Machine Learning Engineer
Harnham
New York · Posted October 29, 2026
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- Best cities for data and analytics pay after cost of living #1 Foster ($232k)
- Most requested AI skills in data and analytics jobs #1 Machine learning engineering (17.1%)
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Pay compared with the market
This listing does not state pay. Across 66 open machine learning engineer listings that state pay, the middle half runs $190,000 to $258,000 and the median is $210,000.
Listed pay is what employers advertise, not what people are paid.
Machine Learning Engineer salaries by state · Check your own pay
How AI is used in this kind of work
Among computer occupations, all other, AI is already used for a large share of the tasks. Measured exposure for computer occupations, all other: 31% (high).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
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About the job
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Machine Learning Engineer New York | Hybrid (4 days in office) $200k – $225k base + 20% bonus
A well-funded real estate business is investing heavily in AI and data to transform how strategic decisions are made across its portfolio. They’re hiring a Machine Learning Engineer to join a small, highly visible team building predictive analytics and AI-powered products used by investment and operational stakeholders.
This is an opportunity to work on business-critical systems where data and AI directly influence commercial decision-making.
What You’ll Do:
Build scalable data platforms, pipelines and ML infrastructure
Develop and deploy production AI solutions, including LLMs, RAG systems and AI agents
Partner closely with business stakeholders to solve complex problems
Drive architecture decisions and technical strategy
Own projects end-to-end from design through production
What We’re Looking For:
Experience in ML Engineering & Applied AI
Production experience building and deploying AI/ML systems
Strong knowledge of modern data technologies such as Databricks, Spark, Kafka, Airflow and Delta Lake
Excellent software engineering and distributed systems fundamentals
Comfortable operating in fast-moving, high-ownership environments
Ideal Backgrounds:
FinTech, investment management, asset management, hedge funds or other data-driven industries
Startup or scale-up environments
Data platform, infrastructure or applied AI teams
Why Join?
Greenfield AI initiatives
Small team with significant ownership
Direct exposure to senior decision-makers
Opportunity to shape products, architecture and strategy
Fast-moving environment where ideas quickly reach production
Interested in building AI products that drive real-world business decisions? Apply here!
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