Location: Madhapur, Hyderabad (In-Person) Schedule: Monday – Friday (5 Days In-Office)
Job Summary
We are seeking an experienced Machine Learning Engineer (4–6 years) to design, develop, and deploy robust ML solutions. The ideal candidate will have expertise in building models as well as implementing pre-processing and post-processing logics to ensure data quality, model accuracy, and business usability of predictions.
Key Responsibilities
- Design, implement, and deploy machine learning models for production use cases.
- Develop and optimize pre-processing logics for data cleaning, feature engineering, and transformation.
- Implement post-processing logics to refine raw predictions into actionable insights aligned with business rules.
- Collaborate with data scientists to transition prototypes into scalable production systems.
- Work with data engineers to ensure data integrity, consistency, and availability for ML workflows.
- Deploy and monitor ML models in cloud and containerized environments (AWS, GCP, Azure, Docker, Kubernetes).
- Monitor and evaluate model performance, drift, and reliability, triggering retraining as needed.
- Contribute to MLOps practices including model versioning, reproducibility, and continuous integration.
- Document ML systems, pre/post-processing logic, and best practices for maintainability.
Qualifications
- Bachelor’s or Master’s in Computer Science, Data Science, AI/ML, or related field.
- 4–6 years of hands-on experience as an ML Engineer, Data Scientist, or Applied AI Engineer.
- Strong programming skills in Python with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
- Proven experience in designing custom pre-processing and post-processing logics for ML models.
- Knowledge of databases (SQL/NoSQL) and data manipulation at scale.
- Experience with model deployment via APIs (FastAPI, Flask, gRPC).
- Familiarity with cloud-based ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML).
- Strong understanding of software engineering best practices (Git, unit testing, modular code).
Nice-to-Have
- Domain experience in NLP, computer vision, or predictive analytics.
- Exposure to real-time inference systems and low-latency model serving.
Knowledge of CI/CD for ML models (MLflow, Kubeflow, Airflow).