Open to opportunities

Spencer Allison

@spencerallison

Message

Senior software engineer specializing in AI, data infrastructure, and scalable cloud systems.

United States

Message

What I'm looking for

I seek roles building production AI and data systems—focused on scalable cloud deployments, rigorous evaluation, and collaborative teams that value experimentation and measurable impact.

I am a Senior Software Engineer with a decade of experience delivering data-driven systems and AI-powered applications across fintech, gaming, and large-scale cloud platforms. I design and build scalable data infrastructure, machine learning pipelines, and production LLM services using cloud-native technologies to drive measurable improvements in model quality and system performance.

My work spans building RAG pipelines, integrating transformer models, implementing distributed ETL with Spark, and deploying inference services on AWS serverless and container platforms. I emphasize rigorous evaluation, prompt engineering, and automated experimentation—efforts that have increased system accuracy and reduced latency for high-volume, mission-critical workloads.

Experience

Work history, roles, and key accomplishments

Current

Senior Software Engineer

Current

Coinbase

Aug 2022 - Present (3 years 8 months)

Developed production-grade LLM applications and RAG pipelines to power financial knowledge assistants, improving system accuracy metrics by 34% and enabling low-latency, fault-tolerant inference on AWS serverless infrastructure.

Python RAG Vector Databases AWS Lambda Hugging Face Spark Prompt Engineering

Software Engineer

FanDuel

Jul 2020 - Aug 2022 (2 years 1 month)

Built ML pipelines and real-time inference APIs to predict player engagement and personalize betting recommendations, improving model performance by 27% via optimized feature engineering and experimentation workflows.

Python Spark Airflow TensorFlow scikit learn Docker Kubernetes

Software Engineer

Amazon

Mar 2016 - Jul 2020 (4 years 4 months)

Built large-scale ETL and streaming data pipelines with Spark and Kafka, optimized ETL runtimes by 31%, and designed S3-based data lake strategies and data quality monitoring for analytics and ML workflows.