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About the Role
We are seeking a Senior Machine Learning Engineer to lead the systems responsible for product surfacing, ranking, and discovery across Arena Club's marketplace, including search relevance, ranking, and personalization. This role involves production machine learning in the request path, directly impacting conversion, engagement, and revenue. The position covers the entire ML lifecycle from concept to deployment and continuous iteration, with a focus on rigorous experimentation and measurable business impact. This is a player-coach role, requiring direct model building, establishing methodological standards, and mentoring junior Data Scientists.
Responsibilities
- Design, train, and deploy recommendation and ranking models to enhance marketplace relevance and conversion.
- Own and improve a recommendation and search index to outperform third-party controls on conversion and reduce fallback rates.
- Build personalization ranking for homepages, onboarding flows, and category pages.
- Develop retrieval and candidate-generation systems utilizing embeddings and semantic search.
- Implement cross-domain feature reuse, such as item scores and tier weights, as ranking signals across various surfaces.
- Manage the complete ML lifecycle, including data ingestion, feature engineering, training, evaluation, deployment, monitoring, and iteration.
- Deploy and operate low-latency inference systems within the request path.
- Design scalable systems for model serving and pipeline execution.
- Build and maintain batch and near-real-time data pipelines using Python and PySpark.
- Deploy and operate ML workloads on AWS services (EC2, S3, etc.).
- Enhance reproducibility, experiment tracking, and observability across the ML stack.
- Collaborate with backend engineers to integrate models into customer-facing systems.
- Partner with Product, Engineering, and the marketplace squad to define technical problem statements from high-level requirements.
- Design and interpret A/B tests to validate model and product changes.
- Communicate model behavior, trade-offs, and timelines clearly to non-technical stakeholders.
- Utilize AI tools and agents for code scaffolding, debugging, and optimization throughout the ML lifecycle.
- Operate with a high degree of ownership and autonomy in a dynamic and ambiguous environment.
Requirements
- Bachelor's degree in Computer Science, Statistics, Mathematics, or a related quantitative field; advanced degree preferred.
- 5+ years of experience in applied Machine Learning or ML Engineering.
- Proven track record of shipping models to production in a consumer-facing environment.
- 3+ years of experience building recommendation, ranking, search relevance, or personalization systems.
- Expert-level proficiency in Python and the ML ecosystem (PyTorch, TensorFlow, Scikit-learn).
- Experience with learning-to-rank, embeddings, retrieval, and semantic search.
- Advanced SQL skills for complex data extraction and processing.
- Experience applying ML to user behavior data (clickstream, transactional, event logs).
- Strong AWS experience (EC2, S3, and related services) for model hosting and data workflows.
- Comfort with experimentation methodologies (A/B testing, lift measurement, business impact interpretation).
- Knowledge of MLFlow or an equivalent experiment-tracking and model-registry tool.
Skills
- Python
- PyTorch
- TensorFlow
- Scikit-learn
- SQL
- AWS (EC2, S3)
- MLFlow
- Learning-to-rank
- Embeddings
- Retrieval
- Semantic search
- User behavior data analysis
- Experimentation (A/B testing)
- PySpark
Location
- Remote
Work Type
- Full-time
Experience Level
- Senior
- 5+ years
- 3+ years
Education Level
- Bachelor's degree in Computer Science, Statistics, Mathematics, or a related quantitative field
- Advanced degree preferred
Salary/Compensations
- $170,000—$230,000 USD
Benefits
- Bonus
- Equity
About the Company
- Life at Arena Club is demanding and designed for building unprecedented products and experiences in the collectibles world. It requires peak performance daily, as falling behind is not an option. From the start, employees are trusted, expected to own outcomes, and driven to exceed expectations. The company emphasizes innovation, competition, and collective success to achieve breakthroughs. Routine and predictability are absent; instead, ambition, relentlessness, and a drive to dominate are valued. The company offers unique growth and reward opportunities for those who prove themselves on a high-performing team.