Deep Learning Engineer

Digital ads drive 108 billion phone calls to U.S. businesses… Surprisingly, the marketers who paid for those ads typically have zero insight into these customer interactions and conversions. As the market leader in call analytics and customer experience optimization, DialogTech provides marketers with an end-to-end call attribution and analytics platform. This enterprise-class solution delivers transparency and control over every conversation, so companies can optimize lead generation, map the full path to conversion, and increase sales conversions.

Thanks to smartphones, consumers are calling businesses to engage in conversations at record rates throughout every stage of the customer journey, and at DialogTech we are changing the world of voice communications for our customers. We enable our customers to better attribute, route, personalize, and handle their voice interactions throughout the marketing and sales processes.

We are looking for a highly-motivated, deep-learning expert to join our data science team. You will enjoy learning, pragmatic thinking, and critical reasoning. You would be a part of a team that is driving innovation within the company, working on rapid prototypes and research. DialogTech tracks more than 100 million web sessions a month, and processes tens of millions of phone calls per month. Our extensive network of integrations provide access to display ad networks as well as post-call information (revenue, call disposition, etc.) Our data sciences team is responsible for helping our customers find the signal in the noise: which marketing activities and site paths lead to the most valuable phone calls? What is the best predictor of a successful outcome on a call? Within an industry, what keywords lead to the best results for the customer and the business? You will have call recordings, transcriptions, and our full data catalog at your disposal, using advanced techniques in machine learning, AI, and data sciences to design, execute, and refine experiments in partnership with, and on behalf of, our customers -- some of the biggest and most well-known brand names. As a member of this team, you will work with state of the art AI and Machine Learning tools and techniques on a large, complex, and evolving data set.

Remote workers are welcome. The team is already multi-location. If you happen to be in the Cleveland or Chicago area, you are welcome to work from one of our offices.

So, what will you be doing? 

  • Building and tuning neural networks
  • Crafting and building models using text or audio
  • Finding and building customer value in our large data sets
  • Participating in code reviews, brainstorming and pair-programming
  • Rapidly prototyping models and experiments
  • Staying up to date with, and in some cases advancing the state of the art in machine learning applications on conversational data sets
  • Promoting data science, machine learning, and AI approaches across our development and technology teams

What You Can Bring to DialogTech:

  • Strong Python skills
  • Familiarity with Text Vectorization techniques
  • Strong experience with at least one of the following libraries:
  • Tensorflow
  • Keras
  • Pytorch
  • Understanding of loss functions, activation functions, and how and when to choose them

Some nice to haves:

  • Familiarity with audio processing
  • BS in Computer Science/Engineering, or commensurate experience
  • Familiarity with cloud computing (AWS preferred), clusters, etc
  • Familiarity with Map-Reduce
  • Familiarity with SparkML, MXNet, or Mahout
  • Familiarity with at least one of: RDBMS/SQL, ElasticSearch, or NoSQL storage engines

At Dialog Tech, we hire SWANs, Smarter than average, hard Working, Ambitious, and Nice – we want the best on our team and in turn we give the best. Join us at one of the 101 Best and Brightest Places to Work in Chicago and nationally, 6 times running, Chicago Tribune's Top 100 Workplaces company and a 2017 Crain's Fast 50 company!

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. 

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