Offer summary

Qualifications:

Bachelor's degree in Computer Science, Engineering, Mathematics, or Statistics., At least 2 years of engineering experience, preferably in a client-facing role., Proficiency in Python, JavaScript, or similar languages for automation and scripting., Experience with APIs, data pipelines, cloud platforms (AWS, GCP, Azure), and data processing tools..

Key responsibilities:

Act as a technical partner between teams to ensure smooth collaboration.

Troubleshoot and optimize enterprise integrations for seamless data exchange.

Design and implement technical solutions to support customer and internal success.

Create self-serve tools and automate workflows to improve operational efficiency.

Job description

Welo Data works with technology companies to provide datasets that are highquality, 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 stateoftheart 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 selfserve 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.

What Youll 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 selfserve 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.
Strong problemsolving 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 selfdriven, 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 nontechnical 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 clientfacing setting.
Curiosity and desire to learn
Bachelors degree with an engineering or analytics focused field (e.g., Computer Science, Engineering, Mathematics, Statistics) or equivalent work experience.
Handson experience in ML lifecycle applications, data management, and data wrangling.
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.