Machine Learning Engineer
HiredBuddy
San Francisco, CA0–2 yrs1h agovia LinkedIn
About the Role
Hiredbuddy is seeking a motivated, detail-oriented, and enthusiastic Machine Learning Engineer to join our remote team. This is an entry-level position perfect for someone eager to launch their career in machine learning and artificial intelligence. You will build, train, and evaluate machine learning models to solve real-world problems and support data-driven applications, working with structured and unstructured data, identifying patterns, and experimenting with algorithms to improve model accuracy and performance.
Key Responsibilities
- Prepare datasets
- Develop machine learning models
- Evaluate model performance
- Help integrate ML solutions into applications
- Collect and clean data
- Perform exploratory data analysis
- Prepare features
- Train machine learning models
- Experiment with supervised and unsupervised learning techniques
- Assist with model testing, performance evaluation, documentation, and optimization
- Collaborate with senior engineers and data scientists
Requirements & Tech Stack
- Python proficiency
- Experience with libraries such as Scikit-learn, Pandas, and NumPy
- Familiarity with Git or other version control systems
- Basic understanding of machine learning concepts and algorithms
- Understanding of data preprocessing, feature engineering, and model evaluation
- Familiarity with supervised and unsupervised learning techniques
- Basic knowledge of statistics and probability
- Good understanding of algorithms and data structures
Qualifications
- Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, Statistics, Engineering, or a related field
- 0-2 years of experience in machine learning, data science, or a related role (internships and academic projects count)
- Strong analytical and problem-solving skills
- Good communication skills, both written and verbal
- Ability to work independently and collaboratively in a remote environment
- Eagerness to learn new machine learning tools and technologies
- Passion for artificial intelligence
Opportunities for growth may include experience with deep learning, natural language processing, computer vision, model deployment, TensorFlow, PyTorch, Docker, cloud services, and ML deployment workflows.