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Machine Learning Engineer
Hang · Remote, New York · Remote · Active · Ashby
Job facts
| Field | Value |
|---|---|
| Company | Hang |
| Title | Machine Learning Engineer |
| Normalized title | - |
| Department / team | Engineering / Engineering |
| Location | New York, NY, United States |
| Work model | Remote / Remote |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Ashby |
| Posted / first seen | — / 2026-05-29 |
| Changed / last seen | 2026-05-29 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Hang. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Ashby. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in New York. | Open |
| Department jobs | Active postings in Engineering. | Open |
| Work model jobs | Active Remote postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Hang |
| Source | 16a59955-9b3b-42b9-878d-4320be0d01ae |
| ATS provider | Ashby |
Description
Hang is building the future of loyalty for brands. Hang is the next generation brand loyalty & membership platform. By harnessing the power of personalization, gamification, and its integrations ecosystem, Hang provides brands with a radically new type of loyalty experience for their customers.
Today, they work with a variety of major brands (such as Ulta Beauty, Budweiser, Flipkart, and more), as well as multiple well-known, up-and-coming restaurant chains (Boba Guys, Roam Artisan Burger, and Williamsburg Pizza, among several others).
Hang draws from years of deep expertise in loyalty, game design, and finance with employees from leading companies like Google, Amazon, Apple, Meta, LinkedIn, Coinbase, Square, and Goldman Sachs.
Hang raised a $16 million Series A led by Paradigm last summer, with participation from Tiger Global, Howard Schultz, Kevin Durant, Mr. Beast, and the founders of Warby Parker, Allbirds, and Bombas, among others.
About the Role We are seeking a skilled and innovative Machine Learning Engineer to join our team. This person will implement and develop machine learning models to enhance our platform's capabilities, making key contributions to our product development, and driving data-driven decision-making.
What You’ll Do Model Development: Design, build, and deploy machine learning models to improve various aspects of our platform, including customer personalization, predictive analytics, and automated decision-making.
Data Analysis: Analyze large datasets to identify trends and patterns, and use this information to inform model development and business strategies.
Algorithm Optimization: Continuously test and refine algorithms to improve accuracy and efficiency.
Collaborative Development: Work closely with software engineers, data scientists, and product managers to integrate ML models into our platform and ensure seamless deployment.
Research and Innovation: Stay up-to-date with the latest developments in machine learning and AI, and explore new techniques and technologies that could benefit Hang.
Technical Leadership: Provide insights and guidance on best practices in machine learning, and contribute to the strategic direction of our technology.
Who You Are Bachelor's or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. A Ph.D. is a plus.
5+ years of experience in machine learning and data related roles.
Proven experience as a Machine Learning Engineer or in a similar role.
Strong programming skills in Python and familiarity with ML frameworks (like TensorFlow or PyTorch).
Experience with data processing and data analytics.
Experience with vector databases, demonstrating proficiency in managing and querying high-dimensional data. Familiarity with popular vector databases like Redis, Milvus, Pinecone, Weaviate, Chroma or Faiss is required.
Knowledge of machine learning techniques and algorithms, including fine tuning processes and methodology.
Experience in deploying Large Language Models (LLMs) in production environments, including optimization and scaling considerations.
Experience with snowflake, Postgres, RDS, Redis and AWS.
Excellent problem-solving skills and ability to work in a fast-paced environment.
Strong communication skills and ability to work well in a team.
Experience with Ruby is a plus.
What Would Set You Apart You have a passion for consumer brands and loyalty programs.
Benefits Top-tier health, vision, and dental insurance, including plans with $0 employee cost.
Unlimited PTO / sick leave
Competitive salary & equity compensation.
Quarterly company offsites
Full job record
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| Source ID | 16a59955-9b3b-42b9-878d-4320be0d01ae |
| Board ID | 16a59955-9b3b-42b9-878d-4320be0d01ae |
| Provider | ashby |
| Provider Job Key | 7b899a89-ed68-4988-8c3b-27ee46d6eca3 |
| Title | Machine Learning Engineer |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | Remote, New York |
| Department | Engineering |
| Team | Engineering |
| Employment Type | full_time |
| Workplace Type | remote |
| Remote Policy | remote |
| Country | United States |
| Region | NY |
| City | New York |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://jobs.ashbyhq.com/Hang/7b899a89-ed68-4988-8c3b-27ee46d6eca3 |
| Apply URL | https://jobs.ashbyhq.com/Hang/7b899a89-ed68-4988-8c3b-27ee46d6eca3/application |
| First Seen At | 2026-05-29 05:11:37Z |
| Last Seen At | 2026-06-06 19:25:06Z |
| Last Checked At | 2026-06-06 19:25:06Z |
| Last Changed At | 2026-05-29 05:11:37Z |
| Inactive At | — |
| Source Posted At | — |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=ashby/board=Hang/date=2026-06-06/2026-06-06T19-25-05-226Z-80c25057feccc328f9ff0b58f641accb75c31474e8c017fccb2a6afacb1effb8.json |
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