> Markdown version of [/jobs/ext/3960819-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/3960819-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# 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), Artificial Intelligence, Airflow, Amazon Web Services, Automated Storage and Retrieval Systems, Cloud Computing, Computer Programming, Information Engineering, Fraud Prevention and Detection, Github, Python (Programming Language), PostgreSQL, Machine Learning, Recommender Systems, Redis, Cloud Services, Tensorflow, Next.js, Search Technologies, SQL Databases, TypeScript, Reinforcement Learning, Feature Store, Feature Engineering, Pytorch, LangChain, Large Language Models, Grafana, Scikit Learn, HuggingFace, Cloudflare, Data Management, Machine Learning Operations, Terraform, Data Pipelines
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/machine-learning-engineer-new-york-ny--baff8b9e-1284-46de-8d44-8363ee4e051d

## About the Role

Machine Learning, Restaurant, Hospitality and Tourism, Leading Edge Technology, Machine Learning, Data Management, Data Modeling, Pricing, Search Ranking, Cloud Computing, * 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., * 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 ScaleBuild 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., * 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