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Machine Learning Engineer
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We are looking for a Machine Learning Engineer to build and deploy ML models supporting the Linkfields platform — for example recommendations, demand forecasting or anomaly detection — and to productionize them at scale on AWS.
About the Role
We are looking for a Machine Learning Engineer to build and deploy ML models supporting the Linkfields platform — for example recommendations, demand forecasting or anomaly detection — and to productionize them at scale on AWS.
Key Responsibilities
- Design, train and evaluate ML models for relevant use cases.
- Build production ML pipelines covering feature engineering, training, deployment and monitoring.
- Deploy models via AWS SageMaker, Lambda or containerized services.
- Implement MLOps practices — CI/CD for models, monitoring and retraining.
- Collaborate with Data Engineers on data pipelines and feature stores.
- Document model performance, limitations and assumptions.
Must-Have Skills & Experience
- 5+ years of experience building and deploying ML models.
- Strong Python skills and experience with ML frameworks (scikit-learn, PyTorch or TensorFlow).
- Experience productionizing ML models at scale.
- Hands-on experience with the AWS ML stack (SageMaker or equivalent).
- Experience with data pipelines and feature engineering.
Good to Have
- MLOps tooling experience (MLflow, Kubeflow).
- NLP or LLM fine-tuning experience.
- Telecom or retail use-case experience.
Role Details
- Experience - 5-8 Years
- Location - Hyderabad, India
- Work Mode - Hybrid
- Employment - Contract-to-Hire
- Domain - AI/ML Platform Engineering, AWS
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