Technical Lead Machine Learning Engineer
- Published on
About the Role
Harnham is seeking a Technical Lead Machine Learning Engineer to join their fast-growing company in the behavioral modeling and personalization space. This role will be central to building and scaling ML-powered products focused on ad optimization and recommendation systems. Key responsibilities include:
- Designing, building, and deploying end-to-end machine learning models.
- Developing ML pipelines and production systems that leverage rich behavioral signals.
- Partnering with product and R&D teams to ideate and execute on high-impact ML-first product strategies.
- Leading experimentation and model evaluation in a data-rich environment.
- Contributing to scalable infrastructure development using tools like Airflow and Spark.
About the Candidate
To be successful in this role, candidates should have:
- An MSc or PhD in a STEM field.
- Proven experience in building and deploying ML systems in a commercial setting.
- A strong background in AdTech or recommender systems with a clear understanding of personalization and targeting.
- Hands-on experience with tools such as Airflow, Spark, SQL, Scala, or Python.
- Knowledge of DevOps practices, including CI/CD and model monitoring.
- Familiarity with cloud platforms and ML tooling, such as AWS and TensorFlow.
- Excellent collaboration and communication skills, with a strong product-oriented mindset.
- A proactive approach with a “roll up your sleeves” attitude.
Company Overview
Harnham is a tech company with a mission-driven approach, aimed at providing private-by-design AI solutions for top brands using one of the largest consented behavioral datasets in the US. They are partnered with major cloud providers and have a team of seasoned ML professionals from top companies.
Company Culture and Benefits
Harnham offers a competitive salary range of $300,000 – $350,000, alongside meaningful equity and financial upside. The position allows for full remote work with options for hybrid setups in major US cities such as Boston, San Francisco, Seattle, and New York City.
How to Apply
Interested candidates are encouraged to apply by submitting their CV via the Apply link provided.