Software Engineer (AI/ML) (Secunderabad) | C685

Software Engineer (AI/ML) (Secunderabad) | C685

Job Description

Job description

Role Overview

We are seeking aMachine Learning Engineerto join a high-impact team withinExperian Consumer Services (ECS), focused on building scalable, reusable AI capabilities that power personalized financial experiences for millions of users. This role is ideal for someone who thrives at the intersection ofmachine learning, software engineering, and product thinking.

You will work closely withproduct managers,data scientists,platform engineers, andUX teamsto understand consumer needs, define ML-driven solutions, and deliver production-grade AI services such asLLM-as-a-Service,enterprise knowledge orchestration,predictive intelligence APIs, andpersonalized decisioning engines.





Success in this role requires not only strong technical skills but also the ability toevaluate trade-offs,select the right models and tools, andalign ML solutions with business goals. You'll be expected to own the full ML lifecycle-from problem framing and experimentation to deployment, monitoring, and continuous improvement.

Key Responsibilities1. Business-Aligned ML Engineering

- Collaborate with product and analytics teams to identify high-impact personalization and automation opportunities.
- Translate business problems into ML use cases, selecting appropriate modeling techniques (e.g., classification, ranking, recommendation, summarization).
- Evaluate trade-offs between accuracy, interpretability, latency, and scalability to guide model and architecture choices.

2. Model Development & Optimization

- Design and implement ML models using Python and frameworks likescikit-learn,XGBoost,TensorFlow, andPyTorch.
- Apply advanced techniques such asfeature selection,regularization,hyperparameter tuning(Grid Search, Bayesian Optimization), andensemble learning.
- Leveragetransfer learning,fine-tuning,



andprompt engineeringto extend the capabilities of pre-trained LLMs.

3. LLM Integration & Extension

- Build and operationalize LLM-based services usingAmazon Bedrock,LangChain, andvector databases(e.g., FAISS, Pinecone).
- Develop use cases such as intelligent summarization, contextual recommendations, and conversational personalization usingretrieval-augmented generation (RAG)pipelines.

4. Productionization & Deployment

- Package and deploy models usingAmazon SageMaker,SageMaker Inference Pipelines,AWS Lambda, andKubernetes.
- Build containerized ML services and expose them via secure, versionedRESTful APIsusingFastAPIorFlask.
- Integrate models into real-time and batch workflows, ensuring reliability and scalability.

5. Performance Monitoring & Governance





- Implement robust evaluation pipelines using metrics likeAUC-ROC,F1-score,Precision/Recall,Lift, andRMSE, aligned with product KPIs.
- Monitor model drift, data quality, and prediction stability using tools likeEvidently AI,SageMaker Model Monitor, and custom telemetry.
- Ensure model explainability, auditability, and compliance usingMLflow,SageMaker Model Registry,SHAP, andLIME.

6. MLOps & Automation

- Automate end-to-end ML workflows usingSageMaker Pipelines,Step Functions, and CI/CD tools likeGitHub Actions,CodePipeline, andTerraform.
- Collaborate with platform engineers to ensure reproducibility, scalability, and adherence to security and privacy standards.

7. Core ML Algorithms & Techniques

- Supervised Learning: Logistic Regression, Decision Trees, Random Forests, Gradient Boosting (XGBoost, LightGBM)
- Unsupervised Learning: K-Means, DBSCAN, PCA, t-SNE
- Deep Learning: CNNs, RNNs,



Transformers (BERT, GPT), Autoencoders
- Recommendation Systems: Matrix Factorization, Neural Collaborative Filtering, Hybrid Models
- NLP: Text Classification, Named Entity Recognition, Embeddings, RAG
- Time Series Forecasting: ARIMA, Prophet, LSTM
- Evaluation & Tuning: Cross-validation, Hyperparameter Optimization, A/B Testing

Qualifications

Qualifications

- Generative AI
- Applied Machine Learning & Deep Learning
- Software Engineering Best Practices (SOLID, Design Patterns, CI/CD)
- Advanced Python Development
- Cloud-Native ML Engineering (AWS SageMaker, Bedrock, etc.)
- MLOps & Model Lifecycle Management

Additional Information

Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters DEI, work/life balance, development,



authenticity, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning World's Best Workplaces 2024 (Fortune Top 25), Great Place To Work in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age.



If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

Experian Careers - Creating a better tomorrow together

📌 Software Engineer (AI/ML)
🏢 Experian
📍 Secunderabad

The original job offer can be found in Kit Job:
kitjob.in/job/177772196