Senior Staff/Technical Lead Machine Learning Engineer
- Published on
About the Role
Harnham is seeking a Senior Staff/Technical Lead Machine Learning Engineer to join a mission-driven tech company focused on behavioral modeling and personalization. This role involves leading a team to build and deploy end-to-end machine learning models, particularly in areas like ad optimization and recommendation systems. Your responsibilities include:
- Designing, building, and deploying machine learning models.
- Developing ML pipelines that drive user value and business ROI.
- Collaborating with product and R&D teams to execute ML strategies.
- Conducting experimentation and model evaluation in a fast-paced environment.
- Contributing to scalable infrastructure with tools like Airflow, Spark, and CI/CD platforms.
About the Candidate
The ideal candidate should possess an MSc or PhD in a STEM field and have proven experience in deploying machine learning systems commercially. Key requirements include:
- A strong background in AdTech and recommender systems, with an understanding of personalization and targeting.
- Hands-on experience with orchestration tools (Airflow, Bazel) and data infrastructure (Spark, SQL, Scala, Python).
- Knowledge of CI/CD best practices and cloud platforms (AWS, Databricks).
- Excellent collaboration and communication skills, coupled with a proactive mindset and an ability to thrive in a dynamic startup environment.
About the Company
Harnham is a leading tech company that leverages one of the largest consented behavioral datasets in the US to deliver innovative AI solutions. Partnered with major cloud providers, Harnham aims to push the boundaries of AI, benefiting top global brands and platforms through sophisticated machine learning products.
Company Culture and Benefits
- Competitive base salary ranging from $300,000 to $350,000.
- Meaningful equity and financial upside.
- Fully remote position, with the option for hybrid arrangements in various locations including Seattle, Boston, SF Bay Area, and NYC.
How to Apply
If you feel you meet the criteria, please submit your CV via the Apply link provided.