About the position
This is a full time position that consists in leading our MLOps and will require both machine learning and software engineering skills. The core work will be connected to the deployment of machine learning models. This involves tuning existing models to increase speed and performance and developing software infrastructure to make them scalable.
- Code development to put machine learning models into production, including backend interfaces.
- Define and implement ML workflows to process data, feed it to the models, and collect outputs.
- Tune models to ensure fast inference and reliable performance.
You are a highly enthusiastic, results-driven and experienced data engineer. You thrive in dynamic environments and you are able to take initiative and enjoy challenges. You are an experienced leader that enjoys building diverse data solutions.You constantly aim for excellence and you are motivated to scale up a marketing optimization platform to reach market leadership.
- Bachelor's degree in Data Science, Computer Science, Software Engineering, Mathematics, similar technical field of study or equivalent practical experience.
- +6 years of practical experience.
- Experience leading Data Scientist teams and projects.
- Software development and data science experience in Python and SQL.
- Experience with Machine Learning development, preferably in the application of Computer Vision models.
- Experience with cloud based infrastructure setups, preferably the Amazon Web Services stack.
- Experience with DevOps tools: Docker, Git, Continuous Integration (CI), Continuous Deployment (CD)
- Excellent written and verbal communication skills.
- Excellent time management skills, with the ability to prioritize and multi-task, and work under shifting deadlines in a fast-paced environment.
- MS or PhD degree in Engineering, Data Science, Computer Science, or other technical related field; or equivalent practical experience.
- Familiarity with compartmentalization and ML deployment.
- Experience using machine learning tools in production.
- Experience working in a growth-stage startup.
- Experience working with Agile and Scrum methodologies
What we offer
- Competitive salary.
- Work from home with flexible work hours.
- Unlimited paid time off.
- Publication opportunities.
- Science-driven culture.
- Contacts within the Harvard and MIT ecosystem.
- Yearly bonus for personal learning.