Tomás Ferreyra, llm engineer

Tomás Ferreyra

Senior LLM Engineer

Córdoba, Argentina · UTC-3 (America/Argentina/Cordoba) · 7 years of experience

Tomás focuses on measurable model behavior, reliable retrieval, and production evaluation.

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Why this profile fits

Evaluation before optimization

Defines datasets, graders, and regression checks so model changes are measured against real failure cases.

Reliable retrieval and tool use

Improves grounding, structured outputs, tool permissions, and recovery behavior for production workflows.

Cost and latency control

Treats task success, response time, and model spend as one production system rather than separate concerns.

Relevant toolkit

PythonLangGraphClaude APIOpenAI GPT APIPostgreSQL

Delivery evidence

Selected work

Per-Request Model Router & Cost Governor

B2B support-automation SaaS

Designed a routing layer that scores each request and picks the cheapest model (Claude, GPT, or Gemini) that clears a Braintrust quality gate, with semantic caching and prompt compression on top. Cut monthly inference spend 64 percent and p95 latency by more than half while holding CSAT flat.

PythonLiteLLM

Eval-Gated Prompt CI

Fintech lending platform

Built a CI pipeline where every prompt or model change runs an offline eval suite plus a 5 percent canary before promotion, with results posted to pull requests. Regressions caught pre-production rose to 9 in 10, and the team shipped prompt changes daily instead of weekly.

PythonLangSmith
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Relevant experience

Career timeline

Senior LLM Engineer

Jan 2023–Present

Corven (fintech payments scale-up) · Remote (US client)

  • Designed a per-request model router across Claude, GPT, and Gemini that moved 71 percent of traffic to smaller models and cut monthly inference spend from 48k to 17k US dollars with no measurable quality loss.

Machine Learning Engineer (Applied NLP)

Feb 2021–Jan 2023

Helio (B2B customer-support SaaS) · Remote

  • Migrated an intent-classification stack from fine-tuned BERT to few-shot LLM prompting, cutting model-maintenance time 60 percent while improving F1 from 0.83 to 0.90.

Machine Learning / Data Engineer

Jun 2019–Feb 2021

Datalexa (e-commerce analytics vendor) · Córdoba, Argentina (hybrid)

  • Built recommendation and churn models in Python and scikit-learn that lifted repeat-purchase rate 11 percent for a mid-market retail client.

Skill depth

Show experience in context.

VerbalCommunicationDomainUnderstandingProblemSolvingCodeQualitySystemDesignDeliverySpeed
Competency shapeAssessment across the same six dimensions used for every profile.

Relevant experience by skill

Python7 years
Applied NLP & ML7 years
FastAPI5 years
Prompt Engineering4 years
Retrieval-Augmented Generation4 years
Vector Search4 years
LLM Evaluation3 years
Model Routing & Cost Control3 years
See the complete skill index

Languages

PythonTypeScriptSQLBash

Frameworks

FastAPILangGraphLangChainGuardrailsPydanticDjango REST

Libraries/APIs

Claude APIOpenAI APIGemini APILiteLLMinstructorHugging Face Transformerssentence-transformerstiktoken

Tools

BraintrustLangSmithOpenAI EvalsWeights & BiasesMLflowGitDockerGrafana

Paradigms

RAGPrompt EngineeringModel RoutingEvaluation-Driven DevelopmentTool CallingStructured OutputsSemantic CachingCost Optimization

Platforms

AWSGCPAzure OpenAIModalVercel

Storage

pgvectorPineconeQdrantWeaviatePostgresRedis

Other

LLM ObservabilityA/B TestingToken BudgetingUnit Economics

Education

Formal background

Licenciatura en Ciencias de la Computación, Computer Science

Universidad Nacional de Córdoba (UNC) · 2013–2018 · Graduated with honors; thesis on neural sequence models for text

Especialización en Inteligencia Artificial, Artificial Intelligence

Instituto Tecnológico de Buenos Aires (ITBA) · 2020–2021

Credentials

Certifications

Google Cloud Professional Machine Learning Engineer

Google Cloud · 2024 · Certified

NVIDIA-Certified Professional: Generative AI LLMs

NVIDIA · 2026 · Certified

Communication

Languages

Spanish

Native

English

Fluent

Portuguese

Conversational

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