques, including Descriptive Analytics, Predictive Analytics, Prescriptive Analytics, and Text Analytics. - Extensive knowledge of machine learning techniques, encompassing Supervised Learning, Unsupervised Learning, and Reinforcement Learning. - Experience with Generative AI and large language models (LLMs) for text generation, summarization, and conversational agents. - Proficiency in data visualization tools like Tableau or Power BI. - Strong skills in data management, structuring, and harmonization to support analytical requirements. Location: Coimbatore Brand: Merkle Time Type: Full time Contract Type: Permanent,

Company Description LueinAnalytics, founded in 2017, is a pioneer in AI Research and Consulting, offering next-generation AI consulting services. The company helps organizations across diverse industries to implement and optimize Artificial Intelligence and analytics solutions. Luein Analytics combines industry expertise, leading cloud platforms, and data science to deliver transformative outcomes, maximizing the power of data to solve critical challenges. Role Description This is a remote internship role for a Computer Vision Deep Learning Intern at Luein Analytics. The intern will be responsible for working on computer vision projects using deep learning techniques. They will collaborate with the team on research, development, and implementation of computer vision algorithms and models. Duration : 3 months, Full-time (10am-6pm), Remote Stipend : INR 8000 / month Qualifications Experience with Computer Vision and Deep Learning Python programming fluency Knowledge of Supervised and Unsupervised Learning, Reinforcement Learning, and Neural Networks Familiarity with Image Processing and Computer Vision libraries (e.g - OpenCV, TensorFlow, PyTorch) Experience fine-tuning base models like ResNet, EfficientNet, Contrastive learning, for image classifications and image detection tasks. Strong programming skills in languages such as Python. Understanding of Machine Learning concepts and algorithms Ability to work independently and collaboratively in a remote setting Pursuing or completed a graduate degree in Computer Science, Artificial Intelligence, or related field Show more Show less

We are seeking a highly skilled and motivated Lead DS/ML engineer to join our team. The role is critical to the development of a cutting-edge reporting platform designed to measure and optimize online marketing campaigns. We are seeking a highly skilled Data Scientist / ML Engineer with a strong foundation in data engineering (ELT, data pipelines) and advanced machine learning to develop and deploy sophisticated models. The role focuses on building scalable data pipelines, developing ML models, and deploying solutions in production to support a cutting-edge reporting, insights, and recommendations platform for measuring and optimizing online marketing campaigns. The ideal candidate should be comfortable working across data engineering, ML model lifecycle, and cloud-native technologies. Job Description: Key Responsibilities: Data Engineering & Pipeline Development Design, build, and maintain scalable ELT pipelines for ingesting, transforming, and processing large-scale marketing campaign data. Ensure high data quality, integrity, and governance using orchestration tools like Apache Airflow, Google Cloud Composer, or Prefect. Optimize data storage, retrieval, and processing using BigQuery, Dataflow, and Spark for both batch and real-time workloads. Implement data modeling and feature engineering for ML use cases. Machine Learning Model Development & Validation Develop and validate predictive and prescriptive ML models to enhance marketing campaign measurement and optimization. Experiment with different algorithms (regression, classification, clustering, reinforcement learning) to drive insights and recommendations. Leverage NLP, time-series forecasting, and causal inference models to improve campaign attribution and performance analysis. Optimize models for scalability, efficiency, and interpretability. MLOps & Model Deployment Deploy and monitor ML models in production using tools such as Vertex AI, MLflow, Kubeflow, or TensorFlow Serving. Implement CI/CD pipelines for ML models, ensuring seamless updates and retraining. Develop real-time inference solutions and integrate ML models into BI dashboards and reporting platforms. Cloud & Infrastructure Optimization Design cloud-native data processing solutions on Google Cloud Platform (GCP), leveraging services such as BigQuery, Cloud Storage, Cloud Functions, Pub/Sub, and Dataflow. Work on containerized deployment (Docker, Kubernetes) for scalable model inference. Implement cost-efficient, serverless data solutions where applicable. Business Impact & Cross-functional Collaboration Work closely with data analysts, marketing teams, and software engineers to align ML and data solutions with business objectives. Translate complex model insights into actionable business recommendations. Present findings and performance metrics to both technical and non-technical stakeholders. Qualifications & Skills: Educational Qualifications: Bachelors or Masters degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, or a related field. Certifications in Google Cloud (Professional Data Engineer, ML Engineer) is a plus. Must-Have Skills: Experience: 5-10 years with the mentioned skillset & relevant hands-on experience Data Engineering: Experience with ETL/ELT pipelines, data ingestion, transformation, and orchestration (Airflow, Dataflow, Composer). ML Model Development: Strong grasp of statistical modeling, supervised/unsupervised learning, time-series forecasting, and NLP. Programming: Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL for large-scale data processing. Cloud & Infrastructure: Expertise in GCP (BigQuery, Vertex AI, Dataflow, Pub/Sub, Cloud Storage) or equivalent cloud platforms. MLOps & Deployment: Hands-on experience with CI/CD pipelines, model monitoring, and version control (MLflow, Kubeflow, Vertex AI, or similar tools). Data Warehousing & Real-time Processing: Strong knowledge of modern data platforms for batch and streaming data processing. Nice-to-Have Skills: Experience with Graph ML, reinforcement learning, or causal inference modeling. Working knowledge of BI tools (Looker, Tableau, Power BI) for integrating ML insights into dashboards. Familiarity with marketing analytics, attribution modeling, and A/B testing methodologies. Experience with distributed computing frameworks (Spark, Dask, Ray). Location: Bengaluru Brand: Merkle Time Type: Full time Contract Type: Permanent Show more Show less

