About the Role

As an ML Engineer at Rubiscape, you will
build and operationalise machine learning models that power RubiStudio — our
AutoML and MLOps studio trusted by Fortune 500 enterprises. You will work at
the intersection of data engineering, feature design, and model training,
turning raw enterprise data into production-grade predictive intelligence at
scale. This role is central to Rubiscape’s mission of compressing the time from
raw data to first production use case to under 90 days.

Key Responsibilities

· Design,
train, and evaluate supervised and unsupervised ML models across BFSI,
manufacturing, and healthcare verticals using Python, scikit-learn, and
PyTorch.

· Build and
maintain feature engineering pipelines integrated with Rubiscape’s internal
Feature Store, ensuring consistency between training and inference
environments.

· Collaborate
with data engineers on RubiFlow to define feature contracts and manage data
quality upstream of model training.

· Integrate
trained models into RubiStudio’s model registry and automate versioning,
lineage capture,



and metadata tagging via MLflow.

· Profile
model performance across data slices; diagnose drift, bias, and degradation
using monitoring hooks connected to RubiSight dashboards.

· Write
clean, type-annotated Python code that meets production standards and can be
reviewed, tested, and deployed by the platform engineering team.

· Participate
in quarterly Innovation Lab collaborations with Rubiscape’s 10
Industry-Academia COEs to prototype novel modelling approaches.

Nice to Have

· Hands-on
experience with AutoML frameworks (Auto-sklearn, FLAML, or similar) and their
integration into governed ML platforms.

· Exposure
to regulated-sector modelling requirements such as model explainability under
RBI or IRDAI guidelines.

· Familiarity
with Rubiscape or comparable unified analytics platforms (Databricks, Dataiku,
or SageMaker Studio).

· Published
research or patents in applied machine learning.

About Ru

📌 ML Engineer (Pune)
🏢 Rubiscape
📍 Pune