Artificial Intelligence (AI) Data Engineer
- Post Date:April 24, 2019
- Applications: 29
CallMiner empowers organizations of any size to extract and act on intelligence from customer interactions and feedback, including live and recorded calls, chat, email, social platforms and surveys, for improving customer experience, sales, marketing, compliance, and agent and customer engagement center performance. Highlighted by multiple customer achievement awards, including eight Speech Technology implementation awards in the past six years, CallMiner was recently named a leader in the industry analyst report Forrester New Wave: AI-Fueled Speech Analytics Solutions, Q2 2018.
At CallMiner, we hire great people and challenge them every day. CallMiner team members are passionate about delivering innovative technology solutions and industry leading customer success. Core to our culture is the power of feedback which we leverage to improve our own organization every day in every way. To hear more about what it’s like to work at CallMiner, watch our video at Careers.CallMiner.com
The AI & Research team at CallMiner is tackling some of the toughest problems in speech analytics with AI – deciphering human conversations. We do this using “Conversational AI” – a blend of NLP, ML, and statistical ingenuity. The goal of the team is to augment the leading Speech Analytics product suite in the industry, Callminer Eureka. The challenge of unlocking business intelligence from human speech requires a multidisciplinary approach, and the best candidates have proven experience in applying ML, technology, and business strategy to discover key insights that lie hidden within our customer’s data sets.
This role bridges the gap between Software Engineer and Data & Research Scientist and will focus on refining models and ML approaches relating to speech analytics. It will involve wrangling large amounts of speech data to figure out efficient and elegant ways to take our product suite capabilities to the next level. In addition, using new and progressive tools, engineer and extract features, test them in models, and predict outcomes using AI algorithms.
The ideal candidate can understand how to extract data efficiently from a variety of sources, build and test their own machine learning models, and deploy those models using either embedded code or API calls to build new product features.
Key responsibilities include:
- Understand how to efficiently “wrangle” data from relational and non-relational data stores, and prepare it for machine learning (feature engineering, data transformations).
- Improve and optimize current machine learning models and processes to handle ever-growing big-data training sets.
- Work with the CallMiner Dev and Product teams to integrate new AI models and technology into the current Eureka product platform.
- Manage the release of new models into production and partner with product teams in monitoring them for drift and maintaining them going forward.
- Develop feedback learning loops and fine-tune models before and during production release.
- Assist in designing, prototyping, coding, debugging, and releasing new tools to aid in AI/ML process.
- Build tools and datafeeds to support experimentation and data analysis, including visualization and statistical analysis.
- Design experiments to understand user behavior and make data driven decisions.
- Bachelor’s degree in computer science or closely related field, Masters preferred.
- 2+ years’ experience in production AI modeling or commercial software development.
- Strong coding fundamentals and background in either C#, Java, or python. Proficient in version control tools like Git or TFS
- Strong database fundamentals, including relational databases like Microsoft SQL/Oracle/MySQL, and non-relational databases like MongoDB, Cassandra, etc.
- Proven track record of strong verbal/written communication and presentation skills, including an ability to effectively communicate with both business and technical teams.
- Experience with big data architecture and distributed computing processes and platforms (e.g. Map/Reduce, Hadoop, Hive, Spark, Kafka, etc.)
- Experience in neural networks, logistic regression, natural language processing and word embeddings.
- Experience with new and traditional machine learning APIs and computational packages and tools (e.g. TensorFlow, Keras, Scikit-Learn, NumPy, SciPy, Pandas, DataRobot, Tableau, AWS/Azure)
- Skilled in NLP, Conversational AI, predictive and classification algorithms.
- Speech recognition programming and use