AI/ML Scientist

Responsibilities

Conduct cutting-edge research in Generative AI (GAI) and Large Language Models (LLMs), staying at the forefront of AI/ML advancements

Identify and explore novel algorithms, architectures, and techniques to enhance model performance, scalability, and efficiency in e-commerce applications

Train, deploy, and optimize GAI and LLM algorithms and models to improve product recommendations, search relevance, personalization, and customer interaction

Design, build, and manage ETL processes to gather data from various sources, transform it into a usable format, and load it into a data warehouse or data lake

Collaborate with product, engineering, and data teams to identify opportunities for applying generative AI and LLMs to solve complex problems and enhance customer experiences

Design and conduct experiments to evaluate the performance and effectiveness of generative and language models in an e-commerce context

Benefits

Competitive salary with uncapped commission and equity

Benefits: Health, dental, and vision insurance, 401(k), Unlimited PTO

As more of the shopping journey shifts to Instagram, Tik tok, ChatGPT and Google, purchase decisions form before consumers reach your site.

Bellevue, Washington, USA

https://www.spangle.ai/

Distribution of Different Job Fields Receiving Sponsorship

Represents job field similar to this job

Product Management

Trends of Total Sponsorships

*2026

(1)

Total Funding

$21M

Key Investors

NewRoad Capital Partners,Streamlined

Madrona,Streamlined

2026-01-08

Series A· $15M

2025-03-18

Seed· $6M

Recent News

PR Newswire

Spangle Launches Spangle Halo, Bringing Retailer-Side Intelligence to AI Agent Commerce

2026-10-16

Spangle Launches AI Discovery as More Shopping Decisions Move to AI

2026-09-22

thesaasnews.com

Spangle AI Raises $15 Million in Series A

2026-01-12

Company data provided by

Qualifications

Ph.D. or Master's degree in AI, Machine Learning, Data Science, Computer Science, Electrical Engineering, Statistics, or a related field with a focus on artificial intelligence

2-5 years of experience, proven experience in developing and deploying AI applications end to end in real-world applications, preferably in e-commerce or a related field

Deep expertise in generative models (e.g., GANs, diffusion models, autoencoders) and Large Language Models (e.g., GPT, BERT, T5, LLaMA)

Experience with LLM fine-tuning, RL post training, prompt engineering, and deploying LLMs for applications such as natural language understanding, content generation, and recommendation systems

Strong understanding of the architecture and training techniques for transformer-based models, attention mechanisms, and optimization strategies for LLMs

Expertise in distributed training of large-scale models, including using parallelization and optimization techniques for handling large datasets

Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, Hugging Face, and libraries focused on GAI/LLM development

Familiarity with data warehouse and data pipeline technologies (e.g., Amazon Redshift, Google BigQuery, Snowflake, Apache Airflow)

Knowledge of cloud platforms and services (e.g., AWS, Google Cloud, Azure) for deploying and scaling machine learning models, especially those involving LLMs and GAI

Understanding of reinforcement learning and its applications within generative AI and LLMs for decision-making, personalization, or conversational AI systems

Required skills

Generative models, Large Language Models, LLM fine-tuning, Reinforcement learning, Transformer-based models, Distributed training, Python, PyTorch, TensorFlow, Hugging Face, Data warehouse technologies, Data pipeline technologies, Amazon Redshift, Google BigQuery, Snowflake, Apache Airflow, Cloud platforms, AWS, Google Cloud, Azure

Experience

2-5 years