Senior AIML Engineer - Bangalore

Impelsys; Bengaluru; On-site; INR 4,000,000 - 7,500,000; Full time

Job summary

Impelsys in Bengaluru is seeking a Senior AIML Engineer to design, develop, and deploy scalable ML models and AI systems, with a strong focus on Generative AI, LLMs, and RAG architectures.

You will build and maintain end‑to‑end ML pipelines, optimize models for performance and cost, and integrate embedding models with vector databases. The role includes mentoring juniors and collaborating with stakeholders to deliver enterprise AI solutions.

Qualifications

• Bachelor's or Master's degree in CS/AI/ML or related field.
• 5+ years of ML engineering/AI development experience.
• Strong Python programming and experience with large datasets.

Responsibilities

• Design, develop, and deploy ML models and AI systems including LLMs and RAG architectures.
• Build and maintain scalable ML pipelines for data ingestion, preprocessing, model training, validation, and deployment.
• Optimize and fine‑tune models for performance, scalability, and cost efficiency.
• Develop embedding models and vector database integrations.
• Implement and maintain MLOps pipelines, CI/CD workflows, and model monitoring.
• Integrate ML models into production apps via APIs and microservices.
• Lead experimentation, model evaluation, and A/B testing initiatives.
• Collaborate with cross‑functional teams to translate business problems into AI solutions.
• Ensure robustness, reliability, and security of ML systems in production.
• Mentor junior engineers and promote AI/ML best practices within the org.

Skills

Python

LLMs

NLP

MLOps

Cloud (AWS/Azure)

CI/CD

Mentoring

Education

Bachelor's or Master's in CS/AI/ML

Tools

Pandas

NumPy

TensorFlow

PyTorch

Scikit-learn

Hugging Face Transformers

spaCy

NLTK

Docker

Kubernetes

REST APIs

Spark

MongoDB

Vector databases

Job description

As a Senior AIML Engineer, you will be responsible for designing, developing, and deploying scalable machine learning models and AI systems in production environments. You will work closely with junior ML engineer and other product stakeholders to build advanced AI solutions, with a strong focus on Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and enterprise-grade ML systems.

Key Responsibilities

• Design, develop, and deploy machine learning models and advanced AI systems, including LLMs and RAG architectures
• Build and maintain scalable ML pipelines for data ingestion, preprocessing, model training, validation, and deployment
• Optimize and fine-tune models for performance, scalability, and cost efficiency
• Develop and integrate embedding models and vector database solutions
• Implement and maintain MLOps pipelines, CI/CD workflows, and model monitoring systems
• Integrate ML models into production applications using APIs and microservices architecture
• Lead experimentation, model evaluation, and A/B testing initiatives
• Work closely with cross-functional teams to translate business problems into AI-driven solutions
• Ensure robustness, reliability, and security of ML systems in production
• Mentor junior engineers and contribute to AI/ML best practices within the organization

Required Qualifications

• Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or related field
• 5+ years of experience in Machine Learning engineering or AI development
• Strong programming expertise in Python
• Extensive experience with:
• Data manipulation and analysis libraries: pandas, numpy
• Machine learning frameworks: scikit-learn, TensorFlow, PyTorch
• NLP libraries: Hugging Face Transformers, spaCy, NLTK
• Strong proficiency in working with large datasets
• Experience with cloud platforms (AWS, Azure) and ML services
• Solid understanding of machine learning algorithms, deep learning, and statistical modeling
• Hands-on experience with Docker, Kubernetes, and CI/CD pipelines
• Experience working with REST APIs and microservices architecture

Preferred Qualifications

• Experience with Large Language Models (LLMs), prompt engineering, and fine-tuning
• Hands-on experience with Retrieval-Augmented Generation (RAG) systems
• Experience with vector databases (e.g., Pinecone, Azure Index)
• Practical experience implementing MLOps best practices
• Experience with distributed computing frameworks (e.g., Spark)
• Familiarity with NoSQL databases (e.g., MongoDB)
• Experience leading AI initiatives or mentoring junior engineers
• Contributions to AI research, publications, or open-source projects

Skills and Attributes

• Strong analytical and problem-solving abilities
• Excellent communication and stakeholder management skills
• Ability to lead technical discussions and mentor team members
• Strong ownership mindset and accountability
• Passion for staying updated with advancements in AI, NLP, and Generative AI
• Ability to explain complex AI concepts to non-technical stakeholders