Applied AI / Machine Learning Engineer
About the Role
We are looking for an early Applied AI/ML hire to help build the intelligence layer behind our AI-powered marketplace. This is a highly hands-on role for someone who enjoys solving ambiguous problems through software, machine learning, experimentation, and modern AI tooling.
The ideal candidate is someone who can move fluidly between engineering and data science — building production systems, developing models, experimenting with new AI capabilities, and translating business problems into measurable technical solutions.
This person will have ownership across the full lifecycle of AI/ML initiatives: understanding the problem, designing the solution, building prototypes, developing production systems, measuring impact, and iterating.
This is not a pure research role and not a pure analytics role. We are looking for someone who loves building.
What You'll Do
- Build and deploy AI/ML solutions that directly improve marketplace outcomes including recommendations, search, ranking, pricing, forecasting, inventory decisions, and operational efficiency.
- Develop production-quality machine learning systems using Python and modern ML/AI tooling.
- Design AI-powered applications using large language models, retrieval-augmented generation (RAG), agent frameworks, embeddings, and evaluation techniques.
- Translate ambiguous business challenges into technical solutions, identifying where AI, machine learning, automation, or optimization can create measurable value.
- Build data pipelines, feature engineering workflows, model evaluation frameworks, and decision systems that support production ML applications.
- Experiment rapidly with emerging AI technologies and determine how they can create business value.
- Develop offline evaluation strategies and measurement frameworks to understand whether models and AI systems are improving outcomes.
- Partner closely with engineering, product, operations, and business teams to bring ideas from concept through production.
- Own projects end-to-end, from architecture decisions and technical implementation through monitoring and continuous improvement.
What We're Looking For
Must Have
- 3+ years building software, machine learning systems, or AI-powered products in a professional environment.
- Strong Python development experience.
- Experience taking technical solutions from prototype into production.
- Comfortable operating in an early-stage environment where priorities are ambiguous and ownership is high.
Strong understanding of machine learning fundamentals including:
- supervised learning
- feature engineering
- model evaluation
- predictive modeling
- experimentation
Experience building with modern AI technologies including:
- large language models
- RAG systems
- embeddings/vector databases
- AI agents/workflows
- prompt engineering
- model evaluation
Along with:
- Strong SQL skills and experience working with modern data platforms.
- Ability to independently explore new technologies and quickly turn ideas into working prototypes.
Strong software engineering fundamentals:
- APIs
- data pipelines
- cloud infrastructure
- testing
- deployment practices
Strong Plus
- Experience with marketplace, ecommerce, search, recommendations, ranking, pricing, logistics, or supply chain problems.
- Experience building recommendation systems or ranking models.
- Experience with forecasting, optimization, personalization, or pricing models.
- Experience with causal inference, experimentation, or A/B testing.
- Experience with ML production systems, MLOps, monitoring, and model lifecycle management.
Experience with tools such as:
- PyTorch
- TensorFlow
- scikit-learn
- XGBoost
- MLflow
- LangChain
- LangGraph
- vector databases
- cloud AI platforms
