Job description
At Goldbelly, we believe food brings people together. We connect people with their greatest culinary desires within and beyond local communities. We empower food makers of all sizes and deliver their passion to food-lovers around the country.
As a Machine Learning Engineer, you will enhance how millions of customers connect with both novel and nostalgic food experiences on our platform. By partnering with business leaders and leveraging state-of-the-art machine learning and engineering resources, you will play a key role in transforming our user experience.
Responsibilities
- Collaborate closely with senior engineers, data scientists / analysts, and product managers to improve our search, recommendations, and personalization algorithms.
- Design, develop, and maintain robust, scalable machine learning systems to ensure the seamless delivery of personalized food experiences.
- Develop algorithms utilizing state-of-the-art machine learning techniques in search, retrieval, recommendation, and natural language processing (NLP).
- Improve our core machine learning infrastructure, focusing on product and user embeddings to boost efficiency and effectiveness across all ML-driven services.
- Apply software engineering rigor and best practices to machine learning, including CI/CD, pipeline orchestration, etc.
- Define and promote best practices and workflows throughout the machine learning life cycle.
Qualifications
- 1+ years of experience in ML modeling and working on large scale production systems.
- Proficient in Python and SQL.
- Experienced with data processing libraries such as Pandas and NumPy.
- Skilled in machine learning libraries and frameworks including Scikit-learn, PyTorch, TensorFlow, or Keras.
- Proficient in using version control systems like Git and collaborative development platforms such as GitHub or GitLab.
- Strong background in developing personalized search and recommendation systems, preferably in an e-commerce context.
- Familiarity with development in containerization and cloud computing environments (we use AWS, but experience in other platform is useful as well).
Compensation information: $160,000 - $220,000 base salary range (dependent on experience level and interview performance) + equity (incentive stock options, vested over 4 years) + benefits.
