Machine Learning Engineer

Hiring : Machine Learning Engineers (ML 2 / ML 3) – Bangalore

Are you passionate about building customer-facing AI solutions that make a real impact?

Do you thrive in fast-paced, product-driven environments where ownership and accountability are valued?

We are looking for ML Engineers (Level 2 / 3) to join our growing AI / ML team in Bangalore. This is an exciting opportunity to work on Generative AI, personalization, and intelligent search systems that will directly shape the experience of millions of users.

Key Responsibilities

As a part of our ML team, you will :

Design and implement scalable ML solutions that directly align with product and business goals.

Develop, test, and optimize ML models for production environments with high availability and low latency.

Build Generative AI features such as conversational interfaces, intelligent assistants, and personalized experiences.

Partner with product managers, data scientists, and engineers to integrate ML into customer-facing applications .

Monitor and evaluate model performance post-deployment; iterate to improve accuracy, latency, and UX.

Drive best practices in experimentation, reproducibility, and deployment workflows .

Participate actively in code reviews, design discussions, and technical deep dives .

Work closely with stakeholders to translate business needs into ML-driven solutions .

️ Required Skills & Experience

4–8 years of applied machine learning experience with proven deployment track record.

Hands-on experience with Generative AI, NLP, conversational AI, or personalization systems .

Proficiency in Python and frameworks like PyTorch, TensorFlow, Hugging Face .

Experience deploying ML models on cloud platforms (AWS / GCP / Azure) .

Strong knowledge of feature engineering, ML pipelines, and MLOps practices .

Ability to work cross-functionally and communicate complex ML concepts clearly .

Demonstrated impact through production-level ML solutions .

⭐ Preferred Qualifications

Master’s degree in Computer Science, Machine Learning, or related field .

Experience in fintech / financial services domains is a plus.

Exposure to recommendation engines, ranking, or personalization techniques .

Contributions to open-source ML frameworks or active participation in ML / AI communities.