AI Engineer

Role Overview

As an AI Engineer at Nineleaps, you will work on building, testing, and improving machine learning solutions that solve real-world business problems. You’ll contribute across the AI lifecycle—from data preparation and model experimentation to evaluation, documentation, and collaboration with cross-functional teams. This role is ideal for professionals with a strong foundation in machine learning and Python who are excited to explore modern AI concepts, including deep learning, LLMs, and generative AI.

Key Responsibilities

• Implement, test, and optimize foundational machine learning models using frameworks such as TensorFlow, PyTorch, or scikit-learn
• Assist with data collection, preprocessing, and exploratory data analysis (EDA) to prepare high-quality datasets for model training and evaluation
• Conduct literature reviews and stay up to date with the latest developments in AI, machine learning, and generative AI
• Apply new ideas and emerging techniques in prototypes and proof-of-concept solutions
• Document technical processes, experiments, and results thoroughly to support reproducibility and knowledge sharing
• Participate actively in code reviews, brainstorming sessions, and team discussions to foster collaboration and innovation
• Present findings, analyses, and model outcomes clearly to both technical and non-technical stakeholders
• Support experimentation and evaluation of models to improve accuracy, efficiency, and business relevance

What We’re Looking For

• Strong proficiency in Python and hands-on experience with core libraries such as NumPy and pandas
• Foundational experience with at least one major deep learning framework, such as TensorFlow or PyTorch, along with scikit-learn for classical machine learning tasks
• Strong grasp of data structures and algorithms (DSA) and core computer science fundamentals
• Familiarity with version control tools such as Git
• Solid understanding of core AI/ML concepts, including supervised learning, unsupervised learning, classification, regression, and model evaluation metrics
• Understanding of deep learning concepts and architectures, especially Transformer models, Large Language Models (LLMs), and generative AI
• Familiarity with data preprocessing, feature selection, and basic data visualization techniques
• Basic conceptual understanding of RAG (Retrieval-Augmented Generation) architectures and prompt engineering techniques
• Strong analytical thinking, attention to detail, and a proactive problem-solving mindset
• Excellent written and verbal communication skills
• Prior internships, academic projects, coursework, or research experience in AI/ML is a strong plus

About Nineleaps

Nineleaps is a technology company specializing in digital engineering, data, and AI. We work with businesses across industries to solve complex challenges through modern technology and create an environment where people can learn fast, take ownership, and build meaningful careers while doing it.