Junior AI/ML Engineer
United Consulting Hub
Type: Fulltime
Location: Remote
Job Summary
We are seeking a motivated and analytical Entry-Level AI/ML Engineer to support the development, testing, and implementation of artificial intelligence and machine learning solutions. This role is ideal for recent graduates in Computer Science, Information Technology, Data Science, Artificial Intelligence, or related fields who are eager to build their careers in AI and machine learning technologies.
Key Responsibilities
- Assist in developing, training, and testing machine learning models for business applications
- Collect, clean, preprocess, and organize structured and unstructured datasets
- Support data analysis and exploratory data analysis to identify patterns and trends
- Implement basic machine learning algorithms for classification, regression, and clustering tasks
- Assist in evaluating model performance using appropriate metrics and validation techniques
- Develop and maintain Python scripts for data processing and model development
- Work with libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch
- Support feature engineering, data transformation, and model optimization activities
- Collaborate with data scientists, software engineers, and cross-functional teams
- Assist in documenting model development processes, experiments, and technical findings
- Participate in debugging, testing, and improving AI/ML applications
- Follow best practices for data quality, model reliability, security, and responsible AI development
Requirements & Tech Stack
- Basic knowledge of Python programming and object-oriented programming concepts
- Understanding of fundamental machine learning algorithms and statistical concepts
- Familiarity with data manipulation, preprocessing, and visualization techniques
- Basic knowledge of SQL and database concepts
- Understanding of model training, testing, evaluation, and performance metrics
- Strong analytical thinking, problem-solving, and communication skills
Preferred Skills
- Academic projects, internships, or practical experience in AI, machine learning, or data science
- Familiarity with TensorFlow, PyTorch, or Scikit-learn
- Basic understanding of cloud platforms such as AWS, Azure, or Google Cloud
- Exposure to Git, APIs, Jupyter Notebook, or model deployment concepts