Senior Staff Machine Learning Engineer
- Published on
About the Role
Harnham is seeking a Senior Staff / Technical Lead Machine Learning Engineer to join their rapidly growing team. You will design, build, and deploy end-to-end machine learning models focusing on ad optimization and recommendation systems. This role leverages one of the largest consented behavioral datasets in the US to deliver AI solutions for top global brands.
Key Responsibilities
- Design, build, and deploy machine learning models for ad optimization and personalization use cases.
- Develop ML pipelines and production systems utilizing behavioral signals to enhance user value and business ROI.
- Partner with product and R&D teams to implement impactful ML-first product strategies.
- Lead experimentation and evaluate models in a dynamic, data-rich environment.
- Contribute to scalable infrastructure development using tools like Airflow, Spark, and CI/CD platforms.
- Work cross-functionally to launch innovative ML products and continuously refine them after launch.
- Stay current with emerging ML techniques in recommendation systems and behavioral modeling.
About the Candidate
Candidates should hold an MSc or PhD in a STEM field and have proven experience in building and deploying machine learning systems commercially. A strong background in AdTech or recommender systems is essential, with familiarity in user intent modeling and targeting. Hands-on experience with orchestration tools such as Airflow, Bazel, and data infrastructure tools like Spark, SQL, Scala, and Python is required. Additionally, candidates should possess DevOps knowledge, particularly CI/CD best practices and production monitoring.
Employment and Benefits
The position offers a competitive salary between $300,000 and $350,000 with meaningful equity and financial upside. Harnham promotes a fully remote work environment with hybrid options available in Boston, SF Bay Area, Seattle, and NYC.
Other benefits include strong collaboration opportunities, a product-oriented workplace, and a dynamic startup culture that encourages a bias toward action and cooperation.
How to Apply
Please apply by submitting your CV through the provided link.