7.0 - 12.0 years

20 - 30 Lacs

Kolkata, Hyderabad, Bengaluru

Work from Office

Responsibilities Design, develop, and deploy scalable AI/ML solutions using AWS services such as Amazon Bedrock, SageMaker, Amazon Q, Amazon Lex, Amazon Connect, and Lambda. Implement and optimize large language model (LLM) applications using Amazon Bedrock, including prompt engineering, fine-tuning, and orchestration for specific business use cases. Build and maintain end-to-end machine learning pipelines using SageMaker for model training, tuning, deployment, and monitoring. Integrate conversational AI and virtual assistants using Amazon Lex and Amazon Connect, with seamless user experiences and real-time inference. Leverage AWS Lambda for event-driven execution of model inference, data preprocessing, and microservices. Design and maintain scalable and secure data pipelines and AI workflows, ensuring efficient data flow to and from Redshift and other AWS data stores. Implement data ingestion, transformation, and model inference for structured and unstructured data using Python and AWS SDKs. Collaborate with data engineers and scientists to support development and deployment of ML models on AWS. Monitor AI/ML applications in production, ensuring optimal performance, low latency, and cost efficiency across all AI/ML services. Ensure implementation of AWS security best practices, including IAM policies, data encryption, and compliance with industry standards. Drive the integration of Amazon Q for enterprise AI-based assistance and automation across internal processes and systems. Participate in architecture reviews and recommend best-fit AWS AI/ML services for evolving business needs. Stay up to date with the latest advancements in AWS AI services, LLMs, and industry trends to inform technology strategy and innovation. Prepare documentation for ML pipelines, model performance reports, and system architecture. Qualifications we seek in you: Minimum Qualifications Proven hands-on experience with Amazon Bedrock, SageMaker, Lex, Connect, Lambda, and Redshift. Strong knowledge and application experience with Large Language Models (LLMs) and prompt engineering techniques. Experience building production-grade AI applications using AWS AI or other generative AI services. Solid programming experience in Python for ML development, data processing, and automation. Proficiency in designing and deploying conversational AI/chatbot solutions using Lex and Connect. Experience with Redshift for data warehousing and analytics integration with ML solutions. Good understanding of AWS architecture, scalability, availability, and security best practices. Familiarity with AWS development, deployment, and monitoring tools (CloudWatch, CodePipeline, etc.). Strong understanding of MLOps practices including model versioning, CI/CD pipelines, and model monitoring. Strong communication and interpersonal skills to collaborate with cross-functional teams and stakeholders. Ability to troubleshoot performance bottlenecks and optimize cloud resources for cost-effectiveness Preferred Qualifications: AWS Certification in Machine Learning, Solutions Architect, or AI Services. Experience with other AI tools (e.g., Anthropic Claude, OpenAI APIs, or Hugging Face). Knowledge of streaming architectures and services like Kafka or Kinesis.

Posted 1 month ago

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Sr. Data Scientist Int9 Solutions

5.0 - 10.0 years

12 - 18 Lacs

Bengaluru

Work from Office

We are looking for a skilled Data Scientist to develop and implement predictive models that drive business decision-making. The ideal candidate will have strong expertise in machine learning, data analysis, and statistical techniques, using tools such as Python, R and Jupyter Notebooks. This role involves collaborating with cross-functional teams to translate business challenges into data-driven solutions. Requirements and Qualifications: Must-Have Skills: Bachelor's degree in Data Science, Statistics, Computer Science, or a related field. 5+ years of experience in data science roles. Strong experience in predictive modeling and machine learning. Proficiency in Python and R for data analysis and model development. Hands-on experience with Jupyter Notebooks for data exploration. Solid knowledge of statistics, probability, and hypothesis testing. Experience working with large datasets and data-wrangling techniques. Ability to build data-driven visualizations and communicate insights effectively. Nice-to-Have Skills: Experience in HR analytics and workforce data modeling. Familiarity with machine learning frameworks like TensorFlow, PyTorch, or Scikit-Learn. Knowledge of SQL for data querying and manipulation. Experience with big data tools like Spark, Hadoop, or AWS ML services. Understanding of data visualization tools such as Tableau or Power BI. Roles and Responsibilities: Develop and implement predictive models to support business decision-making. Build and deploy machine learning algorithms to solve complex problems. Analyze large datasets using statistical and data science techniques. Use Python, R, and Jupyter Notebooks for data analysis, modeling, and visualization. Collaborate with cross-functional teams to translate business challenges into data-driven insights. Continuously improve and optimize machine learning models for accuracy and efficiency. Present findings to stakeholders in a clear and actionable manner.

Posted 2 months ago

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