This role is for someone who can take machine learning out of the lab and make it bulletproof in production. You’ll build the infrastructure and systems that power discovery, personalization, pricing, inventory optimization, and fraud prevention for millions of fans using SeatGeek.
About SeatGeek
SeatGeek builds technology that modernizes ticketing for fans, venues, and performers. Their ML engineering work sits at the intersection of research and real-world product, translating models into scalable, reliable systems that drive business impact across the marketplace.
Schedule
Remote (United States)
Compensation: $145,000–$209,000 USD (equity eligible; total package varies by experience and location)
What You’ll Do
- Design, build, and deploy machine learning models and systems that operate reliably at production scale
- Build and maintain ML infrastructure like feature stores, model serving platforms, and real-time inference pipelines
- Partner closely with data scientists, product managers, and engineers to turn research into production-ready systems
- Solve technical challenges tied to real-time pricing optimization, demand forecasting, personalization, and fraud detection
- Build automated pipelines for training, validation, deployment, and monitoring using MLOps best practices
- Evangelize ML capabilities across teams and embed them into core product offerings
What You Need
- Experience building and deploying ML systems in production, including scale, business impact, and reliability considerations
- 4+ years of software engineering experience, with 2+ years focused on ML systems and MLOps
- Strong Python skills and experience with ML frameworks like scikit-learn, TensorFlow, PyTorch, or similar
- Experience with cloud platforms and containerization technologies
- Understanding of batch and real-time ML systems, including model serving, A/B testing, and performance monitoring
- Strong software craftsmanship and product mindset that goes beyond model accuracy
- Collaborative approach, including mentoring and working cross-functionally
Benefits
- Equity stake
- Flexible work environment (remote or optional in-office days)
- Work-from-home stipend
- Unlimited PTO
- Up to 16 weeks fully paid family leave
- 401(k) matching and student loan matching program
- Health, vision, dental, and life insurance
- Up to $25k toward family building, reproductive health services, and gender-affirming care
- $500/year wellness expenses
- Subscriptions to Headspace, Headspace Care, and One Medical
- $120/month for tickets to live events
- Annual subscription to Spotify, Apple Music, or Amazon Music
If you’ve built ML systems that stay standing in the real world, and you’re ready to own both the models and the machinery that keeps them alive, this is the one.
Build it fast. Build it clean. Build it so it doesn’t break at showtime.
Happy Hunting,
~Two Chicks…