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# Machine Learning Engineer

- **Company:** Elomi Corporation
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $100,000.0 - $160,000.0
- **Contract:** Permanent contract
- **Skills:** PHP (Programming Language), Airflow, Amazon Web Services, Automated Storage and Retrieval Systems, Computer Programming, Information Engineering, Fraud Prevention and Detection, Github, Python (Programming Language), PostgreSQL, Machine Learning, Recommender Systems, Redis, Tensorflow, Next.js, Search Technologies, SQL Databases, TypeScript, Reinforcement Learning, Feature Engineering, Pytorch, Large Language Models, Grafana, Scikit Learn, HuggingFace, Cloudflare, Machine Learning Operations, Terraform
- **Published:** September 12, 2026
- **Apply:** https://startup.jobs/machine-learning-engineer-dorsia-6843160

## About the Role

* 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, * 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

## Description

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., 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., * 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


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