Bring me in for high-stakes AI and systems delivery.
I take on focused freelance work where the technical bar is real: model pipelines, scientific analysis systems, forecasting, data engineering, research prototyping, and product features that need to move from concept to dependable implementation.
Production engineering for non-trivial ML workloads.
Three explicit engagement tiers. Zero ambiguous billing.
Every contract begins with a clearly defined scope, explicit acceptance criteria, and daily asynchronous terminal updates.
Technical Sprint
Best for audits, rigorous prototypes, proof-of-concept builds, profiling compute bottlenecks, or unblocking an engineering effort currently stalled on edge cases.
- done Detailed Scoping Brief & Hypothesis Map
- done Working prototype code + setup script
- done Live 60-min recorded screen walkthrough
Technical Retainer
Best for engineering organizations seeking a fractional senior technical collaborator across AI architecture, research validation, and compute optimization.
- done Dedicated weekly architecture review slots
- done Direct Slack/Discord access for core team
- done Pull request review & algorithmic auditing
Clear deliverables. No fragile technical debt.
Explicit Contract Deliverables
Rigorous specification document mapping requirements, dataset schemas, performance benchmarks, and explicit non-goals before code is executed.
Clean system structure designed for your actual compute budget and operational capacity, avoiding unnecessary cloud complexity.
Type-hinted, modular code with reproducible run scripts, automated test matrices, and containerized Docker/Conda manifests.
Recorded video walkthrough, runbooks, and direct pair-programming sessions to guarantee your internal engineers can maintain the system.
Best Clients For This Setup
Seed and Series A founders who need an experienced technical builder to execute a critical AI pillar without hiring a bloated team.
Principal investigators and labs lacking the engineering bandwidth to translate messy academic code into scalable HPC pipelines.
Teams whose legacy training jobs constantly fail, leak memory, or lack reproducible regression test coverage.
Engineering directors validating whether a cutting-edge model can meet operational cost and latency thresholds before full hiring.
Let’s scope the problem.
Fill out this structured intake matrix to receive an initial architecture diagnostic and quotation within 24 hours.
- arrow_forward Primary technical blocker or desired pipeline
- arrow_forward Data constraints (confidentiality, format, size)
- arrow_forward Compute environment (AWS, GCP, On-Prem HPC)
- arrow_forward Ideal kick-off horizon and delivery timeline
Looking for full-time research leadership or lab architecture roles?
In addition to high-impact contracts, I am open to select full-time research scientist and lead ML systems positions globally.