AI - ML Engineer

Company Overview

At Gaditek, our talent is not just exceptional - it's world-class! Our unstoppable team of 800+ employees is the best and the brightest, driving innovation across 7 Global SaaS Brands in 6 hottest industries, including Cyber Security, Digital Media, Managed Cloud, Affiliate Marketing, E-Commerce, Web.3.0, and Venture Building as a Service.

Our team is made up of dreamers, doers, and all-around rockstars who are committed to making a difference. As a result, we’re among the best companies to work for, with a plethora of benefits and an amazing culture.

Overview Of The Role

We are looking for a highly skilled AI/ML Engineer to develop and implement Large Language Models (LLMs) and Knowledge Graphs for intelligent data processing, retrieval, and reasoning. The ideal candidate will have expertise in machine learning, natural language processing (NLP), and graph-based AI to drive innovative AI-powered solutions.

What You Will Be Expected To Perform

• Develop and fine-tune LLMs – Work on training, optimizing, and deploying large language models for various applications.
• Design and implement knowledge graphs – Build and maintain scalable knowledge graph systems to enhance AI-driven insights.
• Data pipeline management – Develop efficient data ingestion, preprocessing, and feature engineering pipelines for ML models.
• Integration with AI applications – Implement LLMs and knowledge graphs in real-world AI applications, ensuring seamless performance.
• Model evaluation and optimization – Fine-tune AI/ML models for efficiency, accuracy, and scalability.
• Collaborate with cross-functional teams – Work with data scientists, engineers, and domain experts to align AI solutions with business goals.
• Stay updated on AI advancements – Research and experiment with state-of-the-art LLM and knowledge graph technologies.
  
  

Qualifications And Requirements

• Education – Bachelor’s or Master’s in Computer Science, AI, Data Science, or related fields. Ph.D. is a plus.
• ML & NLP Expertise – Strong experience with deep learning, transformers, and NLP models (e.g., BERT, GPT, Llama, T5, etc.).
• Knowledge Graphs – Hands-on experience with graph databases (Neo4j, RDF, OWL, GraphQL) and reasoning techniques.
• Programming Skills – Proficiency in Python, TensorFlow/PyTorch, and libraries like Hugging Face, LangChain, or Ray.
• Data Engineering – Experience with data pipelines, ETL, and big data technologies (Spark, Kafka, Airflow, etc.).
• Cloud & Deployment – Familiarity with AWS, GCP, Azure, Kubernetes, and model deployment strategies.
• Problem-Solving & Research – Strong analytical thinking, experimentation, and ability to push AI capabilities further.
• Collaboration & Communication – Ability to work in cross-functional teams and present AI-driven insights effectively.
  
  

You Should Be

• A Problem-Solver – You thrive on solving complex AI/ML challenges and optimizing models for real-world applications.
• Passionate About AI – You stay up to date with the latest advancements in LLMs, NLP, and Knowledge Graphs.
• A Strong Coder – You write clean, efficient, and scalable code in Python, TensorFlow/PyTorch, and related frameworks.
• Data-Driven – You understand the importance of structured and unstructured data and know how to leverage it for AI solutions.
• Collaborative – You work well with cross-functional teams and can effectively communicate AI concepts to stakeholders.
• Curious & Innovative – You experiment with new AI techniques and push the boundaries of LLMs and Knowledge Graph applications.
• Detail-Oriented & Analytical – You focus on model accuracy, performance, and efficiency while keeping scalability in mind.
  
  

Dimensions And Supplementary Information

• Scope of Work – You will be working on designing, developing, and optimizing LLMs and Knowledge Graphs for various AI-driven applications.
• Technical Depth – The role requires deep expertise in machine learning, NLP, graph-based AI, and large-scale data processing.
• Industry Application – The AI/ML solutions you develop may be applied in finance, healthcare, e-commerce, cybersecurity, or other industries.
• Collaboration – You will work closely with data scientists, software engineers, product managers, and domain experts.
• Innovation & Research – A part of your role will involve exploring state-of-the-art AI methodologies and implementing them effectively.
• Scalability & Performance – Your solutions must be scalable, optimized for high-performance, low-latency AI processing.
• Compliance & Ethics – You may work with AI governance, bias mitigation, and responsible AI practices to ensure ethical AI development.