Job description

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 Compensation: New York Pay Range $100,000 — $250,000 USD Workplace Philosophy at Dorsia At Dorsia, we believe that culture eats strategy. The best ideas in the world mean nothing without the right people around the table and the right chemistry between them. We are, unapologetically, a people-first organization. In-Person Matters We’re creating once-in-a-lifetime experiences for the most discerning audience in the world. That doesn’t happen over Zoom. It happens through collisions: a spark across a desk, a kitchen-side conversation that unlocks a partnership, the energy of ideas felt, not typed. That’s why in-office culture is non-negotiable at Dorsia. Who We Hire We don’t subscribe to check-the-box hiring. We hire for merit and mindset, which naturally creates a team with varied backgrounds. What unites us isn’t demographics, it’s a shared vision: to build the social operating system for the cultural vanguard. Lifestyle Hours We’re not a 9-to-5 company. Our lifestyle mirrors our members. Early flights, after-work events, and late-night sprints when the work demands it. But we love what we do, and we definitely love a good party. High Performance Culture Working at Dorsia isn’t for everyone—and that’s the point. Our culture is designed for builders, not passengers. We move fast, set ambitious standards, and expect people to rise to them. If you have the talent and the drive, this will be a ride to remember. A Final Word We’re building something special. It will take long hours and relentless effort. It’s not for everyone. For those with the metabolism, you’ll create something that changes how culture is lived. And that’s the kind of work worth your life’s energy.

Requirements

Must-haves

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
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

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmlaipythonsqlawsgcptypescript

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto