Senior Machine Learning Engineer
Skills
About the role
This is a senior machine learning engineering role at Syncron, based in Bengaluru, bridging data science and ML engineering. It suits a hands-on ML practitioner who can build models and also take them into production, not just work in notebooks. Syncron builds a SaaS aftermarket platform (CSX) covering supply chain, pricing and service lifecycle management.
What you’ll do
- Translate business problems into ML-ready problem statements.
- Perform exploratory data analysis, feature discovery and target definition.
- Build and validate ML models across classification, regression, forecasting, clustering, anomaly detection and recommendation.
- Evaluate models using statistical, ML and business metrics, and explain drivers using techniques like SHAP.
- Build reusable ML pipelines for processing, training, deployment, monitoring and retraining.
- Convert data science prototypes into production-ready, config-driven workflows.
- Build CI/CD pipelines for ML code, configs and model artifacts.
- Implement experiment tracking, model registry, versioning and lineage.
- Support controlled model promotion across dev, staging and production.
What they’re looking for
- 4-8 years of experience in data science, ML engineering or applied ML.
- Strong hands-on Python and SQL skills.
- Strong understanding of ML algorithms, evaluation, feature engineering and validation.
- Experience converting notebooks into production-quality code.
- Experience with orchestration tools such as Airflow, Kubeflow or Mage.
- Experience with model lifecycle tools such as MLflow, SageMaker, Azure ML or Vertex AI.
- Experience with Docker, Git and CI/CD automation such as GitHub Actions.
- Experience with a cloud platform such as AWS, Azure or GCP.
- Familiarity with production ML monitoring concepts such as drift and data quality validation.
- Familiarity with NLP fundamentals such as tokenization and semantic embeddings.
Nice to have
- Experience supporting GenAI use cases involving LLMs, embeddings and vector databases.
- Experience with document processing, chunking, retrieval and prompt engineering workflows.
- Experience with managed LLM platforms, open-source models or LLMOps tools.
Questions about this role
How much does it pay?
Glassdoor estimates a base pay range of ₹7L to ₹11L per year for this role.
How many years of experience do I need?
The posting asks for 4-8 years of experience.
Is this role remote?
The posting does not clearly state remote status; it lists the role in Bengaluru with hashtags referencing both remote and hybrid.
How this role compares
One of 8 open Senior Machine Learning Engineer roles we are tracking today.
Posted 5 days ago, with 3 of the others posted since and 4 still open from before.
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