Azure ML engineer
Machine Learning, MLOps, Python, Data Science, Databricks, Azure
Description
We are looking for a seasoned Azure Machine Learning (ML) Engineer to join our growing team. In this role, you will play a critical role in bridging the gap between data science and production by designing, developing, and implementing the infrastructure needed to operationalize machine learning models at scale.
Who We Are
GSPANN has been in business for over a decade, with over 2000 employees worldwide, and servicing some of the largest retail, high technology, and manufacturing clients in North America. We provide an environment that enables career growth while still interacting with company leadership.
Visit Why GSPANN for more information.
Location: Hyderabad / Gurugram / Pune
Role Type: Full Time
Published On: 25 April 2024
Experience: 5+ years
Description
We are looking for a seasoned Azure Machine Learning (ML) Engineer to join our growing team. In this role, you will play a critical role in bridging the gap between data science and production by designing, developing, and implementing the infrastructure needed to operationalize machine learning models at scale.
Role and Responsibilities
- Design and implement MLOps pipelines for training, deployment, and monitoring of machine learning models.
- Build and maintain a scalable and reliable ML infrastructure using tools like Docker, Kubernetes, and cloud platforms like Azure and Databricks.
- Collaborate with data scientists and software engineers to ensure seamless integration of models into production environments.
- Develop and implement CI/CD pipelines for automated model training, testing, and deployment.
- Monitor model performance and implement alerting systems for drift and degradation.
- Champion best practices in MLOps and stay up-to-date with the latest advancements in the field.
- Identify opportunities to improve the efficiency, maintainability, and scalability of our ML systems.
Skills and Experience
- A degree in Computer Science, Engineering, or a related field (or equivalent experience).
- 5+ years of experience in software development or machine learning engineering.
- Expertise in building and deploying machine learning models in production.
- Strong understanding of MLOps concepts and practices.
- Mandatory experience in cloud platforms (AWS, GCP, Azure).
- Must know containerization technologies (Docker/Kubernetes) and CI/CD tools (GitLab CI, Jenkins, etc.).
- Expertise in ML model management tools (MLflow, Kubeflow, etc.).
- Proficiency in Python and familiarity with ML libraries (TensorFlow, PyTorch, etc.)
- Excellent communication, collaboration, and problem-solving skills.
- It is an opportunity to work on cutting-edge ML projects in a collaborative and supportive work environment.
- Be a part of a team that is transforming the future!
