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Overnight Machine Learning Testing Jobs (NOW HIRING)

We are looking for a Machine Learning Engineer to design, build, and deploy machine learning ... Solid software engineering fundamentals (architecture, Git workflows, testing, code review)

CI/CD pipelines and regression testing โ€ข AI/ML expertise: Machine learning fundamentals; Deep knowledge of state-of-the-art in any of the following: computer vision (preferred), natural language ...

Python Developer

Pittsburgh, PA ยท On-site

$48.75 - $67.25/hr

Data Analysis/Machine Learning. * Testing/Debugging/Security. * Writing, testing, and debugging Python code for various applications. * Developing server-side logic, back-end components, and APIs.

The role involves developing and optimizing machine learning models, managing large-scale datasets ... Develop efficient workflows for training, validation, and testing, incorporating distributed ...

CI/CD pipelines and regression testing. * AI/ML expertise: Machine learning fundamentals; Deep knowledge of state-of-the-art in any of the following: computer vision (preferred), natural language ...

REMOTE Machine Learning Engineer This project-based consulting role invites an experienced Machine ... Hands-on experience with A/B testing, experimentation design, and causal inference approaches.

Engineer, Machine Learning

Arlington, VA ยท On-site

$157K - $185K/yr

Continuously push the practice forward, learning and testing newer and better ways of performing work. Qualifications Required experience * 5 years of machine learning engineering, software ...

A/B Testing and Experimentation : Design and conduct A/B tests to assess the performance of different machine learning models. This includes setting up the test environment, monitoring performance ...

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$31.5K

$128.8K

$193.5K

How much do overnight machine learning testing jobs pay per year?

As of Sep 8, 2026, the average yearly pay for overnight machine learning testing in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

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Machine Learning

Manhattan, NY โ€ข On-site

Full-time

This job post hasย expired today.ย Applications are no longer accepted.


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.
Responsibilities
  • 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.

Qualifications
  • 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