Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Machine Learning
New York, NY, United States
Live, first seen by us 63 days ago- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDesign and implement LLM-driven features in production systems
Build and maintain data pipelines for structured and unstructured data
Create evaluation suites, define success metrics, and analyze failures
Diagnose and mitigate hallucination, latency, and cost issues
Implement monitoring, logging, and alerting for AI services
From the employer’s posting
Design and implement LLM‑driven features in production systems.
Build and maintain data pipelines for both structured and unstructured data.
Create evaluation suites, define success metrics, and analyze failures.
Diagnose and mitigate hallucination, latency, and cost issues.
Implement monitoring, logging, and alerting for AI services.
What you’ll bring
All qualificationsCore experience
- Strong Python programming with tested, maintainable code
- Hands-on experience building with LLM tools or frameworks
- Experience evaluating LLM-powered applications with test sets and metrics
- Bachelor's degree in a quantitative field or equivalent practical experience
- Experience contributing to production or production-like software
Qualification wording
Strong programming ability in Python with clear, tested, and maintainable code.
Hands‑on experience building with LLM tools or frameworks (prompting, structured outputs, tool‑calling, retrieval, multi‑step workflows)
Experience evaluating LLM‑powered applications: building test sets, reviewing failures, defining metrics, and iterating on prompts or retrieval.
Bachelor’s degree in computer science, machine learning, mathematics, physics, statistics, econometrics, or equivalent practical experience.
Experience contributing to production or production‑like software through work, internships, research, open source, or substantial personal projects.
Education & alternatives
- Document designs, experiments, and findings for internal knowledge sharing. - Bachelor’s degree in computer science, machine learning, mathematics, physics, statistics, econometrics, or equivalent practical experience. - Experience contributing to production or production‑like software through work, internships, research, open source, or substantial personal projects.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 2, 202663 days ago
- Recorded sightings
- 248
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 63
Similar jobs usually come down between day 6 and day 69.
At Newmark Group, jobs usually come down by about day 35.
From 4,418 similar postings that came down, and 18 of Newmark Group’s. Coming down is not always a hire.
Newmark Group is hiring
6 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
Where the posting names them
- Build and maintain data pipelines for both structured and unstructured data. - Write clean, testable Python code and maintain reusable libraries. - Develop prompts, tool‑calling workflows, and retrieval pipelines.
- Experience contributing to production or production‑like software through work, internships, research, open source, or substantial personal projects. - Strong programming ability in Python with clear, tested, and maintainable code. - Experience with web services, data integrations, testing, logging, and basic monitoring across diverse data types.
Your next step
Complete your application on hdow.fa.us6.oraclecloud.com. The employer’s form will show what is required.
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About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Join Cantor Fitzgerald Technology Markets LLC as a Machine Learning Engineer focused on building AI‑driven solutions for a high‑volume financial services business. You will work closely with product, engineering, and business teams to create, test, and operationalize large language model (LLM) applications, ensuring they meet performance, reliability, and responsible‑AI standards.
- Design and implement LLM‑driven features in production systems.
- Build and maintain data pipelines for both structured and unstructured data.
- Write clean, testable Python code and maintain reusable libraries.
- Develop prompts, tool‑calling workflows, and retrieval pipelines.
- Create evaluation suites, define success metrics, and analyze failures.
- Diagnose and mitigate hallucination, latency, and cost issues.
- Collaborate with product, engineering, and business stakeholders.
- Implement monitoring, logging, and alerting for AI services.
- Contribute to responsible‑AI guardrails and human‑in‑the‑loop processes.
- Document designs, experiments, and findings for internal knowledge sharing.
- Bachelor’s degree in computer science, machine learning, mathematics, physics, statistics, econometrics, or equivalent practical experience.
- Experience contributing to production or production‑like software through work, internships, research, open source, or substantial personal projects.
- Strong programming ability in Python with clear, tested, and maintainable code.
- Experience with web services, data integrations, testing, logging, and basic monitoring across diverse data types.
- Hands‑on experience building with LLM tools or frameworks (prompting, structured outputs, tool‑calling, retrieval, multi‑step workflows) and awareness of common failure modes.
- Experience evaluating LLM‑powered applications: building test sets, reviewing failures, defining metrics, and iterating on prompts or retrieval.
- Solid grounding in machine learning, statistics, and experimental design with ability to interpret technical papers and documentation.
- Strong communication skills and comfort working with product, engineering, and business partners.
- Interest in applying AI responsibly in financial services, including privacy, security, human review, and appropriate automation.
- Familiarity with cloud deployment, containers, and modern release pipelines.
$140,000 - $160,000
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
New York, NY, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.