Machine Learning Engineer
🇺🇸 United States › California › Millbrae (Posted Jun 3 2018)
About the company
At FunnelEnvy we optimize B2B revenue through intelligent customer experiences. Our FunnelEnvy PRO (Predictive Revenue Optimization) platform uses data to automate 1:1 experiences and deliver revenue faster, better and easier than A/B testing or rules-based personalization. deliver experiences across channels including the website, chat and ads. We're helping some of the fastest growing and largest B2B marketing teams optimize revenue and deliver personalized 1:1 experiences at scale.
- Remote work possible
FunnelEnvy is looking for a Machine Learning Engineer to improve client outcomes and influence product direction by application, analysis, and improvement of machine learning techniques on our available data.
We’re a rapidly growing startup near San Francisco with a unique B2B marketing optimization platform that uses Predictive Revenue Optimization to automate experimentation and personalization on the website and across channels.
Who We’re Looking For
The ideal candidate has experience in working with big data and machine learning models. You’re well versed in the fundamentals of software engineering development and can work in a rapid, iterative manner with a cross functional team of engineers.
In this role you will be working with our product engineering and solutions engineering team and interfacing with customers periodically. You’ll be responsible for:
Bringing together disparate data sources into a valid, useful format.
Implementing practical machine learning models with outputs applicable to directly improving client outcomes.
Integrating model inputs and outputs with existing systems for real time online usage.
Correctly measuring models with both offline metrics and via observed client impact, with an understanding of significance and noise.
Proposing, implementing, and validating improvements to existing ML components.
Skills & requirements
Key Competencies to be successful at this role
Background in applied statistics and mathematics
Experience with relational, no sql and cloud-based data platforms including MongoDB, Dynamo, Redshift and Redis
Working and proven knowledge of machine learning models, how to apply them, how to tune them
Use of Python libraries for machine learning
Understanding of Agile methodology/iterative development
Makes decisions based on evidence
Excellent communication skills
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