Machine Learning Engineer

Job description

This job is going to build MVP (minimum viable product). The Data scientist will be responsible for developing causal inferences methods to estimate the effect of treatment and implementing machine learning algorithms, pattern recognition. They will also work on data analysis, statistical modeling, and algorithm optimization. The Machine Learning Engineer will collaborate with a team of engineers and data scientists to improve recommender systems. 

As a Machine Learning Engineer, you will work with Data Scientist in causal inference to build recommendation system, where an end-to-end AI system processes raw sensor input to make direct decisions, we are building end-to-end AI based recommendation algorithms. These algorithms aim to discover the most compelling content on platform — including posts, promoted content, creators, and videos — based directly on users' activity on the platform. 

As a key driver of this effort, you will test state-of-the-art methodologies to significantly enhance users' experiences on the platform. 

Your responsibilities will include: 

• Designing and architecting recommendation algorithms across various product surfaces (Timelines, Video, Search, Notifications) 
• Collaborating with cross-functional teams to integrate machine learning models into our platform Iterating and improving the algorithm by gathering user feedback in real time through experimentation 
• Ensuring scalability and efficiency of machine learning systems Mentoring junior engineers and contributing to the team's growth 
• Staying updated on Machine Learning and Deep Learning industry trends 

Your skills and experience

• Strong background in Computer Science and Statistics 
• Experience in developing and implementing machine learning algorithms 
• Knowledge of pattern recognition and Causal inference Proficiency in programming languages such as Python or R Familiarity with algorithms and data structures 
• Strong analytical and problem-solving skills 
• Excellent communication and collaboration abilities Master's or Ph.D. in Computer Science, Engineering, or related field 
• Experience with recommender systems is a plus

Why you'll love working here

• Competitive salary and equity options.
• Opportunity to grow with a passionate and innovative team.
• Health benefits, learning stipend, casual dress code.