Senior Staff Data Science Engineer, AI and MLOps

Lab Summary:

Bixby is an intelligent personal assistant which is only available as a built-in application on Samsung flagship devices and wearables. This application uses Natural Language Understanding to perform tasks on these devices using voice/ text, including but not limited to making phone calls, sending text messages, setting up meetings, opening apps, setting alarms and timers, getting directions, answering general questions, providing information about restaurants and other businesses, etc.

Samsung Bixby Labs is working towards a vision of a voice assistant that provides a unified AI experience across multiple devices. Our industry-leading hardware platforms like the Galaxy phones, and home appliances like smart refrigerators and TVs, smart washers and dryers, etc. allow for deep integration of the AI services like Bixby voice assistant and hardware devices. Real-time AI services on these connected IoT devices enable users to interact with devices more naturally via spoken dialogue, visual interaction, continuous learning, and big data analysis. Researchers and engineers are working hard towards making the Samsung vision a reality.

Position Summary:

Modern AI services are delivered online, in real-time and 24x7. To adapt to this new world, we are building a continuously monitoring and updating platform centered around AI and machine-learned models. The platform manages model training, multiple production releases, data analytics, integration, bugs, rollbacks, patches, A/B testing, online monitoring, etc.  The processes are independent of the type of real-time AI service – voice assistants, web search, autonomous vision systems, etc. If you are interested in data science, AI and machine learning platforms for the online AI services world, this is your dream job.

Position Responsibilities: 

• Design, streamline and implement MLOps processes for continuous ML modeling and monitoring
• Leverage Data Science techniques to establish pipelines for continuous user satisfaction evaluation and monitoring processes, A/B testing, mining insights, and informing the engineers and executives with data-backed hypotheses
• Evaluate and analyze pre-production AI model candidate releases and provide insights derived from production data logs
• Facilitate integration of the AI system/software into existing production environment
• Work with release engineering team and establish a proper model release certification process
• Keep current with the fast-moving world of AI, from modeling techniques like generative AI to platform innovations

Required Skills: 

• Masters in Computer Science, Electrical Engineering, Experimental Physics, Statistics or equivalent combination of education, training, and experience 
• 10+ years of working experience in related field after degree
• Knowledge of statistical techniques (t-tests, confidence intervals, p-value, etc.), tools (R, SAS, etc.) and controlled experimentation (e.g. A/B testing
• Experience with platforms like AI automation platforms like Kubeflow pipeline, MLFlow, Azure Pipeline, AWS SageMaker Pipeline; Airflow, Jenkins; Spark, Hadoop, Kafka; Jira, and Git
• Experience with data visualization/dashboard tools like Superset, Elasticsearch and Kibana, Tableau, Grafana
• Experience with building AI applications using Deep Learning platforms like PyTorch, TensorFlow on GPU, Jupyter Notebook
• Strong programming skills (C++, Java, Javascript, etc.) and scripting skills (Python, R, Perl, SQL, etc.)
• Strong problem-solving skills
• Fluent in Linux, scripting in Python and other languages
• Good communication and team-working skills

Special Attributes: 

• Experience with building Apps in Alexa, Google Assistant, or Siri a plus
• Experience with cloud computing platforms like AWS, GCP and Azure a plus