Senior Staff Engineer (Machine Learning)

Delhi - India

Monthly Salary: Not Disclosed

Posted on: 3 days ago

Vacancies: 1 Vacancy

Department:

Engineering

Job Summary

REQUIREMENTS:

Strong expertise in Python and ML frameworks such as TensorFlow PyTorch Scikit-learn and Hugging Face.
Solid understanding of supervised/unsupervised learning data preprocessing and feature engineering.
Experience with model evaluation metrics (accuracy precision recall F1-score).
Familiarity with banking AI use cases such as fraud detection personalization credit scoring and churn prediction.
Hands-on experience with cloud ML platforms (Azure ML AWS SageMaker Google Vertex AI).
Knowledge of MLOps tools like MLflow and Kubeflow for CI/CD model lifecycle management and monitoring.
Ability to develop explainable AI models using SHAP LIME and ensure regulatory compliance.
Strong skills in NLP and LLM engineering including fine-tuning prompt engineering and RAG-based architectures.
Knowledge of vector databases (FAISS Pinecone) orchestration tools (LangChain LlamaIndex) and conversational AI frameworks.
Strong backend integration capabilities using REST APIs Docker/Kubernetes and microservices.
Preferred certifications: TensorFlow Developer AWS ML Specialty Google Professional ML Engineer.

RESPONSIBILITIES:

Understanding the clients business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.
Mapping decisions with requirements and be able to translate the same to developers.
Identifying different solutions and being able to narrow down the best option that meets the clients requirements.
Defining guidelines and benchmarks for NFR considerations during project implementation
Writing and reviewing design document explaining overall architecture framework and high-level design of the application for the developers
Reviewing architecture and design on various aspects like extensibility scalability security design patterns user experience NFRs etc. and ensure that all relevant best practices are followed.
Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies patterns and frameworks to materialize it
Understanding and relating technology integration scenarios and applying these learnings in projects
Resolving issues that are raised during code/review through exhaustive systematic analysis of the root cause and being able to justify the decision taken.
Carrying out POCs to make sure that suggested design/technologies meet the requirements.

Qualifications :

Bachelors or masters degree in computer science Information Technology or a related field.

Remote Work :

Employment Type :

Full-time

REQUIREMENTS: Strong expertise in Python and ML frameworks such as TensorFlow PyTorch Scikit-learn and Hugging Face.Solid understanding of supervised/unsupervised learning data preprocessing and feature engineering.Experience with model evaluation metrics (accuracy precision recall F1-score).Familia...

REQUIREMENTS:

Strong expertise in Python and ML frameworks such as TensorFlow PyTorch Scikit-learn and Hugging Face.
Solid understanding of supervised/unsupervised learning data preprocessing and feature engineering.
Experience with model evaluation metrics (accuracy precision recall F1-score).
Familiarity with banking AI use cases such as fraud detection personalization credit scoring and churn prediction.
Hands-on experience with cloud ML platforms (Azure ML AWS SageMaker Google Vertex AI).
Knowledge of MLOps tools like MLflow and Kubeflow for CI/CD model lifecycle management and monitoring.
Ability to develop explainable AI models using SHAP LIME and ensure regulatory compliance.
Strong skills in NLP and LLM engineering including fine-tuning prompt engineering and RAG-based architectures.
Knowledge of vector databases (FAISS Pinecone) orchestration tools (LangChain LlamaIndex) and conversational AI frameworks.
Strong backend integration capabilities using REST APIs Docker/Kubernetes and microservices.
Preferred certifications: TensorFlow Developer AWS ML Specialty Google Professional ML Engineer.

RESPONSIBILITIES:

Understanding the clients business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.
Mapping decisions with requirements and be able to translate the same to developers.
Identifying different solutions and being able to narrow down the best option that meets the clients requirements.
Defining guidelines and benchmarks for NFR considerations during project implementation
Writing and reviewing design document explaining overall architecture framework and high-level design of the application for the developers
Reviewing architecture and design on various aspects like extensibility scalability security design patterns user experience NFRs etc. and ensure that all relevant best practices are followed.
Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies patterns and frameworks to materialize it
Understanding and relating technology integration scenarios and applying these learnings in projects
Resolving issues that are raised during code/review through exhaustive systematic analysis of the root cause and being able to justify the decision taken.
Carrying out POCs to make sure that suggested design/technologies meet the requirements.

Qualifications :

Bachelors or masters degree in computer science Information Technology or a related field.

Remote Work :

Employment Type :

Full-time

Key Skills

Computer Science
Docker
Kubernetes
Python
VMware
C/C++
Go
System Architecture
gRPC
OS Kernels
Perl
Distributed Systems

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About Company

Nagarro

Nagarro helps future-proof your business through a forward-thinking, fluidic, and CARING mindset. We excel at digital engineering and help our clients become human-centric, digital-first organizations, augmenting their ability to be responsive, efficient, intimate, creative, and susta ... View more

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