We are looking to add a Junior Machine Learning Engineer Intern with experience in designing machine learning models to our founding team.
About Us
Joulea is a startup tackling climate change by building a software platform that reduces energy costs and consumption in commercial buildings, helping lower global carbon emissions. Today, energy use in commercial buildings within the United States represents 33% of their operating budgets, coupled with all building types this represents 40% of the entire United States’ carbon emissions. We use the aerospace industry’s product lifecycle management principles in order to create a novel approach to apply them to commercial real estate. Joulea implements holistic, integrated optimization methods that redefine energy efficiency and reduce operating costs within commercial buildings. We are an ATDC portfolio company backed by wemarathon with offices at ATDC in Midtown Atlanta.
Job Description
We are seeking a talented and passionate Junior Machine Learning Engineer Intern to join our growing team of innovators. As a Junior Machine Learning Engineer, you will collaborate with senior members of the team to design, develop, and implement machine learning models and algorithms. Your work will have a direct impact on enhancing our products and services by leveraging the power of artificial intelligence and data-driven insights. This is an exciting opportunity for motivated individuals looking to kickstart their career in the cutting-ed field of machine learning and contribute to groundbreaking projects.
Responsibilities
Assist in the design, development, and deployment of machine learning models and algorithms.
Work closely with senior engineers to preprocess, clean, and analyze large datasets to derive meaningful patterns and features.
Implement and experiment with various machine learning techniques, including supervised and unsupervised learning, reinforcement learning, and deep learning.
Collaborate with cross-functional teams to integrate machine learning solutions into our applications and systems.
Participate in the evaluation and optimization of model performance and scalability.
Keep abreast of the latest advancements in machine learning and AI research to contribute to continuous improvement.
Contribute to the documentation of machine learning processes, experiments, and results.
Support the team in troubleshooting and debugging machine learning models during development and deployment.
Requirements
Students working towards their bachelor's degree in computer science, Data Science, Electrical Engineering, or a related field.
Solid understanding of machine learning fundamentals, algorithms, and statistical concepts.
Proficiency in programming languages such as Python or R, and familiarity with data manipulation and analysis libraries (e.g., NumPy, Pandas).
Exposure to machine learning frameworks and libraries (e.g., scikit-learn, TensorFlow, PyTorch) is a plus.
Basic knowledge of data visualization techniques to communicate insights effectively.
Strong problem-solving skills and attention to detail.
Excellent communication skills and the ability to work collaboratively in a team environment.
Minimum experience
No prior professional experience required, though relevant internships or personal projects are beneficial.
Preferred experience
Hands-on experience with machine learning projects, either through coursework or personal projects.
Familiarity with neural networks and deep learning architectures.
Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for machine learning deployment.
Knowledge of natural language processing (NLP) or computer vision techniques.
Understanding of version control systems, such as Git.
Enthusiasm for continuous learning and a strong desire to grow as a machine learning professional.
Benefits
Per Diem
