Technical Lead Machine Learning Engineer
- Published on
About the Role
Harnham is seeking a Senior Staff/Technical Lead Machine Learning Engineer to join and lead a team in Santa Clara, CA. This individual will be integral to building and scaling machine learning-powered products focused on ad optimization and recommendation systems. The role includes designing, building, and deploying end-to-end machine learning models, developing ML pipelines, and collaborating across teams.
Responsibilities
- Design, build, and deploy end-to-end machine learning models focused on ad optimization and recommendation systems.
- Develop ML pipelines and production systems leveraging rich behavioral signals.
- Partner with product and R&D teams on high-impact, ML-first product strategies.
- Lead experimentation and model evaluation in a fast-paced, data-rich environment.
- Contribute to developing scalable infrastructure utilizing tools like Airflow, Spark, and CI/CD platforms.
About the Candidate
The ideal candidate should have:
- An MSc or PhD in a STEM field.
- Proven experience in building and deploying machine learning systems in a commercial setting.
- Strong knowledge in AdTech or recommendation systems, focusing on personalization and user intent modeling.
- Hands-on experience with orchestration tools (Airflow, Bazel) and data infrastructure (Spark, SQL, Scala, or Python).
- Familiarity with cloud platforms (AWS, Databricks) and ML tooling (MLFlow, TensorFlow, Kubernetes).
About the Company
Harnham is a fast-growing, mission-driven tech company specializing in behavioral modeling and personalization. They leverage one of the largest consented behavioral datasets in the US to deliver private-by-design AI solutions. The team is comprised of experienced ML professionals and partnered with significant cloud providers.
Salary and Benefits
- Salary range: $300,000 – $350,000 base
- Meaningful equity and financial upside
- Fully remote with hybrid options in Boston, SF Bay Area, Seattle, and NYC
How to Apply: Please register your interest by submitting your CV via the Apply link on this page.