Data Science Engineer – AI/ML & Data Engineering

We are seeking a highly skilled and motivated Data Science Engineer with strong experience in AI/ML, Data Engineering, and cloud infrastructure (AWS). You will play a critical role in shaping intelligent, scalable, and data-driven solutions that deliver meaningful impact for our clients.
As part of a cross-functional team, you will design and build end-to-end data pipelines, develop predictive models, and deploy production-ready data products across a variety of industries.Key Responsibilities:Collaborate with engineering teams, data scientists, and clients to build and deploy impactful data products.Design, develop, and maintain scalable and cost-efficient data pipelines on AWS.Build and integrate AI/ML models to enhance product intelligence and automation.Develop backend and data components using Python, SQL, and PySpark.Leverage AI frameworks and tools to deploy models in production environments.Work directly with stakeholders to understand and translate their data needs into technical solutions.Implement and manage cloud infrastructure including PostgreSQL, Redshift, Airflow, and MongoDB.Follow best practices in data architecture, model training, testing, and performance optimization.Required Qualifications:Experience:Minimum 3 years in Data Engineering, Software Development, or related roles.At least 2 years of hands-on experience applying AI/ML algorithms for real-world use cases.Proven experience in building and managing AWS-based cloud infrastructure.Strong background in data analysis, mining, and model interpretability.Technical Skills:Programming Languages: Python, SQL, PySparkFrameworks/Tools: Airflow, Django (optional), Scikit-learn, TensorFlow or PyTorchDatabases: PostgreSQL, Redshift, MongoDBExperience with real-time and batch data workflowsSoft Skills:Strong problem-solving and logical reasoning abilitiesExcellent communication skills for client interactions and internal collaborationAbility to work in a fast-paced, dynamic environmentNice to Have:Experience with MLOps and CI/CD for ML pipelinesExposure to BI tools like Tableau, Power BI, or MetabaseKnowledge of data security and governance on AWS