Senior Machine Learning Engineer II

Meet Fetch AI & Data

AI & Data at Fetch sit at the center of how we understand our business, make decisions, and build intelligent products. The organization operates as an integrated AI & data ecosystem, spanning multiple disciplines, including data engineering, analytics engineering, machine learning, experimentation, and data platforms, all working together to turn data into durable business and customer impact.

Teams operate in complex problem spaces where requirements evolve, tradeoffs are constant, and the right answer is rarely obvious. Success depends on strong technical judgment, comfort with ambiguity, and the ability to gather context and make informed decisions while balancing quality, performance, scalability, and responsible use.

Practitioners across this org contribute hands-on to production systems, analytical foundations, and intelligent features. You will collaborate closely with product, platform, and engineering partners, help shape standards and best practices, and ensure our AI and data capabilities scale reliably as Fetch grows.

About the Role:

We are seeking a Senior Machine Learning Engineer II to join Fetch's Ad Ranking 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:

• 6+ 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.

This is a full-time role that can be held from one of our US offices or remotely in the United States.

Compensation: At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. The base salary range for this position is $211,353 - $248,650. Discover our benefits and how our employees live rewarded at .

At Fetch, we'll give you the tools to feel healthy, happy and secure through:

• Equity: We offer full-time employees equity in Fetch, so that everyone can benefit from Fetch's growth.
• 401k Match: Dollar-for-dollar match up to 4%.
• Benefits for humans and pets: We offer comprehensive medical, dental and vision plans for everyone including your pets.
• Continuing Education: Fetch provides ten thousand per year in education reimbursement.
• Employee Resource Groups: Take part in employee-led groups that are centered around fostering a diverse and inclusive workplace through events, dialogue and advocacy. The ERGs participate in our Inclusion Council with members of executive leadership.
• Paid Time Off: On top of our flexible PTO, Fetch observes 9 paid holidays, as well as our year-end week-long break.
• Robust Leave Policies: 20 weeks of paid parental leave for primary caregivers, 14 weeks for secondary caregivers, and a flexible return to work schedule.
• Calvin Care Cash: Employees who are welcoming new family members will also receive a one time $2,000 incentive to assist employees with covering the cost of childcare, clothing, diapers and much more!
• Flexible Work Environment: Collaborate with your team in one of our stunning offices, or you can work fully remotely from anywhere in the US. We'll ensure you are equally equipped with the hardware and software you need to get your job done in the comfort of your home. (applicable for most roles)

Fetch is an equal opportunity employer that embraces diversity, inclusion, and respect for all individuals. We do not discriminate on the basis of race, color, religion, gender, gender identity or expression, sexual orientation, age, national origin, marital status, veteran status, disability, or any other characteristic protected by applicable law. Our commitment to inclusivity ensures that everyone is treated with dignity and has the opportunity to succeed based on their talent, skills, and potential.

Fetch also provides reasonable accommodations to qualified individuals with disabilities or those with sincerely held religious beliefs, as required by law. If you need assistance with the application process or require an accommodation, please contact us at View email address on click.appcast.io.