Description:

Design and implement machine learning models to build personalized features and enhancements in partnership with appropriate stakeholders.
Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready.
Collaborate with multidisciplinary teams to understand project requirements and objectives.
Contribute to projects that require cutting-edge technology and innovative approaches.
Coach and mentor other engineers to allow for a robust and reliable Machine Learning and AI development process.
Passionate about building high-performance and cost-efficient solutions using the latest container, cloud, and serverless technologies.
Feel a sense of accomplishment when identifying bottlenecks and improving software efficiency.
Obsessed with quality and user experience – attention to detail and the ability to think abstractly.
A thought leader who challenges conventional thinking throughout the business to understand and identify pain points and improve the status quo through data-driven solutions.
Looking for opportunities to gain a wide breadth of knowledge across the entire stack and interested in developing more deeply into backend technologies.

Requirements:

Must have experience with Natural Language Processing (NLP) and Generative AI technologies.
Strong product sense with a focus on delivering user-facing, data-driven features.
Proficiency in developing and optimizing advanced Retrieval-Augmented Generation (RAG) pipelines.
Excellent programming skills in Python, with a focus on writing clean and modern code.
Proven expertise in building, fine-tuning, and deploying Large Language Models (LLMs).
Nice-to-haves include familiarity with knowledge graph technologies for enhancing LLM capabilities, experience in designing and implementing APIs, and familiarity with LLamaIndex/LangChain frameworks.
Ability to read Ruby and Ruby on Rails codebases is a plus.
Knowledge of cloud-based tools and services for building and deploying generative AI applications, preferably ones hosted by AWS.
Familiarity with MLOps practices and continuous integration/deployment for ML models is desirable.

The annual salary for this position is $160,000 to $225,000 + equity and benefits, with starting pay depending on various job-related factors.
Enjoy a fast-paced and collaborative remote environment where you will regularly engage with our senior leadership.
Receive competitive compensation and health benefits, including medical, dental, and vision coverage.
Benefit from Transit, Flex Spending, and 401(k) benefits.
Gain meaningful equity in the company.
Take advantage of a flexible PTO policy and generous paid holidays/company off days per year.
New hires will receive a stipend for a remote workstation.