As a skilled professional in data handling and processing, you will demonstrate expertise in SQL Server and query optimization, ensuring efficient application data design and process management. Your knowledge in data modeling will be extensive, supported by hands-on experience with Azure Data Factory, Azure Synapse Analytics, and Microsoft Fabric. Additionally, your familiarity with Azure Databricks will be utilized in your work. In the realm of data warehouse development, your proficiency in SSIS (SQL Server Integration Services) and SSAS (SQL Server Analysis Services) will be essential. You will excel in ETL processes, encompassing data extraction, transformation, and loading, including data cleaning and normalization. Moreover, your exposure to big data technologies like Hadoop, Spark, and Kafka will enable you to handle large-scale data processing efficiently. Your understanding of data governance, compliance, and security measures within Azure environments will be integral to your role. Furthermore, your expertise in data analysis, statistical modeling, and machine learning techniques will drive insightful decision-making. Proficiency in analytical tools such as Python, R, and libraries like Pandas and NumPy will be leveraged for data analysis and modeling. You will showcase a strong command of Power BI for data visualization, data modeling, and DAX queries, following best practices in the field. Implementing Row-Level Security in Power BI will be one of your key responsibilities. Handling medium-complex data models and quickly grasping application data design and processes will be part of your routine tasks. In addition to technical skills, you will lead a team of 4-5 developers, ensuring timely deliverables and fostering a culture of continuous learning. Your communication skills in English, both written and verbal, will be crucial for effective collaboration with customers. You will adeptly explain complex technical concepts to non-technical stakeholders, showcasing your ability to bridge the gap between technical and non-technical perspectives. Your proficiency in SQL, Azure Synapse Analytics, Azure Analysis Service, and Data Marts will enable effective data management. Utilizing ETL tools like Azure Data Factory, Azure Data Bricks, Python, and SSIS will streamline your workflow. Data visualization will be a key aspect of your role, with Power BI and DAX serving as your primary tools for creating impactful visual representations of data. Overall, as a data professional, you will be responsible for handling and processing data efficiently, leveraging your technical expertise and non-technical skills to drive valuable insights and support strategic decision-making.,

