Ahmedabad, Gujarat, India
Information Technology
Full-Time
MagellanicCloud
Overview
Job Description
Key Responsibilities :
Key Responsibilities :
- Design, build, and deploy machine learning models to solve real-world business problems.
- Perform data preprocessing, cleansing, transformation, and feature engineering on both structured and unstructured data.
- Train, evaluate, and optimize ML models for performance, scalability, and accuracy.
- Integrate ML models into production systems and ensure their continuous performance using MLOps practices.
- Leverage cloud platforms, especially Google Cloud Platform (GCP), for scalable model training and deployment (e.g., Vertex AI, BigQuery, Dataflow).
- Develop REST APIs for ML models using Docker and orchestrate deployments via Kubernetes.
- Collaborate closely with data engineers, product managers, and software developers to translate business requirements into technical solutions.
- Monitor and maintain models in production, ensuring stability, performance, and regular updates.
- Maintain best practices in version control, documentation, and continuous integration using Git, GitHub, or GitLab.
- 5+ years of hands-on experience in building, training, and deploying machine learning models in a production-oriented environment.
- Proficiency in Python (preferred) or R, along with common machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Solid knowledge of machine learning algorithms including regression, classification, clustering, and deep learning.
- Experience with Natural Language Processing (NLP), Computer Vision, or other advanced AI techniques is a
- Strong expertise in SQL and NoSQL databases, with a deep understanding of data warehousing concepts.
- Demonstrated ability in data blending and transformation, working with structured and unstructured data formats.
- Hands-on experience with GCP tools like Vertex AI, BigQuery, and Dataflow is highly desirable.
- Familiarity with MLOps practices, including model versioning, monitoring, and CI/CD pipelines.
- Working knowledge of Docker and Kubernetes for containerized deployments.
- Proficiency with Git-based version control systems for collaborative development workflows.
- GCP certifications or equivalent cloud training.
- Experience working in agile and fast-paced environments.
- Prior experience deploying AI solutions in industries like finance, healthcare, retail, or supply chain.
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