Staff Machine Learning Engineer
AngiSalary not specified
- Full Time
- Expert & Leadership (9+ years)
Not SpecifiedCompensation
Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Artificial Intelligence, Data ScienceIndustries
Requirements
Candidates should possess proven experience with recommendation engines, including cold-start scenarios, classical machine learning expertise, and data ETL experience utilizing tools such as Airflow or DBT. Familiarity with modeling both structured and unstructured data from NoSQL databases like MongoDB is required, along with experience in production-grade NLP using Large Language Models (LLMs). Demonstrated professional experience in high-performing settings, ideally with a combination of big tech and startup experience or experience in the workforce development industry, is also expected.
Responsibilities
The Staff Machine Learning Scientist will own problem spaces from 0 to 1, including defining product requirements with stakeholders and maintaining high-quality recommender science. They will also uphold best practices in data science and machine learning, dedicating 70% of their time to improving the recommendation engine, 20% to building out data ontologies, and 10% to acting as a strategic partner to the VP of Data and Product, re-thinking the recommender architecture and optimizing data usage.
Skills
Recommendation engines
Cold-start scenarios
Classical machine learning
Data ETL
Airflow
DBT
NoSQL databases
MongoDB
Structured data modeling
Unstructured data modeling
FutureFit AI
AI-powered career guidance and navigation tool
About FutureFit AI
FutureFit AI offers an AI-powered tool that helps individuals navigate their career paths by assessing their skills, exploring job opportunities, and outlining steps to achieve their goals. This tool is particularly useful in the changing job market, catering to those looking to transition careers and organizations supporting employee development. By analyzing labor market data, FutureFit AI provides personalized career guidance through a subscription model, partnering with educational institutions and workforce agencies. The company's goal is to transform career transitions with data-driven insights that empower users to make informed decisions.
New York City, New YorkHeadquarters
2018Year Founded
$5.2MTotal Funding
EARLY_VCCompany Stage
Data & Analytics, AI & Machine Learning, EducationIndustries
11-50Employees