Job Summary:We are seeking a skilled and innovative Data Scientist with a strong foundation in hyperparameter optimization, TensorFlow Lite, and IoT-based electronics. The ideal candidate will have experience in building and deploying efficient machine learning models on resource-constrained embedded devices. You will work closely with hardware, firmware, and software teams to optimize ML pipelines and enable intelligent edge solutions. Key Responsibilities:Develop and deploy ML models for embedded/IoT devices using TensorFlow Lite or similar frameworks.Design and run experiments to optimize model performance through hyperparameter tuning (Grid Search, Random Search, Bayesian Optimization, etc.).Work with cross-functional teams to integrate ML models into embedded systems and validate them on target hardware.Preprocess and analyze sensor/electronic data from IoT devices.Conduct performance evaluations (accuracy, latency, memory footprint) and ensure models meet hardware constraints.Automate training, validation, and deployment workflows using scripting and ML tools.Stay updated with emerging trends in TinyML, on-device learning, and efficient model architectures. Required Qualifications:Bachelor’s or Master’s degree in Computer Science, Electronics, Electrical Engineering, or a related field.3+ years of experience in applied machine learning or data science roles.Proficiency in Python, TensorFlow, and TensorFlow Lite.Strong understanding of hyperparameter optimization techniques and experience with relevant tools/libraries (Optuna, HyperOpt, Ray Tune, etc.).Good understanding of edge AI constraints (compute, memory, power consumption).Experience in preprocessing data from sensors such as accelerometers, gyros, temperature, etc.Familiarity with embedded development tools and debugging. Preferred Skills (Nice to Have):Knowledge of C/C++ for embedded systems.Experience with TinyML and model quantization/pruning techniques.Exposure to platforms like Edge Impulse, TensorFlow Lite Micro, or Arduino ML.Understanding of communication protocols (BLE, MQTT, LoRa, etc.). What We Offer:Work on cutting-edge AI for IoT projects with real-world impact.Collaborative and growth-oriented team environment.Competitive salary and benefits package.

As a Microsoft Azure Engineer in Bangalore (Hybrid) with 5+ years of experience, you will be responsible for building and optimizing cloud solutions on Microsoft Azure. Your expertise in Azure Synapse, Azure Data Factory, and related cloud technologies will be crucial in ensuring scalability, security, and automation. Your key responsibilities will include: Cloud Data Engineering & Processing: - Designing and optimizing ETL/ELT pipelines using Azure Synapse and Data Factory. - Developing and managing data pipelines, data lakes, and workflows within the Azure ecosystem. - Implementing data security, governance, and compliance best practices. Backend & Application Development: - Developing scalable cloud applications using Azure Functions, Service Bus, and Event Grid. - Building RESTful APIs and microservices for cloud-based data processing. - Integrating Azure services to enhance data accessibility and processing. Cloud & DevOps: - Deploying and managing solutions using Azure DevOps, CI/CD, and Infrastructure as Code (Terraform, Bicep). - Optimizing cloud costs and ensuring high availability of data platforms. - Implementing logging, monitoring, and security best practices. Required Skills & Experience: - 5+ years of experience in Azure cloud engineering and development. - Strong expertise in Azure Synapse, Data Factory, and Microsoft Fabric. - Proficiency in CI/CD, Azure DevOps, and related tools. - Experience with Infrastructure as Code (Terraform, Bicep). - Hands-on knowledge of Azure Functions, Service Bus, Event Grid, and API development. - Familiarity with SQL, T-SQL, Cosmos DB, and relational databases. - Strong experience in data security and compliance. Preferred Skills (Good to Have): - Knowledge of Databricks, Python, and ML models for data processing. - Familiarity with event-driven architectures (Kafka, Event Hubs). - Azure certifications (e.g., DP-203, AZ-204). Apply now if you are ready to leverage your expertise in Microsoft Azure to contribute to building robust cloud solutions and optimizing data processing workflows.,

We are hiring Microsoft Azure Data Engineers to join our team. You will be responsible for designing, building, and maintaining scalable data pipelines and solutions on Azure cloud infrastructure. This includes working with services like Azure Data Factory, Azure Synapse, Azure Data Lake, and Cosmos DB. Responsibilities Design and implement scalable ETL/ELT pipelines using Azure Data Factory. Build and manage data integration workflows across various data sources. Develop and optimize data models in Azure Synapse Analytics and SQL Database. Implement data quality and governance practices in the Azure environment. Work closely with data scientists, analysts, and business stakeholders to ensure reliable data delivery. Monitor and troubleshoot data pipelines and ensure performance and security best practices. Automate deployment using CI/CD pipelines in Azure DevOps. Implement and maintain data lake solutions using Azure Data Lake Storage (ADLS). Qualifications Strong understanding of Azure cloud services, especially in data engineering and storage. Hands-on experience with Azure Data Factory, Synapse Analytics, ADLS, Azure SQL, and Cosmos DB. Proficiency in SQL and working with structured and semi-structured data. Experience with Python, PySpark, or Scala for data transformation. Knowledge of data warehousing concepts and dimensional modeling. Experience in creating and optimizing stored procedures, views, and functions. Understanding of data security, encryption, and access control in Azure. Experience with CI/CD tools like Azure DevOps for automating data pipelines. Knowledge of Power BI or similar tools is a plus. Experience working in Agile environments with Git version control. Familiarity with monitoring tools like Azure Monitor and Log Analytics. Strong problem-solving skills and attention to detail.