Role Description & Responsibilities
Machine Learning
About Pinterest
Pinterest is a high-growth technology leader building scalable solutions for global users. Millions of companies and teams rely on their infrastructure and services to execute high-value workflows, analyze massive datasets, and scale modern operations.
CadetX Candidate Advantage: As an applicant for this Machine Learning role, you are evaluated on practical proficiency with real-world query execution, data pipelines, and clear stakeholder communication.
CadetX Role Brief & Company Specifications
Role Mission & Impact
With more than 640 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers help build personalized experiences to help Pinners create a life they love. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.
By applying to this role, you will be considered for multiple roles open across our various ML teams. Please only apply once within the USA or Canada as multiple applications may delay our recruitment process.
Key Responsibilities & Day-to-Day Scope
- ✓ Contribute to cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems
- ✓ Collect, analyze, and synthesize findings from data and build intelligent data-driven model
- ✓ Write clean, efficient, and sustainable code
- ✓ Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across discovery, ads and search
- ✓ Design, build, and test models to predict engagement for notifications (push, emails, in-app notifications)
- ✓ Build content recommendation systems to power our push, email, and in-app notifications
- ✓ Work on state-of-the-art large-scale applied machine learning projects
- ✓ Scope and independently solve moderately complex problems
- ✓ Master's in Computer Science, ML, NLP, Statistics, Information Sciences or related field required
- ✓ Machine Learning experience (ranking, computer vision, NLP, content recommendations, embedding, information retrieval etc)
Official Qualifications & Technical Requirements
- • Experience with big data technologies (e.g., Hadoop/Spark) and scalable realtime systems that process stream data
- • Mastery of at least one systems languages (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow)
- • Proficiency with AI-native engineering, including the design of agent-friendly codebases.
- • High degree of autonomy in learning new agent-first development tools.
- • Strong critical thinking when working with AI-generated suggestions, with a clear approach to validating correctness, performance, security, and maintainability.
- • Comfort iterating on prompts, refining workflows, and adapting AI-assisted approaches based on the problem, context, and constraints.
- • Experience in research and in solving analytical problems
- • Strong communicator and team player. Being able to find solutions for open-ended problems.
- • We let the type of work you do guide the collaboration style. That means we’re not always working in an office, but we continue to gather for key moments of collaboration and connection
- • This role may require you to be located near an office for in-person collaboration, and therefore may need to be located a commutable distance from one of our Pinterest offices.
Preferred Skills & Technology Stack
- + Familiarity with MLOps pipelines (Docker, Kubernetes, Kubeflow, Triton Inference Server).
- + Knowledge of distributed training techniques and GPU acceleration (CUDA).
- + Relevant coursework, research publication, or open-source contribution in ML/DL.
Tech Stack & Tools in this role
Expected technical competencies for Day 1 productivity:
★ Life & Culture at Pinterest
Verified EmployerPinterest champions rigorous analytical discipline, continuous learning, and low-ego teamwork. Team members enjoy flexible hybrid allowances, learning stipends, and structured mentorship to fast-track career mobility.