Senior Staff Machine Learning Engineer
- Published on
About the Role
Harnham is seeking a Senior Staff/Technical Lead Machine Learning Engineer to join and spearhead a team in building groundbreaking AI solutions. This role involves leveraging one of the largest consented behavioral datasets in the US, focusing on ad optimization and recommendation systems.
Key responsibilities include:
- Designing, building, and deploying end-to-end ML models.
- Developing and implementing ML pipelines using rich behavioral signals to enhance user value and business ROI.
- Collaborating with product and R&D teams to conceptualize and execute impactful ML-first product strategies.
- Leading experimentation and model evaluation in a data-rich environment.
- Developing scalable infrastructure using tools like Airflow, Spark, and CI/CD platforms.
About the Candidate
The ideal candidate will have:
- An MSc or PhD in a STEM field.
- Extensive experience in building and deploying machine learning systems.
- A strong background in AdTech or recommender systems with an understanding of user intent modeling.
- Hands-on experience with tools like Airflow, Spark, SQL, and Python.
- DevOps knowledge, including CI/CD best practices.
- Familiarity with cloud platforms such as AWS and ML tooling such as TensorFlow and Kubernetes.
- Strong communication skills and a product-oriented mindset suitable for a startup environment.
About the Company
Harnham is a fast-growing tech firm dedicated to introducing innovative solutions in behavioral modeling and personalization. They are partnered with major cloud providers and focus on delivering private-by-design AI solutions for notable global brands.
Company Culture and Benefits
Harnham offers a competitive salary of $300,000 to $350,000 plus equity and financial opportunities. They support a fully remote work environment, with hybrid options available across several cities, including Boston and San Francisco.
How to Apply
Interested candidates should submit their CV via the application link.
Desired skills include expertise in Machine Learning Engineering, AdTech, Personlization, Recommender Systems, CI/CD, and technologies such as Airflow and Spark.