Senior Staff Machine Learning Engineer

HarnhamAlameda, US
Published on

About the Role

Harnham is seeking a Senior Staff/Technical Lead Machine Learning Engineer who will play a critical role in leading a team. This position is at a fast-growing tech company specializing in behavioral modeling and personalization. The successful candidate will design, build, and deploy end-to-end machine learning models focused on ad optimization and recommendation systems.

Key Responsibilities

  • Design, build, and deploy end-to-end machine learning models focused on ad optimization and personalization use cases.
  • 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 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 updated on emerging ML techniques in RecSys, behavioral modeling, and model optimization.

About the Candidate

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, 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 proactive, action-oriented mentality suitable for a dynamic startup environment.

Salary and Benefits

  • Base salary of $300,000 – $350,000
  • 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.