Machine Learning Engineer

Job Title- Machine Learning Engineer

Location:

Mohali / Chandigarh |

Full-time | Work from Office

We’re looking for a

Machine Learning Engineer

to work at the intersection of

data, AI, and customer platforms , enabling smarter decision-making and impactful customer experiences.

What You Bring ✅ Bachelor’s degree in

Computer Science / Data Science / Engineering

(Master’s preferred) ✅

5+ years

of hands-on experience in

Machine Learning Engineering ✅ Strong foundation in

ML algorithms, model building, and deployment ✅ Expertise in

Python

and ML libraries such as

scikit-learn, TensorFlow, PyTorch, XGBoost ✅ Experience working with

large-scale data platforms

(Treasure Data CDP preferred) ✅ Hands-on experience with

customer segmentation, recommendation systems, predictive modeling, and real-time decisioning ✅ Exposure to

cloud-based ML frameworks & deployment

(MLflow, Kubeflow, SageMaker, etc.) ✅ Excellent

SQL skills

(Presto, MongoDB, MySQL, BigQuery) ✅ Experience with

A/B testing

and marketing experimentation frameworks ✅ Knowledge of

NLP, deep learning, or advanced recommendation systems

for customer behavior analysis ✅ Ability to translate

business problems into ML-driven solutions ✅ Experience in

customer-facing environments

(CRM, marketing automation platforms)

Your Impact 1️⃣

ML Model Development & Implementation • Design, develop, and deploy

machine learning models

within the CDP to enhance customer insights, segmentation, and personalization • Build models for

churn prediction, customer behavior analysis, recommendations, and CLV modeling • Implement

supervised & unsupervised learning

techniques including classification, regression, clustering, and deep learning 2️⃣

Model Evaluation, Monitoring & Optimization • Continuously evaluate and improve ML model performance for accuracy and business impact • Set up

monitoring systems

to track production models and detect

data drift or performance issues • Optimize models for

scalability, efficiency, and cost

within the CDP ecosystem 3️⃣

Scalability & Performance Optimization • Ensure ML workflows scale efficiently to handle

large volumes of customer data

in real-time or near real-time • Optimize

data pipelines and ML models

for low latency, high throughput, and fast insights 4️⃣

Research & Continuous Learning • Stay updated with the latest trends in

Machine Learning, AI, and CDP technologies • Evaluate new algorithms, tools, and techniques to enhance the overall ML and CDP capabilities