Senior Machine Learning Engineer
Syncron (company site, opens in a new tab)4–8 yrsBengaluruHybridDirect career pageEst. 20–40 LPA
Posted on 6 Sept
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Job description
Structured overview of role & requirements
About This Role
- Translate business problems into ML problem statements and develop, validate, and improve ML models for various use cases including classification, regression, forecasting, and anomaly detection.
- Build, maintain, and productize reusable ML pipelines covering data processing, feature engineering, model training, deployment, monitoring, and lifecycle management including versioning and rollout processes.
- Collaborate with Engineering teams to integrate models into production workflows, ensuring production readiness, monitoring, and business impact measurement.
Minimum Requirements
- 4–8 years of experience in Data Science, ML Engineering, Applied ML, or related roles.
- Strong hands-on skills in Python, SQL, and production-quality code development beyond notebooks.
- Experience with orchestration tools (Airflow, Kubeflow, Mage) and model lifecycle tools (MLflow, SageMaker, Azure ML, Vertex AI).
- Experience with cloud platforms (AWS, Azure, or GCP), CI/CD automation tools (e.g. GitHub Actions), Docker, Git, and production ML monitoring concepts.
Ideal Candidate Profile
- Experienced ML practitioner able to bridge data science experimentation and engineering for production ML workflows.
- Comfortable with model evaluation, interpretability techniques (feature importance, SHAP), and analyzing model performance across segments and business outcomes.
- Familiar with NLP fundamentals, GenAI/LLM use cases, and scalable multi-tenant/config-driven pipelines.