Senior Machine Learning Engineer

QuinStreet • Full-time • US, US • $150k - $200k / year • 10m ago

Powering Performance Marketplaces in Digital Media

QuinStreet is a pioneer in powering decentralized online marketplaces that match searchers and “research and compare” consumers with brands. We run these virtual- and private-label marketplaces in one of the nation’s largest media networks.

Our industry leading segmentation and AI-driven matching technologies help consumers find better solutions and brands faster. They allow brands to target and reach in-market customer prospects with pinpoint segment-by-segment accuracy, and to pay only for performance results.

Our campaign-results-driven matching decision engines and optimization algorithms are built from over 20 years and billions of dollars of online media experience.

We believe in:

The direct measurability of digital media.
Performance marketing. (We pioneered it.)
The advantages of technology.

We bring all this together to deliver truly great results for consumers and brands in the world’s biggest channel.

Job Category

QuinStreet seeks an experienced engineer who can help us develop a conversational interface on top of our customer-facing services. The ideal candidate would have experience working with various open domain and task-oriented chatbots as well versed in current state-of-the-art multi-turn dialog systems, including the ChatGPT 4.0 API. They should have expertise in Prompt Engineering. The candidate should also possess a proven ability to develop solutions using minimal hardware resources. Given the rate at which new technologies show up in this space, the candidate should be able to pick and push the state-of-the-art in this area.

Responsibilities

Work with executives, product management, and senior architects to understand conversational AI needs and provide perspective.
Build the chatbot solution.
Provide inputs on model selection and fine-tune or do prompt tuning as needed to get best results.
Develop the chatbot UI.

Requirements

Hands-on experience with state-of-the-art systems and models.
Ability to analyze ongoing research and use solutions and algorithms from open source.
Ability to understand and articulate the business impact of technical decisions.
Good verbal & written communication skills.
2+ years experience in NLP techniques preferably with Chat GPT4.0 API
Evaluated, fine-tuned, and trained variants of BERT and T5 class models.
Experience with Prompt Engineering.
Experience with cloud-based conversational AI models through API's.
Ability to use OpenAI-based offerings.
Chatbot development experience is a plus.
Knowledge level: Machine Learning, NLP techniques, prompt tuning and a few-shot learning, conversational AI models
Experience with using LLM models
Using 3rd party APIs to build applications, Proven ability to design workflows, conduct experiments in an iterative and collaborative fashion
Owned end to end product created and taken to market
Prompt tuning, few-shot learning, model fine tuning for generative models (Big Plus)

The expected salary range for this position is $150,000 USD to $200,000 USD annually. This salary range is an estimate, and the actual salary may vary based on the Company’s compensation practices. The salary may be adjusted based on applicant's geographic location. The position is also eligible to receive performance bonus or commission and equity in the form of restricted stock units. This position is eligible to participate in the Company’s standard employee benefits programs, which currently include health care benefits; (2) retirement benefits; (3) the amount of paid days off (paid sick leave, parental leave, paid time off, or vacation benefits); (4) any other tax-reportable benefits.

#LI-REMOTE

QuinStreet is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, national origin, pregnancy status, sex, age, marital status, disability, sexual orientation, gender identity or any other characteristics protected by law.

Please see QuinStreet’s Employee Privacy Notice here.