Data Science Engineer

4 days ago

Hyderabad, Telangana, India Enterprise Minds Full time ₹ 1,04,000 - ₹ 1,30,878 per year

?? Location:  Hyderabad

????? Experience:  2–4 Years

?? Employment Type:  Full-time

*About the Role: 

We are seeking a Data Science Engineer*  with 2 to 6 years of experience who is passionate about building scalable, robust, and high-performance machine learning systems. You will play a key role in bridging the gap between data science research and production, ensuring smooth deployment, monitoring, and maintenance of ML models and data pipelines in cloud environments.

*Key Responsibilities:- Collaborate with data scientists and analysts to operationalize ML models  and deploy them into scalable production systems.
- Design, build, and maintain automated pipelines  for data ingestion, transformation, model training, validation, deployment, and monitoring.
- Implement MLOps best practices  for model tracking, versioning, testing, and automated retraining using tools like MLflow, Kubeflow, or SageMaker .
- Work with large-scale data platforms and ensure data quality, integrity, and accessibility  for training and inference.
- Optimize system performance and model efficiency using containerization tools  such as Docker and Kubernetes .
- Collaborate in an Agile/Scrum*  environment and actively contribute to sprint planning, reviews, and retrospectives.
- Monitor and troubleshoot models in production for accuracy, drift, and performance degradation.

*RequiredSkills:
- *2 to 4 years  of hands-on experience in data science engineering or ML engineering roles.
- Proficiency in Python  with solid understanding of data structures, algorithms , and software engineering practices .
- Practical experience with machine learning libraries  such as scikit-learn, TensorFlow, or PyTorch .
- Experience with cloud platforms  (AWS, Azure, or GCP) and their ML/AI services (SageMaker, Azure ML, etc.).
- Sound knowledge of MLOps concepts  and tools like MLflow, Airflow, Kubeflow , or similar.
- Strong SQL skills and familiarity with data wrangling, cleaning, and transformation .

*Preferred (Secondary)Skills:
- Experience with *Docker  and Kubernetes  for scalable model deployment.
- Knowledge of data engineering pipelines , batch/stream processing, and ETL tools.
- Familiarity with data visualization tools  like Tableau, Power BI, or Plotly for reporting and dashboards.
- Understanding of CI/CD pipelines  and DevOps practices .
- Exposure to Agile methodologies  and working in cross-functional teams.

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