Machine Learning Engineer
ThinkDigits4–6 yrsHyderabadOn-siteDirect career pageEst. 10–22 LPA
Posted on 24 Sept
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Job description
Structured overview of role & requirements
About This Role
- Design, implement, and deploy machine learning models with robust pre-processing and post-processing logics to ensure data quality, model accuracy, and business usability.
- Collaborate with data scientists and data engineers to transition ML prototypes into scalable, production-ready systems ensuring data integrity and availability.
- Deploy, monitor, and maintain ML models in cloud and containerized environments, managing model performance, drift, and MLOps practices including versioning and continuous integration.
Minimum Requirements
- 4–6 years of hands-on experience as an ML Engineer, Data Scientist, or Applied AI Engineer.
- Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.
- Proficiency in Python with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
- Experience deploying ML models in cloud (AWS, GCP, Azure) and containerized environments (Docker, Kubernetes).
Ideal Candidate Profile
- Experienced in designing custom pre-processing and post-processing logic for ML workflows to improve prediction quality and business alignment.
- Skilled in collaborating across data science and engineering teams to build scalable and maintainable ML systems.
- Comfortable working with cloud-based ML platforms and MLOps best practices including model versioning, reproducibility, and continuous integration.