Senior MLOps Engineer - Remote - Latin America

FullStack; Tacna; Remote; PEN 413,000 - 620,000; Full time

Benefits offered by this job

100% remote work

Competitive pay

Continuing education opportunities

Career growth

Job summary

FullStack is seeking a Senior MLOps Engineer to join our talent network and collaborate with US clients on flexible, project-based development work. You will integrate into client teams, shaping production ML workflows and tooling.

We require 5+ years in software/MLOps, advanced English, and a four-year degree. Experience with Vertex AI, MLflow, Kubeflow, and major cloud platforms is essential. Remote work offers opportunities to work with leading startups and Fortune 500 companies.

Qualifications

• 5+ years of professional experience in Software Engineering, MLOps, ML Engineering.
• Advanced English is required.
• Successful completion of a four-year college degree is required.
• Extensive experience building and operating MLOps platforms and production machine learning workflows.
• Hands-on experience with Vertex AI, MLflow, Kubeflow, or similar MLOps tooling.
• Strong background in feature stores, feature pipelines, SQL, and data workflows.
• Proven experience developing backend services using Python, Go, Ruby, JavaScript, or similar languages.
• Demonstrated experience working with GCP or other major cloud platforms such as AWS or Azure.
• Practical experience implementing A/B testing and experimentation frameworks for ML-driven products.
• Experience with AI-assisted development tools and incorporating AI into engineering workflows.
• Solid understanding of scalable, reliable, and production-ready ML systems.
• Familiarity with search or recommendation systems, real-time systems, and latency/performance optimization is a plus.
• Experience mentoring engineers and contributing to technical direction is a plus.
• Ability to create and maintain continuous integration and delivery of applications.

Responsibilities

• Integrate directly into client teams and work with designers and engineers daily.
• Contribute to building scalable, production-ready ML systems and workflows.
• Mentor engineers and influence technical direction.
• Implement CI/CD practices for ML applications when needed.

Skills

MLOps

ML Engineering

Python

Go

JavaScript

Advanced English

Cloud platforms (GCP/AWS/Azure)

Agile/Scrum

Mentoring

Education

Four-year college degree

Tools

Vertex AI

MLflow

Kubeflow

GCP

AWS

Azure

Job description

About FullStack

FullStack is your AI-native engineering partner, built to turn AI capability into certainty. Most companies can demo AI; few can get it to production and prove what it produced. We close that gap with three capabilities, AI built into your products from the start, elite vetted talent who apply it, and transparent execution that shows value every step of the way. With now over 600 customers in North America, FullStack is one integrated partner for all your AI engineering needs. With FullStack, you move forward with confidence.

We’re Most Proud Of

• Offering life-changing career opportunities to talented software professionals across the Americas.
• Building highly-skilled software development teams for hundreds of the world’s greatest companies.
• Having delivered hundreds of successful custom software solutions, which have positively impacted the lives and careers of millions of users.
• Our 4.1-star rating on GlassDoor.
• Our client Net Promoter Score of 68, twice the industry average.

The Opportunity

Join our talent network and connect with U.S. clients for flexible, project-based development work as a Senior MLOps Engineer.

• You will integrate directly into our client's team and work alongside their existing designers and engineers on a daily basis.

What We're Looking For

• 5+ years of professional experience in Software Engineering, MLOps, ML Engineering.
• Advanced English is required.
• Successful completion of a four-year college degree is required.
• Extensive experience building and operating MLOps platforms and production machine learning workflows.
• Hands‑on experience with Vertex AI, MLflow, Kubeflow, or similar MLOps tooling.
• Strong background in feature stores, feature pipelines, SQL, and data workflows.
• Proven experience developing backend services using Python, Go, Ruby, JavaScript, or similar languages.
• Demonstrated experience working with GCP or other major cloud platforms such as AWS or Azure.
• Practical experience implementing A/B testing and experimentation frameworks for ML-driven products.
• Experience with AI‑assisted development tools and incorporating AI into engineering workflows.
• Solid understanding of scalable, reliable, and production‑ready ML systems.
• Familiarity with search or recommendation systems, real‑time systems, and latency/performance optimization is a plus.
• Experience mentoring engineers and contributing to technical direction is a plus.
• Ability to work through new and difficult issues and contribute to libraries as needed.
• Ability to create and maintain continuous integration and delivery of applications.
• Forensic attention to detail.
• A positive mindset and a can‑do attitude.
• Experience working on Agile/Scrum teams.
• Meaningful experience working on large, complex systems.
• Ability to take extreme ownership over your work. Every day is a challenge to ensure you are performing to the expectations you and your team have agreed upon.
• Ability to identify with the goals of FullStack's clients, and dedicate yourself to delivering on the commitments you and your team make to them.

Nice To Have

We’re Seeking Engineers Who Are AI‑enthusiastic In Their Workflow. Professional Experience Or Personal Project Work With The Following Is a Significant Plus

• Cursor, Windsurf, or Google Antigravity.
• Claude Code, Gemini CLI, Codex, or Copilot CLI.

Work Authorization Requirements

• Applicants must be currently authorized to work in the country of this job posting on a full‑time basis.
• FullStack will not sponsor applicants for work visas now or in the future.

What We Offer

• Competitive pay.
• 100% remote work.
• The ability to work with leading startups and Fortune 500 companies.
• Continuing education opportunities.
• Opportunity to grow and expand your career.

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