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Rol IA · Oferta abierta

Senior ML Platform Engineer — Remote (US)

Snowflake

Tiempo completo
Senior
AI platform
Remote
Remote · United States
Remote, United States
$165k–$220k + equity

Este anuncio está pensado para talento nativo en IA: habilidades y herramientas claras para saber si encajas antes de aplicar — y para reducir descartes por desajuste.

3 habilidades2 herramientas

Aplicar ahora Buscar talento afín

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Cómo trabajarás, dónde y fechas clave del anuncio.

Empleo: Tiempo completo
Modalidad: Remote
Ubicación: Remote · United States
Compensación: $165k–$220k + equity
Nivel de experiencia: Senior
Equipo: AI platform
Beneficios: Remote-first US, equity, home office stipend.
Cómo aplicar: Platform feature for model registry or batch inference.
Web de la empresa: www.snowflake.com
Publicada: 12 jun 2026
Actualizada: 3 ago 2026

Sobre el rol

Qué busca el equipo y cómo encaja el puesto.

Snowflake is hiring a Senior Senior ML Platform Engineer — Remote (US) on the AI platform team (Remote · Remote, United States). This is a hands-on role in LLM & generative AI—not a generic “AI enthusiast” post.

You will own LLM features, retrieval, agents, and evaluation end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.

Snowflake's AI layer brings models and apps to enterprise data without movement. US-remote friendly teams build training and inference paths on Snowflake.

Senior ML Platform Engineer (Remote, US): feature pipelines, model registry, and cost-aware batch inference for customers.

What you will do

Ship production ML platform on cloud data with clear evaluation, monitoring, and rollback paths—not demo-only notebooks.
Partner with product, design, and domain experts on requirements, trade-offs, and safe rollout.
Improve data quality, labeling, and offline metrics that correlate with business KPIs.
Document architectures and runbooks for on-call and customer-facing teams.
Mentor engineers on testing, observability, and responsible AI practices.

What we look for

Strong Python and modern ML/LLM stack experience with multiple shipped features.
Comfort with SQL, experimentation, and communicating results to non-technical stakeholders.
Pragmatic ownership from prototype to production—including cost and latency budgets.
Eligible to work in the listed country; professional English (French a plus for Paris roles).

Habilidades que buscamos

Qué implica cada capacidad en este rol — no solo una lista de palabras clave.

Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
AWS
Cloud primitives for training, storage, IAM, and cost-aware LLM & generative AI deployments.
SQL
Analytical SQL for features, cohorts, label quality, and experiment analysis at scale.

Herramientas y stack

Plataformas y productos mencionados para este rol (APIs, IDEs, BBDD vectoriales, CRM, diseño, etc.).

KubernetesTool
Deploying and scaling model services with health checks, autoscaling, and rollout discipline.
DockerTool
Containerized services and reproducible dev environments for ML and LLM workloads.

Encajas muy bien si…

Adaptado a esta oferta — úsalo para comprobar tu encaje antes de aplicar.

You can show evidence in your application: Platform feature for model registry or batch inference.
Several of these show up in recent shipped work—not only on your CV: Python, AWS, SQL, Kubernetes, and Docker.
You have owned LLM features, retrieval, agents, and evaluation in production: debugging live issues, running postmortems, and iterating from real user or business signals.
You communicate clearly in writing, document decisions, and can overlap with the team’s core hours for pairing and incident response.
You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.
You read the full listing (comp: $165k–$220k + equity, benefits in At a glance) and your expectations align.

Aplicar

Solo cuentas candidato: añade tu titular y bio en Mi cuenta, y opcionalmente un enlace o PDF de CV para que los reclutadores vean tu CV completo. Luego escribe un breve pitch — las candidaturas usan el correo de tu cuenta.

Lo que pide la empresa

Platform feature for model registry or batch inference.

Inicia sesión con cuenta candidato para aplicar

Regístrate, añade titular y bio; luego podrás adjuntar enlace o PDF de CV en Mi cuenta antes de aplicar. Así las candidaturas quedan ligadas a tu perfil.

Iniciar sesión Crear cuenta candidato

Sugerencias

Talento IA que podría interesarte

Perfiles ordenados por solape con habilidades y herramientas de este rol — útil si contratas equipo o comparas candidatos.

Aún no hay coincidencias cercanas en el directorio — prueba Buscar talento con tus filtros.

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Senior ML Platform Engineer — Remote (US)

Talento IA que podría interesarte

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