NLP Engineer

NorthBay Solutions; Lahore; On-site; PKR 2,000,000 - 3,500,000; Full time

Job summary

NorthBay Solutions in Lahore, Pakistan is seeking an experienced NLP Engineer to lead the design, development, and deployment of production-grade NLP and Generative AI solutions. You will own end-to-end AI initiatives, drive technical architecture, and mentor engineers across NLP/Generative AI initiatives.

You will collaborate with ML engineers, software teams, and product stakeholders to translate business needs into scalable ML systems.

Qualifications

• 5+ years of professional NLP/ML or Generative AI experience.
• Strong Python programming and hands-on experience with PyTorch, TensorFlow, Hugging Face, or equivalent frameworks.
• Deep understanding of NLP, transformers, LLMs, embeddings, RAG, fine-tuning, and model evaluation.
• Proven experience taking AI/ML solutions from experimentation to production.
• Strong software engineering and system-design skills, including APIs, data pipelines, and scalable architectures.

Responsibilities

• Lead the design and development of scalable NLP and LLM-powered solutions.
• Architect and optimize RAG pipelines, embeddings, vector search, and LLM applications.
• Fine-tune, evaluate, and optimize transformer-based models for production use.
• Build robust data, training, inference, and model-evaluation pipelines.
• Drive improvements in model quality, latency, scalability, reliability, and cost.
• Establish best practices for experimentation, evaluation, deployment, and monitoring of AI systems.
• Translate complex business requirements into effective AI/ML solutions.
• Collaborate closely with ML engineers, software engineers, product teams, and stakeholders.
• Mentor engineers and provide technical leadership across NLP/Generative AI initiatives.
• Stay current with emerging research, models, frameworks, and best practices in NLP and Generative AI.

Skills

NLP

Python

PyTorch

TensorFlow

Hugging Face

LLMs

Transformers

RAG

Fine-tuning

Model evaluation

APIs

Data pipelines

System design

Job description

Role Overview

We are looking for anNLP Engineerto lead the design, development, and deployment of production-grade NLP and Generative AI solutions. You will own complex AI initiatives end-to-end, drive technical architecture, and help shape our NLP/LLM engineering practices.

Key Responsibilities

• Lead the design and development of scalable NLP and LLM-powered solutions
• Architect and optimize RAG pipelines, embeddings, vector search, and LLM applications
• Fine-tune, evaluate, and optimize transformer-based models and LLMs for production use
• Build robust data, training, inference, and model-evaluation pipelines
• Drive improvements in model quality, latency, scalability, reliability, and cost
• Establish best practices for experimentation, evaluation, deployment, and monitoring of AI systems
• Translate complex business requirements into effective AI/ML solutions
• Collaborate closely with ML engineers, software engineers, product teams, and stakeholders
• Mentor engineers and provide technical leadership across NLP/Generative AI initiatives
• Stay current with emerging research, models, frameworks, and best practices in NLP and Generative AI

Requirements

• 5+ years of professional experience in NLP, Machine Learning, or Generative AI
• Strong Python programming and hands-on experience with PyTorch, TensorFlow, Hugging Face, or equivalent frameworks
• Deep understanding of NLP, transformers, LLMs, embeddings, RAG, fine-tuning, and model evaluation
• Proven experience taking AI/ML solutions from experimentation to production
• Strong software engineering and system-design skills, including APIs, data pipelines, and scalable architectures
• Strong analytical and problem-solving skills with the ability to independently drive technical initiatives

Preferred

• Experience with PEFT/LoRA, quantization, inference optimization, or distributed model training
• Experience with vector databases, MLOps, cloud platforms, and AI evaluation/observability frameworks
• Experience building AI agents, multimodal systems, or other advanced Generative AI applications
• Contributions to open-source projects, research, publications, or applied AI/ML innovation