Staff Machine Learning Engineer

job
  • Harnham
Job Summary
Location
New York ,NY 10261
Job Type
Contract
Visa
Any Valid Visa
Salary
PayRate
Qualification
BCA
Experience
2Years - 10Years
Posted
15 Mar 2025
Share
Job Description

Connecting Top AI and Machine Learning Talent @ Harnham NYC

Staff Machine Learning Engineer (AdTech Focused)

Hybrid (4 days a week in NYC) or Remote

$220,000-$240,000 USD/yr + bonus

Our client is a cutting-edge technology company creating machine learning models to optimize all aspects of the advertising process. They specialize in automating and enhancing ad performance through AI-driven solutions, breaking down traditional marketing silos, and integrating creative, media, and performance strategies to drive measurable business growth. They are rapidly scaling their technology team to revolutionize space and become an industry leader. They want to add senior engineers to their team to tackle complex business problems and mentor junior engineers.

THE ROLE

As a Staff Machine Learning Engineer, you will fully own end-to-end machine learning model development, focusing on one model at a time while collaborating with domain experts, engineers, and business stakeholders. Your work will directly impact advertising performance, optimizing campaigns through cutting-edge ML solutions.

Key Responsibilities:

  • Develop, deploy, and maintain production-level machine learning models that are used by real customers at scale.
  • Work closely with domain experts and engineering teams to integrate ML solutions into a high-performance adtech platform.
  • Lead technical projects throughout the team and mentor junior engineers.
  • Implement models in a cloud environment (AWS, GCP, or Azure) with flexible infrastructure considerations.
  • Fine-tune large language models (LLMs), diffusion models, and other advanced techniques to optimize ad performance.
  • Contribute to ad hoc projects that drive innovation in ad optimization and personalization.
  • Monitor and continuously improve deployed models to maintain accuracy, scalability, and efficiency.

YOUR SKILLS AND EXPERIENCE

  • Strong track record of developing and deploying ML models that have been used by real users.
  • Proficiency in Python (TensorFlow, PyTorch) with hands-on experience in ML model development and deployment.
  • Experience working in AdTech or related fields where optimizing advertising performance through ML is a key focus.
  • Ability to manage multiple domain knowledge experts and drive cross-functional collaboration.
  • Strong problem-solving skills with a laser focus on execution and impact.
  • Comfortable with minimal hand-holding; thrives in a fast-paced, technology-driven environment.
  • Experience at best-in-class ML organizations (e.g., Affirm, Nubank, FAANG, or leading ML-focused companies in their respective industries).
  • Open to candidates from diverse educational backgrounds (BS/MS/PhD) as long as they have built ML systems at scale.
  • Preference for candidates with stable work histories.
  • Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) is a plus but not mandatory.

WHY JOIN?

  • Work at the intersection of machine learning and AdTech, building models that directly impact major advertising campaigns and are used by real customers.
  • Collaborate with a highly skilled, tech-forward team of ML engineers, data scientists, and software developers.
  • Opportunity to work on cutting-edge projects involving LLMs, diffusion models, and real-time ad optimization.
  • Competitive salary, performance-based bonuses, and potential relocation support.
  • Join a company that is reshaping the advertising and marketing landscape through AI-driven automation.

HOW TO APPLY

If you have built ML models that have been used at scale and want to shape the future of AdTech, we encourage you to reach out. Let's chat!

Register your interest by submitting your resume to Virginia via the Apply link on this page.

#J-18808-Ljbffr
Other Smiliar Jobs
 
  • New York, NY
  • 4 Days ago
  • New York, NY
  • 4 Days ago
  • New York, NY
  • 4 Days ago
  • Atlanta, GA
  • 4 Days ago
  • Atlanta, GA
  • 4 Days ago
  • New York, NY
  • 4 Days ago
  • New York, NY
  • 4 Days ago
  • New York, NY
  • 4 Days ago
  • Houston, TX
  • 4 Days ago
  • Tampa, FL
  • 4 Days ago
  • Charlotte, NC
  • 4 Days ago
  • Atlanta, GA
  • 4 Days ago
  • Houston, TX
  • 4 Days ago
  • New York, NY
  • 4 Days ago
  • San Francisco, CA
  • 4 Days ago