About the role

What will you do at Fetch?

About the Role

We are seeking a Machine Learning Software Engineer to join Fetch’s Ads Platform

team. This role sits at the intersection of applied machine learning, data

engineering, and production systems, with a focus on building and improving

ranking, relevance, and optimization models that drive ad selection and delivery

at scale. You will partner closely with product, data, and platform teams to

develop ML-driven decisioning systems, including feature pipelines, model

training and evaluation workflows, and low-latency serving infrastructure. This

is a high-impact opportunity to influence how ads are ranked and personalized

across the Fetch experience, improving advertiser performance, user engagement,

and overall marketplace efficiency.

Role

Responsibilities

* Design, build, and improve machine learning models that power ad ranking,
relevance, and optimization across the Fetch platform.
* Implement and iterate on active learning strategies, including data sampling,
error-driven retraining, and human-in-the-loop workflows to improve ranking
quality.
* Leverage LLMs to reduce model development and annotation effort, including
synthetic data generation, assisted labeling, weak supervision, and error
analysis for ranking and relevance tasks.
* Own ML experimentation, offline and online evaluation, and production
inference for assigned ad ranking components.
* Partner closely with product, data, and platform teams to translate
advertiser and user experience gaps into measurable ML improvements.
* Maintain high standards for model performance, reliability, latency, and data
quality in production ranking systems.
* Use AI-assisted tools to accelerate development, experimentation, debugging,
and analysis while maintaining strong engineering judgment.
* Designing features and validating ideas with ChatGPT & Claude sandboxes.
* Leveraging AI for code generation and technical prototyping.
* Using AI assistants for systems architecture diagramming and design
validation.
Minimum

Requirements

* 5+ years of software engineering experience with a strong track record of
building and maintaining production ML or data-driven systems.
* Strong proficiency in Python for machine learning and data processing, with
working knowledge of Go, and hands-on experience deploying low-latency models
into production ranking or decisioning systems.
* Experience with AWS and distributed systems, including building or operating
scalable training pipelines and online inference services.
* Practical experience applying LLMs to reduce model development and data
labeling effort, including assisted labeling, synthetic data generation, weak
supervision, or model error analysis.
* Strong engineering judgment and systems mindset, with an emphasis on
reliability, performance, and long-term maintainability of ranking or
optimization systems.
* Experience using AI-assisted development tools (e.g., GitHub Copilot,
ChatGPT, or similar) to accelerate iteration while maintaining high code
quality.
* Ability to critically evaluate AI-generated outputs, debug complex issues,
and validate correctness in production ML workflows.
Preferred

Requirements

* Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a
related field, or equivalent practical experience.
* Familiarity with modern AI tooling and frameworks such as AWS Bedrock,
LangChain, vector databases, or similar orchestration technologies used in
ML-powered decisioning systems.
* Experience building and operating machine learning workflows involving large
language models (LLMs), including prompt-driven systems and model-assisted
pipelines.
* Familiarity with orchestrating ML-driven decisions in high-throughput or
low-latency environments, such as ranking, recommendation, or optimization
systems.
* Experience with applied machine learning for relevance, ranking, or
personalization problems (e.g., feature engineering, model evaluation, or
feedback loops).
* Experience working in small, fast-moving, cross-functional teams, partnering
closely with product, data, and platform stakeholders.

Which skills does this role require?

PythonGoDistributed SystemsRanking SystemsData EngineeringInference ServicesSynthetic Data GenerationActive LearningLow-latency SystemsSoftware EngineeringPrompt EngineeringAds PlatformFeature PipelinesModel TrainingInferenceSynthetic DataHuman-in-the-loopGitHub CopilotChatGPTClaudeScalabilityMarketplace EfficiencyPrototypingA/B Testing

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