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Forward Deployed Engineer

Trabajo disponible en: Mexico City, Mexico City, México
Empresa: Arkham Technologies
Tiempo completo puesto
Publicado en 2026-10-10
Especializaciones laborales:
  • TI/Tecnología
    Ingeniero de IA, Machine Learning
Descripción del trabajo
Description
Forward Deployed Engineer

About Arkham:

Arkham is a Data & AI platform that helps large enterprises:
Unify fragmented systems and data
Build a single source of trusted operational metrics
Solve complex challenges with AI tailored to their operations

Teams at Circle K and Kimberly-Clark partner with us to deploy AI-powered solutions for sell-out forecasting, pricing and promo analysis, and automated order assignment. With Arkham, they achieve high-impact results fast, creating a strong foundation for long-term AI transformation.

About the Role

As a  Forward Deployed Engineer , you help drive the AI transformation journey for our customers. You work hands-on across data science, AI architecture, and implementation, partnering closely with client stakeholders to deliver high-impact solutions.

Once a customer's Data Platform is live in Arkham, you help deliver and expand AI use cases. You partner with BI, Finance, Operations, and business stakeholders to:
Identify high-leverage AI opportunities
Build robust ML and GenAI solutions
Deploy production-ready systems
Support adoption across the client organization

You will typically contribute to 1-4 implementations simultaneously, working alongside senior team members.

What You'll Work On
Build and deploy ML models (like forecasting, optimization, clustering, and anomaly detection models)
Develop Generative AI workflows
Implement AI Agents that automate analysis and operational decisions
Follow best practices for model monitoring, retraining, and governance
Contribute to the first  Aha  moment: within 2-4 weeks, help deliver an operational AI solution that solves a core business pain point
Define data requirements and modeling strategies in collaboration with the team

What We Require
2-3 years of hands-on Data Science experience
Experience delivering ML systems into production
Some exposure to client-facing or stakeholder-intensive environments
Solid proficiency in Python and SQL

Experience with forecasting and time-series models

Experience with supervised and unsupervised ML
Familiarity with Generative AI and prompt engineering
Familiarity with AI agents and LLM-based workflows
Proficiency with Git and collaborative development workflows
Good understanding of statistical modeling and model evaluation
Strong communication and collaboration skills

Why This Role Is Different
You don't just build models, you help drive transformation. You work directly with ambitious teams solving meaningful problems, with real ownership and room to grow.
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