The Retail Specialized Data Scientist will play a pivotal role in utilizing advanced analytics, machine learning, and statistical modeling techniques to help the retail business make data-driven decisions. You must have a solid understanding of retail industry dynamics, including key performance indicators (KPIs) such as sales trends, customer segmentation, inventory turnover, and promotions. Your ability to communicate complex data insights to non-technical stakeholders is crucial, including senior management, marketing, and operational teams. You should be meticulous in ensuring data quality, accuracy, and consistency when handling large, complex datasets. Gathering and cleaning data from various retail sources, such as sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns is a key responsibility. Proficiency in Python for data manipulation, statistical analysis, and machine learning (libraries like Pandas, NumPy, Scikit-learn) is a must. Expertise in supervised and unsupervised learning algorithms is also required. You will use advanced analytics to optimize pricing strategies based on market demand, competitor pricing, and customer price sensitivity. It would be good to have familiarity with big data processing platforms like Apache Spark, Hadoop, or cloud-based platforms such as AWS or Google Cloud for large-scale data processing. Experience with ETL processes and tools like Apache Airflow to automate data workflows is advantageous. Familiarity with designing scalable and efficient data pipelines and architecture is beneficial. Experience with tools like Tableau, Power BI, Matplotlib, and Seaborn to create meaningful visualizations that present data insights clearly is a plus. The ideal candidate should have a strong analytical and statistical skills, expertise in machine learning and AI, experience with retail-specific datasets and KPIs, proficiency in data visualization and reporting tools, ability to work with large datasets and complex data structures, strong communication skills to interact with both technical and non-technical stakeholders, a solid understanding of the retail business and consumer behavior. Programming Languages: Python, R, SQL, Scala. Data Analysis Tools: Pandas, NumPy, Scikit-learn, TensorFlow, Keras. Visualization Tools: Tableau, Power BI, Matplotlib, Seaborn. Big Data Technologies: Hadoop, Spark, AWS, Google Cloud. Databases: SQL, NoSQL (MongoDB, Cassandra). In this role, you will collaborate with teams across marketing, product management, supply chain, and customer insights to drive business strategies and innovations. You will leverage your deep understanding of the retail industry to design AI solutions that address critical retail business needs. Applying machine learning algorithms to enhance predictive models and using AI-driven techniques for personalization, demand forecasting, and fraud detection are key responsibilities. Staying updated on the latest trends in data science and retail technology is essential. Collaborating with executives, product managers, and marketing teams to translate insights into business actions is also part of your role. About Our Company | Accenture,

The Retail Specialized Data Scientist will play a pivotal role in utilizing advanced analytics, machine learning, and statistical modeling techniques to help the retail business make data-driven decisions. You will work closely with teams across marketing, product management, supply chain, and customer insights to drive business strategies and innovations. The ideal candidate should have experience in retail analytics and the ability to translate data into actionable insights. Key Responsibilities: - Leverage Retail Knowledge: Utilize your deep understanding of the retail industry (merchandising, customer behavior, product lifecycle) to design AI solutions that address critical retail business needs. - Gather and clean data from various retail sources, such as sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. - Apply machine learning algorithms, such as classification, clustering, regression, and deep learning, to enhance predictive models. - Use AI-driven techniques for personalization, demand forecasting, and fraud detection. - Utilize advanced statistical methods to optimize existing use cases and build new products to serve new challenges and use cases. - Stay updated on the latest trends in data science and retail technology. - Collaborate with executives, product managers, and marketing teams to translate insights into business actions. Professional & Technical Skills: - Strong analytical and statistical skills. - Expertise in machine learning and AI. - Experience with retail-specific datasets and KPIs. - Proficiency in data visualization and reporting tools. - Ability to work with large datasets and complex data structures. - Strong communication skills to interact with both technical and non-technical stakeholders. - A solid understanding of the retail business and consumer behavior. - Programming Languages: Python, R, SQL, Scala - Data Analysis Tools: Pandas, NumPy, Scikit-learn, TensorFlow, Keras - Visualization Tools: Tableau, Power BI, Matplotlib, Seaborn - Big Data Technologies: Hadoop, Spark, AWS, Google Cloud - Databases: SQL, NoSQL (MongoDB, Cassandra) Additional Information: - Job Title: Retail Specialized Data Scientist - Management Level: 09 - Consultant - Location: Bangalore / Gurgaon / Mumbai / Chennai / Pune / Hyderabad / Kolkata - Company: Accenture This position requires a solid understanding of retail industry dynamics, strong communication skills, proficiency in Python for data manipulation, statistical analysis, and machine learning, as well as familiarity with big data processing platforms and ETL processes. The Retail Specialized Data Scientist will be responsible for gathering, cleaning, and analyzing data to provide valuable insights for business decision-making and optimization of pricing strategies based on market demand and customer behavior.,

Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate, and advance faster than ever. As a Micron Front End Central Quality Senior Engineer, you will be a member of the worldwide quality team responsible for driving quality and reliability improvement initiatives into Front End Manufacturing network. You will work closely with Global Quality and internal customers to perform data analysis in key metrics to monitor quality and reliability health, including DPM and Uncorrectable Error (UE) metrics. Additionally, you will work with business partners to develop the strategy for continually improving product quality and reliability for Front End and supporting Time to Mature DPM program and Time to Mature Uncorrectable Error (UE) program execution. Responsibilities And Tasks Include But Not Limited To: - Design and develop methods to extract and analyze unstructured diverse Backend & Front-end data. Perform data correlations to determine the Patterns and perform the first level of debug. - Translate raw data into compelling visual stories that highlight trends, anomalies, and opportunities for improvement. - Collaborate with business partners and multi-functional teams to drive detection, Corrective and Preventive Actions in line-of-sight metrics. - Work with multi-functional team to deploy BKMs of Back End to Front End collaboration process like WL DPM forecast and RMA DPM reduction, etc. - Lead multi-functional initiatives or enabling projects that support companywide quality objectives. - Manage the projects to enable the implementation path for new initiatives. - Strong verbal and written communication skills, able to communicate the analysis and present insights to business partners. Skills And Experience You Will Need: - MS/BS or equivalent experience in Electrical or Computer Engineering. - 3 to 8 years of experience in the following areas. - Good knowledge in Semiconductor Manufacturing, common semiconductor reliability tests, and failure mechanisms. - Fluency in Python and/or R, other statistical software including scripting capability for automating analyses. - Knowledge of using statistical tools, Unix, Tableau, Power BI, JMP. - Understanding of statistics applied to data analysis, especially in Quality and reliability. - Exposure to statistical modeling, feature extraction and analysis. Good to have - supervised/unsupervised/semi-supervised learning, integrating LLM into the production environment. About Micron Technology, Inc.: Micron Technology, Inc. is an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all. With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron and Crucial brands. Every day, the innovations that our people create fuel the data economy, enabling advances in artificial intelligence and 5G applications that unleash opportunities from the data center to the intelligent edge and across the client and mobile user experience. To learn more, please visit micron.com/careers. AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification. Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.,

As a Machine Learning Engineer (MLE) at Capco in Pune, with over 8 years of experience, you will be working in an inclusive environment that values diversity and individuality. Capco is a global technology and business consultancy specializing in the financial services sector, dedicated to helping clients succeed in an ever-evolving industry. Your key responsibilities will include having a strong understanding of LLM architectures, fine-tuning pre-trained models on domain-specific data, and working with concepts such as RAG, Prompt Engineering, and Vector DBs. You should also possess expertise in containerization and orchestration technologies like Kubernetes and Docker, along with in-depth knowledge of machine learning, deep learning, and NLP. Additionally, you will be managing prioritization and technology work for building NLP, ML & AI solutions, experimenting with LLM, and ensuring best practices for ML models integration and deployment. To excel in this role, you should have at least 8-10 years of experience in deploying end-to-end data science solutions, a strong technical background from a top-tier institute, and proficiency in training and fine-tuning LLMs using frameworks like TensorFlow, PyTorch, or Hugging Face Transformer. Skills in Python, SQL, Pandas, Pyspark, GitHub, Confluence, JIRA, and cloud platforms like Azure or GCP are essential. Moreover, experience in stakeholder management, communication, and presentation skills are required to effectively present technical solutions and features in business terms. At Capco, you will have the opportunity to work on projects that will revolutionize the financial services industry, along with a work culture focused on innovation, ongoing learning opportunities, a flat non-hierarchical structure, and competitive family-friendly benefits. If you are excited about advancing your career with Capco, we encourage you to apply and join us in creating lasting value for clients and employees. For more information about Capco and its people, please visit www.capco.com.,

As an Analytics Associate Manager in the Insights and Intelligence vertical at Accenture, you will be responsible for generating insights using the latest Artificial Intelligence (AI) and Analytics techniques to deliver value to clients. Your expertise will be crucial in building world-class solutions, tackling business problems, and overcoming technical challenges using AI Platforms and technologies. It will be essential for you to leverage existing frameworks, standards, and patterns to establish architectural foundation and services needed for scalable AI applications, demonstrating your expertise through active blogging, publishing research papers, and creating awareness in this emerging field. You will be a key member of the Marketing & Customer Analytics team, which focuses on measuring, managing, and analyzing marketing activities to provide actionable insights and recommendations for optimizing ROI and operational efficiency. Your exposure to digital marketing, A/B testing, MVT, Google Analytics/Site Catalyst will be valuable in this role. Additionally, you will play a vital role in the Accenture Operations global Applied Intelligence group, working with machine learning and advanced analytics to drive data-driven decision-making and business transformation. Your responsibilities will include leading a team of data scientists to develop and deploy data science models, refining and enhancing these models based on feedback and evolving business needs. You will analyze available data to identify opportunities for enhancing brand equity, improving retail margins, achieving profitable growth, and expanding market share for clients. We are looking for candidates with extensive experience in leading Data Science and Advanced Analytics delivery teams, strong statistical programming skills in Python, R, SAS, S-plus, MATLAB, STATA, or SPSS, and experience with large data sets and big data tools like Snowflake, AWS, and Spark. Moreover, you should have solid knowledge in areas such as Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling, Multivariate Statistics, Non-parametric Methods, Reliability Models, Markov Models, Stochastic models, Bayesian Models, and experience in domains like CPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, and Supply Chain. Your role will involve client engagement, business development, and working in a global collaborative team environment. In summary, as an Analytics Associate Manager at Accenture, you will play a crucial role in leveraging data science and advanced analytics to drive insights and value for clients, while contributing to the growth and success of the organization.,

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.,

The team at Walmart Global Tech builds reusable technologies to assist in acquiring customers, onboarding and empowering merchants, and ensuring a seamless experience for all stakeholders. They focus on optimizing tariffs and assortment while maintaining Walmart's philosophy of Everyday Low Cost. Additionally, the team creates personalized omnichannel experiences for customers across various platforms. The Marketplace team serves as the gateway for Third-Party sellers, enabling them to manage their onboarding, catalog, orders, and returns. They are responsible for designing, developing, and operating large-scale distributed systems using cutting-edge technologies. As a Staff Data Scientist at Walmart Global Tech, you will be responsible for developing scalable end-to-end data science solutions for data products. You will collaborate with data engineers and analysts to build ML- and statistics-driven data quality workflows. Your role will involve solving business problems by scaling advanced Machine Learning algorithms on large datasets. You will own the MLOps lifecycle, from data monitoring to model lifecycle management. Additionally, you will demonstrate thought leadership by consulting with product and business stakeholders to deploy machine learning solutions. The ideal candidate should have knowledge of machine learning and statistics, experience with web service standards, and proficiency in architecting solutions with Continuous Integration and Continuous Delivery. Strong coding skills in Python, experience with Big Data technologies like Hadoop and Spark, and the ability to work in a big data ecosystem are preferred. Candidates should have experience in developing and deploying machine learning solutions and collaborating with data scientists. Effective communication skills and the ability to present complex ideas clearly are also desired. Educational qualifications in Computer Science, Statistics, Engineering, or related fields are preferred. Candidates with prior experience in Delivery Promise Optimization or Supply Chain domains and hands-on experience in Spark or similar frameworks will be given preference. At Walmart Global Tech, you will have the opportunity to work in a dynamic environment where your contributions can impact millions of people. The team values innovation, collaboration, and continuous learning. Join us in reimagining the future of retail and making a difference on a global scale. Walmart Global Tech offers a hybrid work model that combines in-office and virtual presence. The company provides competitive compensation, incentive awards, and a range of benefits including maternity leave, health benefits, and more. Walmart fosters a culture of belonging where every associate is valued and respected. The company is committed to creating opportunities for all associates, customers, and suppliers. As an Equal Opportunity Employer, Walmart believes in understanding, respecting, and valuing the uniqueness of individuals while promoting inclusivity.,

As an AI/ML Model Developer in this role, your core responsibility will be to build and optimize AI/ML models by leveraging Azure-based AI tools, TensorFlow, PyTorch, and similar frameworks. You will focus on the Logistics & Maritime industries, addressing complex business challenges using AI. Your expertise in cloud-based AI services for data storage, processing, and model deployment, with extensive use of Azure (and optionally AWS), will be crucial in this position. Your key responsibilities will involve designing, developing, and implementing machine learning algorithms. You will collaborate with business teams to translate requirements into technical AI/ML solutions, ensuring data quality for training models through data preprocessing. Using cloud tools like Azure/AWS, you will optimize models for high performance, perform training, tuning, and evaluation of models for continuous improvement. Staying updated on advancements in AI/ML, exploring new techniques, and providing data analysis & visualization to support business decision-making will be essential. You will also enhance existing products with AI-driven features such as automation, prediction, and recommendations while maintaining records for AI models, pipelines, and experiments. To qualify for this position, you should hold a Bachelor's/Master's degree in Engineering Science, Data Science, or a related field, along with 3-4 years of relevant AI/ML experience, preferably in Logistics and Maritime sectors. Key skills and technologies required include proficiency in programming languages like Python, R, or Java, expertise in machine learning techniques such as supervised/unsupervised learning, regression, classification, and clustering. Familiarity with AI frameworks like TensorFlow, PyTorch, Keras, or Scikit-learn, and experience with cloud platforms like AWS or Azure tools for AI services are necessary. Specific experience with Logistics and Maritime products, along with additional skills in deep learning, NLP, and computer vision, will be advantageous. Strong analytical thinking, problem-solving, and communication skills are essential soft skills for this role. This is a full-time, permanent position with a day shift schedule that requires in-person work at the designated location.,

At Rhythm, our values serve as the cornerstone of our organization. We are deeply committed to customer success, fostering innovation, and nurturing our employees. These values shape our decisions, actions, and interactions, ensuring that we consistently create a positive impact on the world around us. Rhythm Innovations is currently looking for a skilled and enthusiastic Machine Learning (ML) Developer to conceptualize, create, and implement machine learning models that enhance our supply chain risk management and other cutting-edge solutions. As an ML Developer, you will collaborate closely with our AI Architect and diverse teams to construct intelligent systems that tackle intricate business challenges and further our goal of providing unparalleled customer satisfaction. Key Responsibilities Model Development: Devise, execute, and train machine learning models utilizing cutting-edge algorithms and frameworks like TensorFlow, PyTorch, and scikit-learn. Data Preparation: Process, refine, and convert extensive datasets for the training and assessment of ML models. Feature Engineering: Identify and engineer pertinent features to enhance model performance and precision. Algorithm Optimization: Explore and implement advanced algorithms to cater to specific use cases such as classification, regression, clustering, and anomaly detection. Integration: Coordinate with software developers to integrate ML models into operational systems and guarantee smooth functionality. Performance Evaluation: Assess model performance using suitable metrics and consistently refine for accuracy, efficacy, and scalability. MLOps: Aid in establishing and overseeing CI/CD pipelines for model deployment and monitoring in production environments. Research and Development: Stay abreast of the latest breakthroughs in Gen AI AI/ML technologies and propose inventive solutions. Collaboration: Engage closely with data engineers, product teams, and stakeholders to grasp requirements and deliver customized ML solutions. Requirements Educational Background: Bachelor's in Engineering in Computer Science, Data Science, Artificial Intelligence, or a related field. Experience: 3 to 6 years of practical experience in developing and deploying machine learning models. Technical Skills Proficiency in Python and ML libraries/frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Experience with data manipulation tools like Pandas, NumPy, and visualization libraries such as Matplotlib or Seaborn. Familiarity with big data frameworks (Hadoop, Spark) is advantageous. Knowledge of SQL/NoSQL databases and data pipeline tools (e.g., Apache Airflow). Hands-on experience with cloud platforms (AWS, Azure, Google Cloud) and their Gen AI AI/ML services. Thorough understanding of supervised and unsupervised learning, deep learning, and reinforcement learning. Exposure to MLOps practices and model deployment pipelines. Soft Skills Strong problem-solving and analytical abilities. Effective communication and teamwork skills. Capability to thrive in a dynamic, collaborative environment.,

We are looking for an experienced AI/ML Architect to spearhead the design, development, and deployment of cutting-edge AI and machine learning systems. As the ideal candidate, you should possess a strong technical background in Python and data science libraries, profound expertise in AI and ML algorithms, and hands-on experience in crafting scalable AI solutions. This role demands a blend of technical acumen, leadership skills, and innovative thinking to enhance our AI capabilities. Your responsibilities will include identifying, cleaning, and summarizing complex datasets from various sources, developing Python/PySpark scripts for data processing and transformation, and applying advanced machine learning techniques like Bayesian methods and deep learning algorithms. You will design and fine-tune machine learning models, build efficient data pipelines, and leverage distributed databases and frameworks for large-scale data processing. In addition, you will lead the design and architecture of AI systems, with a focus on Retrieval-Augmented Generation (RAG) techniques and large language models. Your qualifications should encompass 5-7 years of total experience with 2-3 years in AI/ML, proficiency in Python and data science libraries, hands-on experience with PySpark scripting and AWS services, strong knowledge of Bayesian methods and time series forecasting, and expertise in machine learning algorithms and deep learning frameworks. You should also have experience in structured, unstructured, and semi-structured data, advanced knowledge of distributed databases, and familiarity with RAG systems and large language models for AI outputs. Strong collaboration, leadership, and mentorship skills are essential. Preferred qualifications include experience with Spark MLlib, SciPy, StatsModels, SAS, and R, a proven track record in developing RAG systems, and the ability to innovate and apply the latest AI techniques to real-world business challenges. Join our team at TechAhead, a global digital transformation company known for AI-first product design thinking and bespoke development solutions. With over 14 years of experience and partnerships with Fortune 500 companies, we are committed to driving digital innovation and delivering excellence. At TechAhead, you will be part of a dynamic team that values continuous learning, growth, and crafting tailored solutions for our clients. Together, let's shape the future of digital innovation worldwide!,

As a Python AI/ML Developer with 4-5 years of experience, your main responsibility will be to design, develop, and maintain Python applications while ensuring code quality, efficiency, and scalability. You will collaborate with cross-functional teams to understand project requirements and deliver solutions that align with business objectives. Implementing AI/ML algorithms and models to solve complex problems and extract valuable insights from data will be a key part of your role. Additionally, you will be developing and maintaining RESTful APIs to integrate Python applications with other systems. It is essential to stay updated with the latest trends and technologies in Python development and AI/ML. To excel in this role, you should have a strong proficiency in Python programming, including object-oriented programming and design patterns. Experience with popular Python libraries and frameworks such as NumPy, Pandas, Scikit-learn, TensorFlow, and PyTorch is required. Knowledge of AI/ML concepts, algorithms, and techniques, including supervised and unsupervised learning, is crucial. Experience working with data pipelines and ETL processes is beneficial, and hands-on experience with chatbot applications is necessary. Excellent problem-solving and analytical skills are essential, along with the ability to work independently and as part of a team. Strong communication and documentation skills are also important. Preferred qualifications include experience with cloud platforms such as AWS, GCP, or Azure, knowledge of natural language processing (NLP) or computer vision, experience with machine learning deployment and operationalization, and contributions to open-source Python projects. Stay updated with the latest advancements in technology to enhance your skills and contribute effectively to the development of innovative solutions.,

You are a highly skilled and motivated Lead Data Scientist / Machine Learning Engineer sought to join a team pivotal in the development of a cutting-edge reporting platform. This platform is designed to measure and optimize online marketing campaigns effectively. Your role will involve focusing on data engineering, ML model lifecycle, and cloud-native technologies. You will be responsible for designing, building, and maintaining scalable ELT pipelines, ensuring high data quality, integrity, and governance. Additionally, you will develop and validate predictive and prescriptive ML models to enhance marketing campaign measurement and optimization. Experimenting with different algorithms and leveraging various models will be crucial in driving insights and recommendations. Furthermore, you will deploy and monitor ML models in production and implement CI/CD pipelines for seamless updates and retraining. You will work closely with data analysts, marketing teams, and software engineers to align ML and data solutions with business objectives. Translating complex model insights into actionable business recommendations and presenting findings to stakeholders will also be part of your responsibilities. Qualifications & Skills: Educational Qualifications: - Bachelors or Masters degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, or related field. - Certifications in Google Cloud (Professional Data Engineer, ML Engineer) is a plus. Must-Have Skills: - Experience: 5-10 years with the mentioned skillset & relevant hands-on experience. - Data Engineering: Experience with ETL/ELT pipelines, data ingestion, transformation, and orchestration (Airflow, Dataflow, Composer). - ML Model Development: Strong grasp of statistical modeling, supervised/unsupervised learning, time-series forecasting, and NLP. - Programming: Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL for large-scale data processing. - Cloud & Infrastructure: Expertise in GCP (BigQuery, Vertex AI, Dataflow, Pub/Sub, Cloud Storage) or equivalent cloud platforms. - MLOps & Deployment: Hands-on experience with CI/CD pipelines, model monitoring, and version control (MLflow, Kubeflow, Vertex AI, or similar tools). - Data Warehousing & Real-time Processing: Strong knowledge of modern data platforms for batch and streaming data processing. Nice-to-Have Skills: - Experience with Graph ML, reinforcement learning, or causal inference modeling. - Working knowledge of BI tools (Looker, Tableau, Power BI) for integrating ML insights into dashboards. - Familiarity with marketing analytics, attribution modeling, and A/B testing methodologies. - Experience with distributed computing frameworks (Spark, Dask, Ray). Location: - Bengaluru Brand: - Merkle Time Type: - Full time Contract Type: - Permanent,