Role: As a Cloud Data Engineer at AlgoAnalytics, you will be responsible for designing, deploying, and optimizing cloud-based data solutions. You will work with MLOps pipelines, containerization technologies, and cloud services to ensure smooth and scalable deployment of data-driven applications. This role offers an exciting opportunity to collaborate with cross-functional teams, work on cutting-edge cloud infrastructure, and enhance automation in data workflows. Responsibilities: Design, develop, and manage cloud-based data solutions on AWS/Azure. Implement and optimize CI/CD pipelines for seamless deployment of machine learning models and data applications. Work with Docker and other containerization technologies to streamline deployment and scalability. Automate and monitor cloud infrastructure to ensure reliability and performance. Support Data Storage Solutions, Database Management, and cloud-based ETL pipelines. Collaborate with data scientists, engineers, and DevOps teams to integrate cloud and MLOps best practices. Maintain version control and workflow efficiency using Git and DevOps methodologies. Skillsets: Familiarity with Cloud Platforms (AWS, Azure, or Google Cloud) and cloud-native services. Experience with CI/CD pipelines, container orchestration, and cloud deployment. Proficiency in Python for backend development. Understanding of Databases and Data Storage Solutions in a cloud environment. Experience with Docker, Kubernetes, and Infrastructure-as-Code (IaC) tools. Strong problem-solving skills and ability to troubleshoot cloud-based deployments. Familiarity with Git for version control and team collaboration. Passion for learning new technologies and adapting to evolving cloud architectures. Nice-to-Have (Not Mandatory): Exposure to MLOps frameworks for model training and deployment. Understanding of security best practices in cloud environments. Knowledge of Serverless computing and API development using RESTful Frameworks. Familiarity with Web Development (HTML, CSS, JavaScript, React.JS). This is an excellent opportunity for individuals who are passionate about Cloud Computing, Solution Architecture, and Automation. If you are eager to work on cutting-edge cloud technologies and enhance large-scale data applications, we would love to have you on board!

Role & responsibilities Posting entries in tally Managing and preparing payroll Making Invoices and related calculations Preparing reports in excel Tax compliance Other related duties as assigned. Preferred candidate profile Proficient in Excel. Familiar with Word Strong accounting knowledge, Proficient in Tally ERP 9 Attention to detail and good with financial numbers Good communication skills Ability to work independently and meet deadlines Self motivated and diligent

AlgoAnalytics is looking for a Data Scientist who has the passion for AI/ML solution development and cutting-edge work in Gen AI. Minimum 3 years of experience in AI/MI including Deep Learning, and exposure to Gen AI/LLM is required along with tools/techs/libraries like Agentic AI, Dify/Autogen, Langraphetc. Detailed understanding of Cloud technologies and Deployment with good hands-on experience is an added advantage. Key Responsibilities: AI/ML & Gen AI Development: Develop Gen AI/LLM models using OpenAI, Llama, or other open-source/offline models. Utilize Agentic AI frameworks and tools like Dify, Autogen, Langraph to build intelligent systems. Perform prompt engineering, fine-tuning, and dataset-specific model optimization. Implement cutting-edge research from AI/ML and Gen AI domains. Work on cloud-based deployments of AI/ML models for scalability and production readiness. Leadership & Mentoring: Troubleshoot AI/ML, Gen AI, and cloud deployment challenges. Mentor junior team members and contribute to their skill development. Identify team members for mentoring, hiring, and technical initiatives. Ensure smooth project execution, deadline management, and client interactions. Research & Innovation: Explore and implement recent AI/ML research in practical applications. Contribute to research publications, internal knowledge-sharing, and AI innovation. Qualifications: 2-3 years of hands-on experience in Machine Learning, Deep Learning, and Gen AI/LLMs. Bachelors/Masters degree in Computer Science, Engineering, Mathematics, or Statistics (with strong programming knowledge). Skills: Programming: Strong expertise in Python and relevant ML/AI libraries. AI/ML & Gen AI: Deep understanding of Machine Learning, Deep Learning, and Generative AI/LLMs. Agentic AI & Automation: Experience with Dify, Autogen, Langraph, and similar tools. Cloud & Deployment: Knowledge of cloud platforms (AWS, GCP, Azure) and MLOps deployment pipelines. Communication & Leadership: Strong ability to manage teams, meet project deadlines, and collaborate with clients. Note - We would prefer only Pune based candidates

