Overview

Simplr (www.simplr.ai), is an early-stage startup in San Francisco seeking to disrupt the tired and ineffective customer service model and backed by a $7.5 Billion Parent Company. Simplr’s AI + Human approach to customer service is out to prove that on-demand, US-based, customer service and sales support is the best solution for today’s fastest-growing startups in apparel, health, beauty, food, electronics, and home goods. We are also proud that our platform enables underutilized talent such as teachers, military spouses, and stay-at-home spouses to supplement their family income from the comfort of their own homes.

About the team

We believe in giving our best and brightest the autonomy to define their solutions. Our technology teams work in the Journey Team model, which allows us to move quickly and continuously deploy new features, giving data scientists & researchers freedom to cover all areas of the development process from ideation, research, experimentation, and scaling of new products and services. The position reports directly to the head of Artificial Intelligence and Machine Learning.

What you’ll be doing:

Take Simplr’s automation, self-help, and bot capabilities on digital customer service channels to the next level, working within a highly focused and multi-disciplinary team
Follow cutting-edge NLP research and leverage open-source frameworks to develop self-learning models, handling multiple entities and intents in one utterance. Our automation suite is backed by human specialists so it is a safe place to innovate!
Utilize our on-demand Simplr Specialists (Agents) to continuously train and improve the responses offered to customer inquiries
Build scalable solution configurable through no code interface
Drive a Minimum Viable Product (MVP) test-and-learn approach and push to learn fast
Work in an iterative manner from framing problems, to building prototypes, to deploying end-to-end and reliable production-grade solutions
Help defining and monitoring the right Key Performance Indicators (KPIs) to track and deliver on critical objectives and key results

What you’ll bring to the team:

Your experience building conversational agents in the CX domain, not just rules based bots
Your technical excellence, specifically in latest NLU and transformer models
The ability to root cause, define, and solve complex problems in ambiguous situations
Innate curiosity and product mindset helping you articulate new ideas as well as novel technical approaches
Ability to work and collaborate with different functions of the organization, from operation teammates, to product managers and engineers
Excellent communication (written and oral) and presentation skills, including creating and sharing out complex ideas to peers
You’re a thinker and doer. You offer out-of-the-box ideas and aren’t afraid to roll up your sleeves to get the job done
Respect for all people, an open mind, and an open heart. We pride ourselves on building inclusive environments. After all, it’s the diversity of thought that builds great products!

Company:

Simplr

Qualifications:

Experience and education

Requires a master’s degree in analytics, computer science, electrical engineering, computer engineering, or related advanced analytical & optimization fields, plus at least 2 years of related experience in current or previous company
At least 2 years of research and/or work experience in Machine Learning, deep learning and/or building conversational agents. Peer reviewed publications in NLP, Speech or Machine Learning is a plus.
Familiar with at least one of the deep learning framework such as PyTorch and/or Tensorflow
Solid Knowledge in Deep Learning and/or Machine Learning gained through academic coursework or any amount of internship/work experience. Experience in Neural Networks and Natural Language Processing is a plus.
Knowledge in Statistics, optimization theoretical concepts and/or optimization problem formulation gained through academic coursework or any amount of internship/work experience
Solid Knowledge in Python programming gained through academic coursework or any amount of internship/work experience.

Educational level:

Master Degree

Level of experience (years):

Mid Career (2+ years of experience)

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