5-10 years of experience in software or ML engineering
Proven track record in building, deploying, and scaling ML models in production, particularly in NLP and classification
Proficiency in Python and SQL, with a solid understanding of software and data engineering best practices
Familiarity with ML tools like PyTorch, TensorFlow, and orchestration tools such as Airflow
Experience using cloud services (AWS, GCP, etc.) and an intuitive grasp of data-driven business metrics
Responsibilities
Develop ML-powered features for search, recommendations, and demand prediction
Manage the entire ML lifecycle from data sourcing to model deployment
Create real-time inference pipelines and scalable batch workflows
Utilize generative AI and LLMs to enhance product development
Collaborate with product, design, and operations teams to deliver impactful ML solutions
Benefits
Flexible PTO to encourage work-life balance
Comprehensive medical, dental, and vision insurance
Access to a flexible spending account (FSA)
Commuter benefits to support your daily travel
Free membership to One Medical for convenient healthcare access
Teladoc and Talkspace for remote healthcare options
401(k) plan to support your long-term savings
In-office lunch provided 3 days a week
Employee dining credits for dining experiences
Full Job Description
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 FeaturesTrain and deploy models for search, ranking, recommendations, pricing, fraud detection, demand prediction, and more.
Work Across the ML LifecycleOwn 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 FasterLeverage generative AI and LLMs to accelerate development, boost internal tooling, and augment user experiences.
Collaborate Across FunctionsPartner 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
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:
