Machine Learning Engineer

Why Dorsia

Dorsia is at the forefront of hospitality tech innovation. We are revolutionizing the way people experience dining by leveraging cutting-edge technology to offer exclusive restaurant reservations and VIP experiences. Join us as we continue to expand our footprint and reshape the hospitality industry.

About the Role

We’re looking for a Machine Learning Engineer to join our growing team and own the development of intelligent systems that power core product features, personalization, and operational efficiency. You’ll work across the stack—from data pipelines and model training to inference infrastructure and product integration.

This is a hands-on, full-stack ML role with a direct line to impact—shaping how members discover experiences, how restaurants manage demand, and how our business scales.

What You’ll Do

• 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 from end-to-end, covering data sourcing and feature engineering to 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, boost internal tooling, and augment user experiences.
• Collaborate Across Functions
  Partner closely with product, design, and ops to ship delightful and impactful ML features.

What We’re Looking For

Must-Haves

• 5–10 years of experience in software or ML engineering
• Experience building,shipping and scaling ML models in production (NLP, ranking, classification, etc.)
• Strong programming skills in Python and SQL and a good understanding of best practices in software and data engineering
• 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—and a drive to tie models to real business outcomes
• 5 days a week in our SoHo NYC office

Nice-to-Haves

• Experience working on 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 ranges are based on paying competitively for our size and stage. We determine our pay by considering skills and experience related to the role, location, and ensuring internal equity relative to other Dorsia employees
• 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

Compensation is based on your experience and the scope of the role. Final compensation is based on factors like experience, location, and internal equity. This role also includes equity and a full suite of benefits. Typical base salary ranges are:

• Junior level: $100,000–$160,000

• Mid level: $150,000–$200,000

• Senior level: $190,000–$250,000