Senior Staff Machine Learning Engineer

Harnham; San Francisco (CA); Remote; USD 300,000 - 350,000; Full time

Job summary

An innovative tech company is seeking a Senior Staff Machine Learning Engineer to lead a dynamic team focused on building AI solutions for top brands. This role involves designing and deploying machine learning models, particularly in ad optimization and recommendation systems. The company prides itself on leveraging one of the largest behavioral datasets in the US, offering a unique opportunity to work at the forefront of AI technology. With a collaborative culture and a commitment to personal growth, this position is perfect for those eager to make a significant impact in the field of machine learning.

Benefits

Meaningful Equity

Financial Upside

Fully Remote Work

Hybrid Options

Qualifications

• Proven experience building and deploying machine learning systems.
• Strong background in AdTech or recommender systems.
• Hands-on experience with orchestration tools and data infrastructure.

Responsibilities

• Design, build, and deploy end-to-end ML models for ad optimization.
• Develop ML pipelines leveraging behavioral signals.
• Lead experimentation and model evaluation in a data-rich environment.

Skills

Machine Learning Engineering

AdTech

Personalization

Recommender Systems

MLOps

CI/CD

Python

Education

MSc in STEM

PhD in STEM

Tools

Airflow

Spark

SQL

Scala

AWS

MLFlow

TensorFlow

Kubernetes

Job description

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This range is provided by Harnham. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$300,000.00/yr - $350,000.00/yr

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Building AI/ML & Data/Software Engineering Teams Across The US

Senior Staff Machine Learning Engineer

Remote

Up to $350,000 + Equity

Company:

A fast-growing, mission-driven tech company in the behavioral modeling and personalization space is seeking a Senior Staff/Technical Lead Machine Learning Engineer to join and lead a team. Their platform leverages one of the largest consented behavioral datasets in the US to deliver private-by-design AI solutions for top global brands and platforms.

The team is made up of seasoned ML professionals from Top Companies, and they are partnered with major cloud providers to bring novel AI products to market. This role will be central to building and scaling ML-powered products, with a focus on ad optimization and recommendation systems.

Role:

• Design, build, and deploy end-to-end machine learning models focused on ad optimization, personalization use cases and recommendation systems.
• Develop ML pipelines and production systems that leverage rich behavioral signals to drive user value and business ROI.
• Partner with product and R&D teams to ideate and execute on high-impact, ML-first product strategies.
• Lead experimentation and model evaluation in a fast-paced, data-rich environment.
• Contribute to the development of scalable infrastructure using tools like Airflow, Spark, and CI/CD platforms.
• Work cross-functionally to bring zero-to-one ML products to market and continuously refine them post-launch.
• Stay on the pulse of emerging ML techniques in RecSys, behavioral modeling, and model optimization.

Requirements:

• MSc or PhD in a STEM field.
• Proven experience building and deploying machine learning systems in a commercial setting.
• Strong background in AdTech or recommender systems (RecSys) – with a clear understanding of personalization, targeting, or user intent modeling.
• Hands-on experience with orchestration tools (Airflow, Bazel), data infrastructure (Spark, SQL, Scala, or Python).
• DevOps knowledge including CI/CD best practices and production model monitoring.
• Familiarity with cloud platforms (AWS, Databricks) and ML tooling (MLFlow, TensorFlow, Kubernetes).
• Strong collaboration and communication skills, with a product-oriented mindset.
• A bias toward action and a "roll up your sleeves" attitude—ideal for a dynamic startup environment.

Salary and Benefits:

• Meaningful Equity & Financial Upside
• Fully Remote (with hybrid options in Boston, SF Bay Area, Seattle, NYC)

How to Apply:

Please register your interest by submitting your CV via the Apply link on this page.

Desired Skills and Experience:

Machine Learning Engineering, AdTech, Personalization, Recommender Systems, MLOps, CI/CD, Airflow, Spark, Python, AWS

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Analyst

• Industries

  Software Development

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