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Machine Learning Engineer
Podchaser
Remote
Podchaser is the world’s most comprehensive podcast database — collecting, enriching, and distributing podcast insights to power discovery for listeners, podcasters, and brands. Podchaser was born from a humble Reddit post by CEO Bradley Davis in July 2016 and has since grow into a global team of talented developers, designers, data moderators, user support specialists, marketers, project leads, content creators, advisors, and more! At Podchaser, we believe a unique, aggregated dataset with listener habits, deep layers of metadata, advanced tagging, and powerful machine-driven recommendation systems will bolster the present and future of the podcasting ecosystem.

Your Responsibilities

- Work with the largest collection of podcast information, spanning a catalog of over 150 million episodes, 100 thousand creators, and hundreds of millions of daily listens.
- Develop and deploy models to give listeners, podcasters, and advertisers insights into any podcast. Use internal tools to test and solve support tickets
- Our data is the beating heart of our product offering, and you will be responsible for turning our huge volumes of raw data into information enabling our customers to find exactly the shows and creators they want.
- Our Data Team is focused on a broad range of problems, and we take a variety of different approaches to solving them. You’ll be given the opportunity to explore and iterate on our existing statistical and ML based models, as well as set the direction for new areas of exploration.

Necessary skills

- At least 4 years in a Data or Machine Learning Engineering role or similar roles
- Exceptional analytical and problem-solving skills; ability to structure and conduct appropriate analyses
- Strong written and verbal communication skills
- Experience working with big data – some of our datasets have trillions of data points
- Experience with NLP, including sentiment analysis, text summarization, and entity recognition/extraction
- Strong familiarity with a variety of machine learning approaches, including neural networks, random forest and GBTs, KNNs, k-means clustering, various types of regressions, and Bayesian techniques, and when to use certain ones
- Expert-level SQL – most of our data is in MySQL or Redshift and you should have well-honed skills at accessing it

You’ll Stand Out If You Have

- Podcasting industry expertise
- Proficiency in Slack, Asana, and Knowledge Base Systems (i.e. Guru/Trainual)
- Experience with large scale data processing using tools like Apache Spark
- Experience with Elasticsearch or other Lucene-based inverted indexes
- Experience with data visualization tools such as Tableau

Company Perks

- Fully remote, 100% virtual work in a high-growth, high-flexibility environment
- Great benefits including health*, dental*, vision*, 401 w/ match*, mobile reimbursement plan, generous PTO (with every other Friday off in Summer!), and more (*for US-based employees)
- Supportive and fun work environment. Learn more about our 5-star work culture on GlassDoor

$110,000 - $130,000 a year
Full-time
Mid Level