Chase Jones · signalpursuit.io

Signal over
noise.

End-to-end MLOps consulting and technical advisory for companies building production ML systems. Specializing in financial services and data-intensive infrastructure.

What I do

Built for teams that need
production, not prototypes.

MLOps & cloud consulting

Architecture to deployment. I help companies move ML from notebooks to production — designing pipelines, building the data platform, instrumenting observability, and keeping it running reliably at scale.

AWS SageMaker Bedrock & LLMs Data pipelines Model deployment ML monitoring Financial services

Technical advisory

Strategic ML and infrastructure guidance for seed through Series B companies. Architecture decisions, engineering hiring, LLM system design — and the pattern-matching from real failures and wins at scale.

Fractional CTO ML architecture Data platform strategy LLM & agent systems Hiring signal Fintech & AI startups
13
Production ML models
deployed to AWS
10+
Years building production
ML and data systems
2M+
Market observations
processed daily
6
Enterprise ML engagements
led at AWS

Background

Deep roots in
production systems.

STARlab Capital 2019 — Present

Technology Director

Lead engineering for a systematic derivatives trading firm — the full research-to-execution stack. Built a dual-store data platform ingesting 2M+ daily market observations, low-latency execution with automated failover, continuous strategy reevaluation with 100% trading-window coverage, live audit and position reconciliation workflows, and neural risk models. Currently leading LLM and agent tooling for research automation.

Derivatives trading Low-latency systems Neural risk models RL optimization Cloud architecture Data engineering
Amazon 2022 — 2023

Applied Scientist

Led a three-person engineering team (BIE, SDE, DE) to design and deploy a generic end-to-end MLOps platform using AWS serverless technologies for Amazon Advertising, shipping three production use cases. Designed a time series ranking methodology and built the internal Flask API to serve it.

MLOps platforms AWS serverless Time series Ad tech
Amazon Web Services 2019 — 2022

Data Science Consultant

Advised financial services and public sector enterprises on production ML using AWS best practices. Scoped and led five customer engagements end-to-end, deploying 13 models to production via SageMaker — including multi-task neural networks, semantic segmentation and image classification pipelines, and ensemble deep-learning forecasters.

AWS SageMaker Financial services Deep learning Image processing Forecasting
Caterpillar Inc. 2015 — 2019

Data Scientist

Inventory optimization for global supply chain using predictive modeling and numerical methods. Deployed three production models including a reinforcement learning agent, binary classifier, and unsupervised market basket analysis. Advised executive leadership on AI/ML strategy and led small delivery teams.

Reinforcement learning Supply chain optimization Inventory modeling

Education

M.S. Operations Management & Decision Analytics UNIVERSITY OF ALABAMA
B.S. Actuarial Science BRADLEY UNIVERSITY

Let's build something
that ships.

Working on production ML infrastructure, an AI platform, or a financial technology system? I'd like to hear about it.