ML Engineer

Rubiscape; Pune District; On-site; INR 1,600,000 - 3,000,000; Full time

Job summary

Rubiscape is seeking an ML Engineer to build and operationalise machine learning models powering 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 to deliver production-grade predictive intelligence at scale, aiming to shorten the data-to-use case cycle.

Responsibilities include creating ML models, feature pipelines, and model registry integration, with emphasis on versioning,

Qualifications

• 3+ years hands-on ML engineering experience in product or enterprise software.
• Strong proficiency in Python with scikit-learn, XGBoost/LightGBM, and at least one deep learning framework (PyTorch preferred).
• Experience with experiment tracking (MLflow or equivalent) and model versioning.
• Understanding of feature engineering for tabular data, time-series, and event-based datasets.

Responsibilities

• Design, train, and evaluate ML models across BFSI, manufacturing, and healthcare verticals.
• Build feature pipelines integrated with the Rubiscape Feature Store.
• Collaborate with data engineers on RubiFlow to define feature contracts and data quality upstream of training.
• Integrate models into RubiStudio’s registry and automate versioning and lineage.
• Profile performance, diagnose drift/bias, and monitor with RubiSight dashboards.
• Write clean, typed Python code for production readiness.
• Participate in Innovation Lab collaborations to prototype novel modelling approaches.

Skills

Python

scikit-learn

PyTorch

XGBoost/LightGBM

Experiment tracking

REST API deployment

Education

Bachelor’s or Master’s degree in Computer Science/Statistics/Mathematics

Tools

MLflow

Rubiscape Feature Store

AutoML frameworks (Auto-sklearn, FLAML)

Job description

As an ML Engineer at Rubiscape, you willbuild and operationalise machine learning models that power RubiStudio — ourAutoML and MLOps studio trusted by Fortune 500 enterprises. You will work atthe intersection of data engineering, feature design, and model training,turning raw enterprise data into production-grade predictive intelligence atscale. This role is central to Rubiscape’s mission of compressing the time fromraw 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, andPyTorch.
• Build andmaintain feature engineering pipelines integrated with Rubiscape’s internalFeature Store, ensuring consistency between training and inferenceenvironments.
• Collaboratewith data engineers on RubiFlow to define feature contracts and manage dataquality upstream of model training.
• Integratetrained models into RubiStudio’s model registry and automate versioning,lineage capture, and metadata tagging via MLflow.
• Profilemodel performance across data slices; diagnose drift, bias, and degradationusing monitoring hooks connected to RubiSight dashboards.
• Writeclean, type-annotated Python code that meets production standards and can bereviewed, tested, and deployed by the platform engineering team.
• Participatein quarterly Innovation Lab collaborations with Rubiscape’s 10Industry-Academia COEs to prototype novel modelling approaches.

Nice to Have

• Hands-onexperience with AutoML frameworks (Auto-sklearn, FLAML, or similar) and theirintegration into governed ML platforms.
• Exposureto regulated-sector modelling requirements such as model explainability underRBI or IRDAI guidelines.
• Familiaritywith Rubiscape or comparable unified analytics platforms (Databricks, Dataiku,or SageMaker Studio).
• Publishedresearch or patents in applied machine learning.

About Rubiscape

Rubiscape is India’s leading DecisionIntelligence Platform, unifying data engineering, BI, machine learning, andagentic AI in a single governed platform. Built in Pune and trusted by Fortune500 enterprises across BFSI, manufacturing, healthcare, and government. 8international innovation patents. 10 Industry-Academia Labs & COEs. From BIto AI — One Platform. Every Decision.

Requirements

• 3+ yearsof hands-on ML engineering experience in a product or enterprise softwareenvironment.
• Strongproficiency in Python with scikit-learn, XGBoost/LightGBM, and at least onedeep learning framework (PyTorch preferred).
• Practicalexperience with experiment tracking (MLflow or equivalent) and a structuredapproach to model versioning.
• Solidunderstanding of feature engineering for tabular data, time-series, andevent-based datasets common in enterprise analytics.
• Experiencedeploying models as REST APIs or batch inference jobs in cloud or on-premisesenvironments (AWS, Azure, or GCP).
• Bachelor’sor Master’s degree in Computer Science, Statistics, Mathematics, or a relatedquantitative discipline.