Dear Candidates,
We are looking for candidates interested in the role of Machine Learning Engineer.
Following is the Job Description for your reference.
Job Title: Machine Learning Engineer
Location: Bangalore/Gurugram/Chennai
Experience: 810 Years
Domain: Payments / FinTech (preferred)
About the Role
We are looking for a seasoned Machine Learning Engineer with 810 years of experience to join our team. The ideal candidate will have a strong foundation in machine learning, deep learning, data science, and model deployment at scale. Experience in the payments domain, especially working with credit card and UPI data, is highly desirable.
Key Responsibilities
- Collect, preprocess, and analyze credit card and UPI payment data to extract features and insights.
- Design and develop ML models for use cases such as fraud detection, transaction risk scoring, and customer analytics.
- Build, fine-tune, and deploy OSS LLMs (Open-Source Large Language Models) like GPT, T5, BERT, Falcon, and Vision Transformers for tasks such as:
- Text summarization
- Synthetic data generation
- NLP applications in payments
- Implement, monitor, and maintain ML/GenAI models in production environments using MLOps tools (MLflow, Kubeflow, AWS SageMaker, Comet OPIK).
- Evaluate model performance using industry-standard metrics (Precision, Recall, F1-score, AUC-ROC).
- Collaborate with cross-functional teams to align ML solutions with business objectives.
- Monitor model drift, performance, and ensure scalability and reliability of production systems.
Required Skills
- 810 years of experience in ML engineering, data science, or related roles.
- Proficient in Python (must), and working knowledge of R and Java.
- Solid understanding of machine learning, statistics, and data science principles.
- Experience with data processing tools such as SQL, Spark, and Hadoop.
- Strong hands-on experience with frameworks:
- TensorFlow, PyTorch, Scikit-learn
- Hugging Face Transformers, LangChain, LlamaIndex
- Familiarity with foundational models: BERT, GPT, T5, ViT, etc.
- Exposure to GenAI and OSS LLM fine-tuning & deployment.
- Hands-on experience with Docker, Kubernetes, and production deployment of ML models.
- Hands-on & strong in Python programming (note: Candidate is expected to complete a coding exercise during the interview)
- Building Agentic solutions & exposing the same Agents as Services
- Building chat-bots based on RAG framework
- Experience in optimizing prompts
- Excellent communication and presentation skills.
Preferred Qualifications
- Background in the payments or financial domain (UPI, credit card data).
- Experience working with fraud detection, customer segmentation, or risk scoring models.
- Experience with model monitoring, feedback loops, and model retraining pipelines.
Those who are interested kindly apply on the following link,
https://forms.office.com/e/q4MmmKbArC
