About CodeGraphers

CodeGraphers builds intelligent products in the fields of AI, Web3, and Automation.
We work on real systems that combine classic machine learning, generative AI, and large-scale automation.
Our environment is fast-paced and idea-driven. Every engineer is expected to think critically, experiment deeply, and contribute to meaningful innovations.

We are looking for an in-house Machine Learning Engineer who has strong foundations in mathematics, statistics, and machine learning theory.
If you only connect APIs or rely on ready models without understanding their inner workings, this role is not for you.

Role Overview
You will join our Core AI Engineering team in Lahore.
Your focus will be to design, train, and deploy classic ML and generative AI models.
You will work on real data, perform experiments, validate results, and build production-grade systems.

Key Responsibilities
• Explore, clean, and analyze datasets for insight and model preparation
• Train, evaluate, and tune supervised and unsupervised models such as regression, classification, clustering, and ensemble methods
• Build and experiment with deep learning and generative AI models including LLMs, embeddings, and diffusion networks
• Apply strong mathematical reasoning and statistical validation to ensure model robustness
• Collaborate with engineering and product teams to integrate trained models into production systems
• Document experiments, maintain reproducibility, and communicate results clearly
• Optimize models for performance, scalability, and inference cost

Required Skills
• Solid knowledge of mathematics and statistics including linear algebra, calculus, probability, and optimization
• Strong programming in Python with experience in NumPy, Pandas, Scikit-Learn, Matplotlib, and Seaborn
• Experience with PyTorch or TensorFlow for deep learning
• Clear understanding of classic algorithms such as logistic regression, SVM, K-Means, PCA, and XGBoost
• Exposure to LLMs and GenAI using Hugging Face, LangChain, or LlamaIndex
• Familiarity with vector databases like Pinecone, FAISS, or Weaviate
• Understanding of experiment tracking and versioning using tools such as MLflow or DVC
• Ability to read research papers, test new ideas, and adapt them into working code

Nice to Have
• Experience with diffusion, vision, or speech models
• Knowledge of FastAPI, Docker, or Kubernetes
• Background in MLOps and model deployment
• Participation in Kaggle competitions, research work, or open-source ML projects

What We Offer
• Full-time in-house position at our Lahore office
• Work on production-level AI projects, not just prototypes
• Competitive compensation and a growth-oriented environment
• Collaboration with senior AI engineers and product teams
• Learning culture focused on experimentation and continuous improvement