Field Engineer - Ops Efficiency & Automation

Mexico

Full-time

Job Description

This job posting has expired and no longer accepting applications.

Welo Data works with technology companies to provide datasets that are high-quality, ethically sourced, relevant, diverse, and scalable to supercharge their AI models. As a Welocalize brand, WeloData leverages over 25 years of experience in partnering with the world’s most innovative companies and brings together a curated global community of over 500,000 AI training and domain experts to offer services that span:

ANNOTATION & LABELLING: Transcription, summarization, image and video classification and labeling.

ENHANCING LLMs: Prompt engineering, SFT, RLHF, red teaming and adversarial model training, model output ranking.

DATA COLLECTION & GENERATION: From institutional languages to remote field audio collection.

RELEVANCE & INTENT: Culturally nuanced and aware, ranking, relevance, and evaluation to train models for search, ads, and LLM output.

Want to join our Welo Data team? We bring practical, applied AI expertise to projects. We have both strong academic experience and a deep working knowledge of state-of-the-art AI tools, frameworks, and best practices. Help us elevate our clients' Data at Welo Data.

About the Role

We are looking for a Field Engineer who is passionate about customer success, operational efficiency, and quality optimizations. In this role, you will act as a technical partner and bridge between quality, operations, sales, and product engineering—helping teams plan, build, and execute complex technical solutions and automations. You’ll work directly with operations stakeholders to develop integrations, automation workflows, and self-serve tools that improve efficiency and scale operations.This role is ideal for someone who thrives at the intersection of engineering and people success, combining technical expertise with a deep understanding of customer needs to drive impact.

About the Role

What You'll Do

Serve as a technical bridge and advisor between quality, ops, sales, and engineering teams, ensuring smooth collaboration and alignment.

Troubleshoot and optimize enterprise integrations to ensure seamless data exchange.

Plan and execute complex technical solutions that support customer and internal team success and reduce manual work.

Consult with customers and internal teams on best practices for platform use, automation, and data quality.

Create self-serve solutions that empower internal teams to handle common technical tasks independently.

Design and implement programmatic quality checks to improve data consistency and accuracy.

What We Are Looking For

Technical experience in Python, JavaScript, or another relevant language for automations, integrations and scripting.

Technical experience in HTML and CSS for lightweight frontend UI building.

Strong problem-solving skills with the ability to plan and execute complex technical solutions.

Excellent communication and collaboration skills, with the ability to work across multiple teams.

Curious and self-driven, with a strong desire to learn and adapt to new technologies and challenges.

Experience working with APIs, data pipelines, and automation frameworks.

Customer success mindset, with a passion for helping internal teams and customers succeed.

Ability to translate operational concepts into actionable solutions for both technical and non-technical stakeholders.

Experience with cloud platforms (AWS, GCP, or Azure) and data processing tools is a plus.

Requirements

2+ years of engineering experience, ideally in a client-facing setting.

Curiosity and desire to learn Bachelor's degree with an engineering or analytics focused field (e.g., Computer Science, Engineering, Mathematics, Statistics) or equivalent work experience.

Hands-on experience in ML lifecycle applications, data management, and data wrangling.

Experience with HTML, and CSS for simple UIs Experience working with REST APIs Proficiency in at least one scripting language, preferably Python Experience with C# is a plus.

Understanding of NLP concepts and techniques would be a plus.

Passion for AI and ML technologies, with a history of exploring new concepts and technique.

ANNOTATION & LABELLING: Transcription, summarization, image and video classification and labeling.

ENHANCING LLMs: Prompt engineering, SFT, RLHF, red teaming and adversarial model training, model output ranking.

DATA COLLECTION & GENERATION: From institutional languages to remote field audio collection.

RELEVANCE & INTENT: Culturally nuanced and aware, ranking, relevance, and evaluation to train models for search, ads, and LLM output.

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