Machine Learning Engineer
Position Overview
Dorsia is seeking a talented Machine Learning Engineer to join our growing team. This role is pivotal in developing intelligent systems that enhance core product features, personalization, and operational efficiency. You will work across the full ML lifecycle, from data pipelines and model training to inference infrastructure and product integration. This is a hands-on, full-stack ML position with a direct impact on how members discover experiences, how restaurants manage demand, and how the business scales.
Why Dorsia
Dorsia is a leader in hospitality tech innovation, revolutionizing the dining experience through cutting-edge technology for exclusive reservations and VIP experiences. Join us as we expand and reshape the hospitality industry.
Responsibilities
- Build ML-Powered Features: Train and deploy models for search, ranking, recommendations, pricing, fraud detection, demand prediction, and more.
- Work Across the ML Lifecycle: Own projects end-to-end, including data sourcing, feature engineering, model deployment, and monitoring.
- Deploy at Scale: Build real-time inference pipelines and batch workflows using modern cloud-native infrastructure.
- Use AI to Ship Faster: Leverage generative AI and LLMs to accelerate development, enhance internal tooling, and improve user experiences.
- Collaborate Across Functions: Partner closely with product, design, and operations teams to deliver impactful ML features.
Requirements
Must-Haves
- 5–10 years of experience in software or ML engineering.
- Proven experience building, shipping, and scaling ML models in production (e.g., NLP, ranking, classification).
- Strong programming skills in Python and SQL, with a solid understanding of software and data engineering best practices.
- Familiarity with ML tooling (PyTorch, TensorFlow, scikit-learn), orchestration (Airflow, dbt), and deployment.
- Experience with cloud services (AWS, GCP, or similar).
- Ability to reason about data and metrics, with a drive to connect models to business outcomes.
Nice-to-Haves
- Experience with recommender systems, reinforcement learning, graph-based models, marketplace dynamics, or pricing systems.
- Understanding of retrieval systems, embeddings, or vector search.
- Experience in luxury, hospitality, or marketplace products.
- Familiarity with feature stores and observability tools.
- Startup mindset: high agency, comfort with ambiguity, bias to ship.
Tech Stack Snapshot
- Languages: Python, TypeScript, PHP
- Modeling & ML: PyTorch, Hugging Face, scikit-learn, LangChain
- Data: dbt, PostgreSQL, Redis, Airflow, Metabase
- Infra: AWS, Cloudflare, Vercel, Terraform, GitHub Actions
Compensation & Benefits
- Salary: New York Pay Range: $100,000 - $200,000 USD. Compensation is commensurate with experience and determined by skills, experience, location, and internal equity.
- Benefits:
- Flexible PTO
- Medical, dental, and vision insurance
- FSA
- Commuter benefits
- Free membership to One Medical
- Teladoc
- Talkspace
- Kindbody
- 401(k)
- In-office lunch 3 days a week
- Employee Dining Credits
Our Core Values
- Lead with hospitality: Respecting the craft and precision of the hospitality industry, fostering a diverse team to connect artists, chefs, diners, and members.
- Mise en place: Persistent preparation, prioritization, and focus to anticipate customer needs, creating a simple and elegant platform. Valuing thoughtful design in all aspects of the brand.
- Go around the table—then commit: Embracing feedback and iteration to foster creativity.