About the role
What will you do at Dorsia?
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.
Which skills does this role require?
Make your next move
Build a shortlist and prepare
Identify the requirements you can demonstrate, then choose examples from your work to discuss with the hiring team.
- Build a focused shortlist before you applyCompare role requirements with your experience and give each application a clear reason.
- Machine learning jobsCompare current openings and review what to look for in this role.
- Practice explaining your experience in an interviewRehearse your answers before meeting the hiring team.
Other roles to compare
Review the responsibilities and requirements before adding an opening to your shortlist.
Staff AI Engineer - Personalization, Brand, Communications Tech
American Express · New York, New York, United States
Sr. Applied AI Engineer
phData · United States
AI Engineer 5 (AI Foundations: LLM Customization, Finetuning, Reinforcement Learning)
Capital One · San Jose, California, United States
Senior AI Engineer
Blue Orange Digital · Washington, District of Columbia, United States
Gen AI Engineer -Dallas, TX
Photon · Dallas, Texas, United States
AI Engineer
CCC Intelligent Solutions · Chicago, Illinois, United States
Role information can change. Confirm current details on the original application page.