Skills Programming: Strong expertise in Python and relevant ML/AI libraries. AI/ML & Gen AI: Deep understanding of Machine Learning, Deep Learning, and Generative AI/LLMs. Agentic AI & Automation: Experience with Dify, Autogen, Langraph, and similar tools. Cloud & Deployment: Knowledge of cloud platforms (AWS, GCP, Azure) and MLOps deployment pipelines. Communication & Leadership: Strong ability to manage teams, meet project deadlines, and collaborate with clients. Responsibilities AI/ML & Gen AI Development Develop Gen AI/LLM models using OpenAI, Llama, or other open-source/offline models. Utilize Agentic AI frameworks and tools like Dify, Autogen, Langraph to build intelligent systems. Perform prompt engineering, fine-tuning, and dataset-specific model optimization. Implement cutting-edge research from AI/ML and Gen AI domains. Work on cloud-based deployments of AI/ML models for scalability and production readiness. Leadership & Mentoring Troubleshoot AI/ML, Gen AI, and cloud deployment challenges. Mentor junior team members and contribute to their skill development. Identify team members for mentoring, hiring, and technical initiatives. Ensure smooth project execution, deadline management, and client interactions. Research & Innovation Explore and implement recent AI/ML research in practical applications. Contribute to research publications, internal knowledge-sharing, and AI innovation. Qualifications 2-3 years of hands-on experience in Machine Learning, Deep Learning, and Gen AI/LLMs. Bachelors/Masters degree in Computer Science, Engineering, Mathematics, or Statistics (with strong programming knowledge).

Skills and Qualifications 2 to 4 years of experience. Bachelor s degree in Comp Sc / IT (or equivalent) with strong background in programming. Experience on Python stack and any cloud stack. Experience working with large database to access, manipulate and process data. Exposure to text parsing, mining, and classification. Good understanding of fundamentals of AI and ML. Experience with machine learning tools and libraries for NLP is a plus. Excellent verbal and written communication skills. Responsibilities Extension of AI Model through technical configurations. Fine-tune the AI Model for customer specific data sets through key words, weightages, rules and preferences. Tailor, develop, test and debug AI models to specific customer needs. Process high volume of data to extract information and store in relational database environments. Write efficient algorithms, optimized code and unit testing of code developed. Implement and manage code customization, build and deployment with TFS or similar tools. Packaging and deploying solutions in cloud.

Skillsets: Familiarity with Cloud Platforms (AWS, Azure, or Google Cloud) and cloud-native services. Experience with CI/CD pipelines, container orchestration, and cloud deployment. Proficiency in Python for backend development. Understanding of Databases and Data Storage Solutions in a cloud environment. Experience with Docker, Kubernetes, and Infrastructure-as-Code (IaC) tools. Strong problem-solving skills and ability to troubleshoot cloud-based deployments. Familiarity with Git for version control and team collaboration. Passion for learning new technologies and adapting to evolving cloud architectures. Nice-to-Have: Exposure to MLOps frameworks for model training and deployment. Understanding of security best practices in cloud environments. Knowledge of Serverless computing and API development using RESTful Frameworks. Familiarity with Web Development (HTML, CSS, JavaScript, React.JS). Responsibilities: Design, develop, and manage cloud-based data solutions on AWS/Azure. Implement and optimize CI/CD pipelines for seamless deployment of machine learning models and data applications. Work with Docker and other containerization technologies to streamline deployment and scalability. Automate and monitor cloud infrastructure to ensure reliability and performance. Support Data Storage Solutions, Database Management, and cloud-based ETL pipelines. Collaborate with data scientists, engineers, and DevOps teams to integrate cloud and MLOps best practices. Maintain version control and workflow efficiency using Git and DevOps methodologies.

Skills Mandatory Skills: Cloud (AWS/GCP or Azure), Database (RDBMS, No-SQL/Mongo), PL/SQL, Python/R programming fundamentals, Apache Spark Preferred Skills: Snowflake, Data Bricks, Kafka, Docker, Kubernetes, Tableau Preference for those with at least introductory certification to AWS or Azure or GCP Experience in configuring Spark cluster Experience bringing prototypes to production on NoSQL platforms Good knowledge of Spark with Python Hands-on experience in the Linux environment with strong coding skills and fundamentals in data structures. This opportunity offers strong exposure to Machine Learning and Deep Learning Qualification: BE/BTech in any stream. BSc/MSc in Math/Stats/IT/BBA. Preferred basic cloud certification (AWS/Azure or GCP). PG Diploma Data Science. Any other branch with proven technology certifications. Experience: 1-3 years of relevant experience. Responsibilities: Develop and maintenance of big data and streaming data architecture and infrastructure Implement ways to improve data reliability and setup data governance Work with teams helping them move existing projects into big data cloud platforms Work with teams to implement solutions on these platforms Working with teams to help troubleshoot problems related to the tools Work with architects and provide inputs and feedback on big data technologies to be used Setup and maintain one of many Cloud data foundation in AWS/GCP/Azure/DataBricks depending on project requirements Handling big-data pipelines

