AI/Machine Learning Engineer
Job Purpose
Role Overview Design, develop, and deploy AI and machine learning solutions that enhance Sleekabyte’s products and internal operations. The AI/Machine Learning Engineer will work closely with software engineers, product teams, and stakeholders to build, optimize, and maintain intelligent applications while driving innovation through modern AI technologies and best practices.
Key Responsibilities
Key Responsibilities
- Design, develop, train, and deploy machine learning models for real-world business applications.
- Build, optimize, and maintain AI-powered solutions that improve product functionality and operational efficiency.
- Collect, clean, preprocess, and analyze data to improve model accuracy and performance.
- Research emerging AI, machine learning, and large language model (LLM) technologies and recommend practical business applications.
- Develop and integrate AI-powered features using APIs, LLMs, and other AI services into web and mobile applications.
- Monitor, evaluate, and optimize model performance to ensure scalability, reliability, and accuracy.
- Collaborate with software engineers, product designers, and cross-functional teams throughout the product development lifecycle.
- Document technical processes, model performance, experiments, and implementation guidelines.
- Participate in sprint planning, code reviews, technical discussions, and solution architecture.
- Ensure AI solutions follow industry best practices for security, ethics, and performance.
- Stay up to date with advancements in artificial intelligence, machine learning, and data science.
Qualifications
Requirements
- Bachelor’s degree in computer science, Artificial Intelligence, Data Science, Software Engineering, Mathematics, or a related field.
- 2–5 years’ experience in AI, machine learning, computer vision, or related roles.
- Strong understanding of machine learning algorithms, model development, and deployment.
- Proficiency in Python and common AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar.
- Experience with data preprocessing, feature engineering, and model evaluation techniques.
- Familiarity with REST APIs, version control systems (Git), and cloud AI services is an advantage.
- Knowledge of Large Language Models (LLMs), prompt engineering, or generative AI tools is an added advantage.
- Strong analytical, problem-solving, and critical thinking skills.
- Excellent communication and collaboration skills.