Senior Machine Learning Engineer

About Arena Club 

If you’re fascinated by sports cards and memorabilia, your search ends here. Arena Club is pioneering the collectibles domain by introducing the first-ever digital card show. Spearheaded by 5x World Series Champion Derek Jeter and serial entrepreneur Brian Lee, Arena Club has developed a fully digital marketplace. This innovative platform is built on trust, transparency, and fun, featuring grading & authentication, vaulting, and digital pack openings for collectors to build and showcase their collections in a personalized online showroom from anywhere in the world. 

 

About The Role

As a key member of the team, you will bridge complex computer vision modeling with scalable engineering systems, owning the full lifecycle from data ingestion and model development through deployment, monitoring, and iteration. You will work cross-functionally to translate business and operational requirements into robust ML-driven solutions that directly impact grading accuracy, product experience, and marketplace efficiency.

 

What You Will Do

Computer Vision for Card Grading

• Design, train, and deploy computer vision models to detect trading cards, identify defects and imperfections, and handle complex visual challenges such as noisy backgrounds, lighting variability, and border sensitivity.
• Work extensively with object detection architectures such as YOLO (or similar frameworks like Detectron) for bounding box detection and classification tasks.
• Leverage OpenCV or equivalent libraries for cropping, edge detection, pixel-based operations, and image preprocessing.
• Continuously evaluate and improve grading model performance in real-world production environments.

Full-Lifecycle ML Ownership

• Own the end-to-end ML lifecycle: data ingestion, feature engineering, model training, evaluation, deployment, monitoring, and iteration.
• Integrate models directly into production systems rather than handing off to separate engineering teams.
• Maintain and improve model reliability, observability, and performance over time.

Data & Pipeline Engineering

• Build and maintain batch and near-real-time data pipelines using Python and PySpark.
• Write complex, production-grade SQL queries (including joins, aggregations, and time-window logic) to extract and transform data independently.
• Develop and operate ML pipelines running on AWS EC2 infrastructure.
• Improve reproducibility, experiment tracking, and data workflows across the ML stack.

Scalable Infrastructure & Systems

• Deploy and operate ML workloads on AWS (primarily EC2, S3, and related services).
• Design scalable systems for model inference and pipeline execution.
• Contribute to infrastructure decisions as the ML platform evolves (orchestration tools such as Airflow are a plus but not required).

Cross-Functional Partnership

• Collaborate closely with Product, Engineering, Data, and Operations teams to translate high-level business needs into clear technical problem statements.
• Communicate technical trade-offs, model behavior, and timelines in plain language to non-technical stakeholders.
• Operate effectively in an ambiguous, fast-moving environment with high ownership and autonomy.

AI-Accelerated Development

• Leverage AI tools and agents throughout the ML development lifecycle for code scaffolding, debugging, experiment design, and optimization.
• Integrate modern AI-assisted workflows to increase iteration speed and system robustness.

 

Qualifications

• Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related technical field required; Master’s degree preferred. 
• 7+ years of experience in machine learning engineering, with a proven track record of shipping models to production in a consumer-facing environment. 
• 3+ years of experience with Computer Vision.
• Expert-level proficiency in Python and its machine learning ecosystem (e.g., Scikit-learn, PyTorch, TensorFlow).
• Advanced SQL skills for complex data extraction and processing.
• Strong experience with AWS (specifically SageMaker, S3, and Lambda) for model hosting and data workflows.
• Solid experience with core ML algorithms, including Gradient Boosting, Neural Networks, and recommendation systems.
• Knowledge and experience with OpenCV & MLFlow

 

The Arena Club Standard

Life at Arena Club isn’t for the faint of heart — and that’s by design. We’re building products and experiences the collectibles world has never seen. This is a proving ground. It demands your best every single day, because anything less means you’re falling behind.

From day one, you’re in the game. Trusted to deliver, expected to own outcomes, and driven to raise the bar higher than you thought possible. We don’t just execute — we innovate, compete, and win together. 

If you want routine or predictability, you won’t find it here. But if you’re ambitious, relentless, and hungry to prove yourself on a team built to dominate — step into the arena. You’ll discover growth and reward here, unlike anywhere else.