Job Description

Job Title: AI/ML Engineer - LLM Deployment & Advanced RAG Systems

Department:

Artificial Intelligence & Machine Learning

About the Role

We are seeking a highly skilled

AI/ML Engineer

with expertise in

Large Language Model (LLM) deployment, fine-tuning, and advanced RAG (Retrieval-Augmented Generation) agent implementation

. The ideal candidate will have a strong background in

AI/ML, deep learning, and NLP

, with hands-on experience in deploying models in

air-gapped systems

and optimizing them for enterprise use cases.

You will be responsible for

designing, fine-tuning, and deploying LLMs

tailored to customer data, implementing

advanced RAG pipelines

, and ensuring seamless integration with existing systems. Your expertise in

OCR, data processing, and MLOps

will be critical in building scalable, efficient, and secure AI solutions.

Key ResponsibilitiesLLM Deployment & Fine-Tuning

Deploy

Large Language Models (LLMs)

in

air-gapped environments

, ensuring compliance with security and operational constraints. Fine-tune and train models using

customer-specific data

, optimizing for performance, accuracy, and efficiency. Implement

model versioning, monitoring, and continuous improvement

using tools like

MLflow, and MLOps pipelines

.

Advanced RAG Implementation

Design and implement

Retrieval-Augmented Generation (RAG) systems

at an advanced level, including:

Document pipelining

for efficient data ingestion and processing.

Removal of obsolete or redundant data

to maintain relevance and accuracy.

Optimization of retrieval and generation workflows

for low-latency, high-accuracy responses.

OCR & Data Extraction

Develop

OCR engines

to extract structured and unstructured information from documents, images, and other data sources. Implement

preprocessing pipelines

to clean, normalize, and enrich extracted data for downstream AI applications.

System Integration & Optimization

Integrate AI models with

enterprise systems

(e.g.,

MongoDB, Oracle DB, PostgreSQL, MySQL

) and

cloud platforms

(e.g.,

AWS, Docker, Kafka

). Optimize

speech recognition, noise reduction, and text-to-speech

pipelines for real-time applications. Collaborate with

DevOps and backend teams

to deploy models using

Flask, Spring Boot, Jenkins, and CI/CD pipelines

.

Collaboration & Innovation

Work closely with

data scientists, engineers, and product teams

to align AI solutions with business objectives. Stay updated with

emerging trends

in AI, NLP, and LLM technologies, and propose innovative solutions.

Required Skills & QualificationsTechnical Expertise

Programming:

Python, Java, Flask, Django

AI/ML Frameworks:

PyTorch, Scikit-Learn, TensorFlow, OpenAI APIs

LLM & NLP:

Fine-tuning, prompt engineering, RAG, OCR, speech recognition

Databases:

PostgreSQL, MySQL

MLOps:

MLflow, model deployment, monitoring

Web & Microservices:

Flask, Gunicorn, Apache Tomcat,

Soft Skills

Strong problem-solving and analytical skills. Ability to work in

agile, cross-functional teams

. Excellent communication and documentation skills.

Education & Experience

Bachelor's/Master's/PhD

in Computer Science, AI, Machine Learning, or a related field.

5+ years

of experience in

AI/ML, NLP, or LLM deployment

. Proven experience in

fine-tuning LLMs, RAG systems, and OCR implementations

.

Preferred Qualifications

Experience with

air-gapped system deployments

and

secure AI workflows

. Familiarity with

noise reduction techniques

in speech processing. Knowledge of

visualization tools

and

data storytelling

.
Job Type: Contractual / Temporary
Contract length: 7 months

Pay: ?1,500,000.00 - ?1,800,000.00 per year

Benefits:

Commuter assistance Food provided Paid sick time
Work Location: In person