Job Title: Data Scientist – AWS | AI/ML | Microservices | CI/CD
Location: Chennai, Bengaluru, Hyderabad, Pune, Mumbai, Noida, NCR
Experience: 3–7 years
Job Type: Full-Time
Department: Data Science / Engineering
Job Summary:
We are seeking a highly skilled and motivated Data Scientist to join our team and drive the development and deployment of advanced machine learning solutions in a cloud-native environment. The ideal candidate has a strong foundation in data science and machine learning, with hands-on experience in building, training, and deploying models using AWS services, microservices architecture, and CI/CD pipelines.
Key Responsibilities:
- Design, develop, and deploy scalable machine learning models and algorithms.
- Work with large-scale datasets, apply data wrangling, feature engineering, and model evaluation techniques.
- Leverage AWS cloud services (SageMaker, Lambda, ECS, S3, RDS, etc.) for AI/ML model development and deployment.
- Develop and deploy microservices for model inference and automation.
- Collaborate with DevOps teams to implement and maintain CI/CD pipelines for model training, testing, and production deployment.
- Translate business requirements into ML/AI solutions and provide actionable insights.
- Monitor and improve model performance post-deployment using feedback loops and retraining mechanisms.
- Ensure data security, privacy, and compliance within the cloud infrastructure.
Required Skills & Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
- 3+ years of experience as a Data Scientist or ML Engineer.
- Proficiency in Python and popular ML libraries (scikit-learn, TensorFlow, PyTorch, etc.).
- Hands-on experience with AWS AI/ML tools like SageMaker, Glue, Step Functions, Lambda, etc.
- Experience building and deploying microservices using Docker and RESTful APIs.
- Solid understanding of CI/CD tools such as Jenkins, GitHub Actions, CodePipeline, or similar.
- Familiarity with MLOps practices and model lifecycle management.
- Strong problem-solving skills and ability to work in a fast-paced, agile environment.
Preferred Qualifications:
- Experience with container orchestration using Kubernetes or Amazon ECS/EKS.
- Exposure to data lake architecture and data warehousing on cloud platforms.
- Knowledge of real-time streaming data processing (e.g., using Kinesis, Kafka).
- Certifications such as AWS Certified Machine Learning – Specialty or AWS Solutions Architect.
Why Join Us:
- Work on cutting-edge AI/ML projects in a dynamic, innovation-driven environment.
- Opportunity to influence architecture and best practices.
- Collaborative team culture focused on learning and growth.
- Flexible working options and competitive compensation.