Machine Learning Engineer

Job Description – Machine Learning Engineer (Benow Entity)

We at Pine Labs are looking for those who share our core belief - "Every Day is Game day". We bring our best selves to work each day to realize our mission of enriching the world through the power of digital commerce and financial services.

Role Purpose

We are seeking a highly skilled Lead Machine Learning Engineer with a track record of driving business impact through classical ML models in the fintech domain. Adept at building, deploying, and scaling machine learning solutions that optimize customer targeting strategies across FOS, digital, and telecalling channels. Proven ability to work with cross-functional teams to leverage data-driven insights and enhance merchant engagement.

Responsibilities we entrust you with

•Designed and deployed ML models that increased the conversion rate of merchants by X% through intelligent lead prioritization.

•Built a machine learning pipeline to predict merchant churn, leading to a Y% increase in merchant retention via proactive interventions.

•Deployed ML models to assign high-value leads to Field Officers, increasing the sales team's efficiency by A%.

•Led multi-channel marketing experiments to measure the effectiveness of digital and telecalling campaigns, improving Return on Ad Spend (ROAS).

•Implemented an anomaly detection system that flagged suspicious transactions in real-time, reducing fraud losses.

Core Technical Skills

•Machine Learning & Statistical Modeling: Logistic Regression, Random Forest, Gradient Boosting (XGBoost, LightGBM), SVM, K-Means Clustering, Time Series Forecasting.

•Data Engineering & Processing: SQL, Apache Spark, Feature Engineering, Data Pipelines.

•Model Deployment & MLOps: AWS SageMaker, FastAPI, Flask, Docker, Kubernetes, Airflow, MLflow.

•Customer Segmentation & Personalization: Clustering models for segmentation, Uplift Modeling for campaign optimization.

•Business Intelligence & Experimentation: A/B Testing, Causal Inference, BI Tools (AWS QuickSight, Tableau).

•Programming Languages: Python (Pandas, NumPy, Scikit-learn), SQL.

•Big Data & Real-time Processing: Kafka, Apache Flink, Elasticsearch for real-time lead scoring.

What Matters In This Role

Relevant work experience

•Work on impactful ML models that directly drive revenue & optimize merchant engagement.

•Access to large-scale transaction data to build cutting-edge predictive models.

•Collaborate with a cross-functional fintech team (Product, Sales, Engineering, BI).

•Opportunity to lead ML innovation in the fintech space with real-world impact.

•Own the end-to-end lifecycle of ML models, from problem definition to production deployment.

•Partner with Sales, Marketing, and Product teams to drive merchant acquisition & engagement.

•Ensure models are scalable, monitored, and optimized for real-time use.

•Work with Data Engineers to build robust, automated data pipelines.

•Develop lead prioritization and recommendation systems for sales teams.

•Implement A/B testing, monitoring dashboards, and retraining strategies.

•Act as a technical mentor, guiding junior ML engineers and data scientists.

Ideal Candidate Profile

•Experience: 5+ years in ML & Data Science, preferably in Fintech, Payments, or Lending.

•Domain Expertise: Strong understanding of merchant acquisition, customer segmentation, and financial risk modeling.

•Business & Product Mindset: Can translate business problems into ML solutions that drive measurable revenue impact.

•Hands-on with ML Deployment: Not just an algorithm expert, but someone who gets models into production at scale.

Experience yrs

Location - Mumbai

What we Value in Our people

• You take the shot: You Decide Fast and You Deliver Right
• You are the CEO of what you do: you show ownership and make things happen
• You own tomorrow: by building solutions for the merchants and doing the right thing
• You sign your work like an artist: You seek to learn and take pride in the work you do