Skillsets: Write clean, efficient, and maintainable code using languages such as Nodejs, Python, C# Build React, NextJS front-end applications adhering to Figma visual design Develop and manage MongoDB, PostgreSQL databases, ensuring data integrity and security Create and maintain RESTful and GraphQL APIs Implement JWT and OAuth for secure authentication and authorization Implement automated testing frameworks for Test Driven Development Manage the deployment process and app containerization Work with development teams and product managers to iterate and optimize solutions Lead and mentor junior developers, providing guidance and support Nice-to-Have: Hands-on experience with cloud platforms (AWS, Azure, or GCP) and CI/CD pipelines. Familiarity with containerization (Docker) and orchestration (Kubernetes). Strong understanding of software development principles, testing, and code reviews. Excellent problem-solving, analytical, and communication skills. Experience with version control systems (Git). Experience with C# .NET, other backend languages. Experience with DevOps (Jenkins, AWS CodePipeline, GitHub Actions) tools is a plus. Responsibilities: Develop and deploy scalable, cloud-native applications on AWS, Azure, or GCP, directly impacting critical AI/ML deployments. Design and deliver high-performance RESTful and GraphQL APIs that power secure, data-intensive web applications. Improve system performance and scalability, contributing to a measurable reduction in API response times and infrastructure costs. Build a robust front-end architecture using React and TypeScript, delivering an intuitive user experience for complex AI/ML tools. Ensure all systems meet high standards of code quality, security, and reliability, minimizing production issues and ensuring seamless deployments.

Mandatory Skills: Cloud based ML foundation (AWS Sage maker OR GCP Vertex AI or Azure Machine Learning), Python/R programming expertise, Communication Preferred Skills: Database (RDBMS, No-SQL/Mongo/RDS/Big-Query), PL/SQL, Docker, Kubernetes Preference for those with certification in AWS or Azure or GCP with exposure to ML services and APIs Experience in building deep learning models in the Cloud Hands on experience in Linux environment with strong coding skills and fundamentals in data structures. Good conceptual understanding of Machine Learning/Deep Learning/Natural Language Processing Strong verbal and written communication skills This opportunity offers strong exposure to Machine Learning and Deep Learning Qualification: BE/BTech in computer science. BSc/MSc in Math/Stats/IT. Preferred cloud certifications (AWS/Azure or GCP). PG Diploma Data Science. Any other branch with proven technology certifications. Experience: 1-3 years of relevant experience. Responsibilities: Develop and maintain machine learning models using cloud based platform-as-a-service Implement ways to improve machine learning accuracy and data reliability Work with teams helping them move existing ML projects into cloud platforms Work with teams to implement solutions on these platforms Working with teams to help troubleshoot problems related to the Cloud Work with architects and provide inputs and feedback on Cloud ML technologies Setup and maintain one of many Cloud ML foundation in AWS/GCP/Azure depending on project requirements Handling training and inference engines around machine learning initiatives Ability to use built in ML/DL services and APIs from the cloud providers

Role & responsibilities Design, build, deploy and optimize computer vision algorithms/models for tasks such as image recognition, object detection, segmentation, and pattern recognition to solve real world problems Implement and test machine learning and deep learning models for visual data analysis Collaborate with data scientists, software engineers, and domain experts to integrate computer vision solutions into products and applications Collect, preprocess, and annotate datasets for training and validating models Evaluate and improve the performance, scalability, and reliability of deployed vision systems Collaborate with cross-functional teams Stay updated with the latest research and advancements in computer vision and AI, and experiment with new techniques Document algorithms, models, and workflows, and contribute to technical reports Preferred candidate profile Bachelors or Master’s degree in Computer Science, Electrical Engineering, or a related field 2-3 years of experience in computer vision, machine learning, or a related area Proficiency in Python and experience with libraries such as OpenCV, TensorFlow, or PyTorch Able to write clean, maintainable and scalable code which leads to robust, adaptable and maintainable code Solid understanding of image processing techniques and computer vision algorithms Experience with deep learning frameworks (e.g., TensorFlow, PyTorch, Keras) Familiarity with version control systems (e.g., Git) Strong analytical and problem-solving skills Good communication and documentation abilities