Machine Learning Software Engineer Job Description Template
Our company is looking for a Machine Learning Software Engineer to join our team.
Responsibilities:
- Analyze experimental and observational data, communicate findings, and facilitate launch decisions;
- Participate in code reviews to ensure code quality and distribute knowledge;
- Write production-level codes to train your ML models into working pipelines and services to serve production online traffic;
- Build a platform for data science/ML at scale;
- Forecast sale timelines and sale price for Opendoor homes;
- Model key features that inform the overall risk to the business in any given cohort of homes;
- Projecting and forecasting resales;
- Build GPU infrastructure that allows Opendoor to embrace deep learning;
- Create and maintain production systems that provide oversight on the uptime and stability of our models;
- Create and maintain Spark and lambda architecture to create data pipelines that generate features;
- Extract features from raw data such as text and images using NLP & CV;
- Design, implement and operate large-scale distributed systems;
- Develop container orchestration systems within a Kubernetes environment;
- Design and develop data science solutions relating to streaming data as well as machine learning solutions;
- Collaboration with various teams during the design, implementation and deployment phases.
Requirements:
- B.S., M.S., or PhD. in Computer Science or equivalent;
- Industry experience building and productionizing innovative end-to-end Machine Learning systems;
- 2+ years of successfully applying machine learning to product/business problems;
- Prior experience building machine learning systems in production;
- Strong grasp of fundamental machine learning techniques;
- Python/R/Javascript (Node.js) experience a plus;
- Experience with machine learning management frameworks (e.g.: Airflow, Argo, Kubeflow, and/or ML Flow);
- Production experience within a variety of storage systems such as (but not limited to) object storage, NoSQL or relational databases;
- Production experience deploying and managing applications in a public cloud provider environment (e.g.: AWS, Google Compute Engine or Azure);
- Experience with path planning;
- Bachelor’s degree;
- 2+ years experience with statistical methods, modern ML algorithms, and software engineering best practices;
- Strong mathematical skills;
- Experience developing reusable Machine Learning tools and pipelines;
- Experience with autonomous robots.