Our team is seeking a motivated and detail-oriented Entry-Level Machine Learning Engineer to join our growing team. As a key contributor, you will help build, test, and deploy machine learning models that solve real-world problems and enhance our data-driven decision-making. This is a great opportunity for someone eager to apply their academic knowledge in a practical, fast-paced environment.
Major Responsibilities
- Assist in designing, training, and validating machine learning models using structured and unstructured data
- Collaborate with data scientists, analysts, and software engineers to develop production-ready ML solutions
- Preprocess and clean large datasets to prepare for modeling
- Conduct experiments, evaluate model performance, and tune hyperparameters
- Write reusable, well-documented code in Python (or similar languages)
- Contribute to model deployment pipelines and MLOps infrastructure
- Stay current with the latest research, tools, and trends in machine learning and AI
- Bachelor’s degree in computer science, Data Science, Engineering, Mathematics, Statistics, or a related field
- 1 to 2 years of foundational knowledge of machine learning concepts and algorithms (e.g., regression, classification, clustering)
- Proficiency in Python and ML libraries such as Scikit-learn, Pandas, NumPy, TensorFlow, or PyTorch
- Familiarity with data manipulation, feature engineering, and exploratory data analysis
- Understanding of model evaluation metrics and techniques
- Good communication and teamwork skills
- Internship or project experience involving machine learning or data science
- Familiarity with version control (e.g., Git), Jupyter notebooks, and cloud platforms (e.g., AWS, GCP, or Azure)
- Exposure to LLM and Agentic AI
- Exposure to SQL and basic database concepts
- Enthusiastic about learning and growing in the field of AI/ML
