Machine Learning Engineer
HiredBuddy
Boston, MA0–2 yrs5h agovia LinkedIn
About the Role
Hiredbuddy is seeking a motivated Machine Learning Engineer to join our remote team. This is an entry-level position, ideal for candidates with strong programming, analytical, and problem-solving skills and a passion for artificial intelligence. You will build, train, and evaluate machine learning models to solve real-world problems and support data-driven applications.
Key Responsibilities
- Prepare datasets
- Develop machine learning models
- Evaluate model performance
- Integrate ML solutions into applications
- Work with structured and unstructured data
- Identify patterns
- Experiment with different algorithms to improve model accuracy and performance
- Collect and clean data
- Perform exploratory data analysis
- Prepare features
- Train machine learning models
- Assist with model testing, performance evaluation, documentation, and optimization
- Collaborate with senior engineers and data scientists
Requirements & Tech Stack
- Python programming
- Machine learning libraries such as Scikit-learn, Pandas, and NumPy
- Basic understanding of machine learning concepts and algorithms
- Experience with 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
- Familiarity with Git or other version control systems
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
Opportunities for growth may include working with deep learning, natural language processing, computer vision, and model deployment, as well as tools like TensorFlow, PyTorch, Docker, and cloud services.