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Senior Staff/Technical Lead Machine Learning EngineerHarnham • New York, New York, United States
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Senior Staff/Technical Lead Machine Learning Engineer

Harnham
  • US
    New York, New York, United States
  • US
    New York, New York, United States
Jetzt Bewerben

Über

Senior Staff/Technical Lead Machine Learning Engineer Senior Staff/Technical Lead Machine Learning Engineer This range is provided by Harnham. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range $300,000.00/yr - $350,000.00/yr Direct message the job poster from Harnham Building AI/ML & Data/Software Engineering Teams Across The US Senior Staff Machine Learning Engineer Remote Up to $350,000 + Equity Company: A fast-growing, mission-driven tech company in the behavioral modeling and personalization space is seeking a Senior Staff/Technical Lead Machine Learning Engineer to join and lead a team. Their platform leverages one of the largest consented behavioral datasets in the US to deliver private-by-design AI solutions for top global brands and platforms. The team is made up of seasoned ML professionals from Top Companies, and they are partnered with major cloud providers to bring novel AI products to market. This role will be central to building and scaling ML-powered products, with a focus on ad optimization and recommendation systems . Role: Design, build, and deploy end-to-end machine learning models focused on ad optimization, personalization use cases and recommendation systems . Develop ML pipelines and production systems that leverage rich behavioral signals to drive user value and business ROI. Partner with product and R&D teams to ideate and execute on high-impact, ML-first product strategies. Lead experimentation and model evaluation in a fast-paced, data-rich environment. Contribute to the development of scalable infrastructure using tools like Airflow , Spark , and CI/CD platforms. Work cross-functionally to bring zero-to-one ML products to market and continuously refine them post-launch. Stay on the pulse of emerging ML techniques in RecSys, behavioral modeling, and model optimization. Requirements: MSc or PhD in a STEM field. Proven experience building and deploying machine learning systems in a commercial setting. Strong background in AdTech or recommender systems (RecSys) - with a clear understanding of personalization, targeting, or user intent modeling. Hands-on experience with orchestration tools ( Airflow , Bazel ), data infrastructure ( Spark , SQL , Scala , or Python ). DevOps knowledge including CI/CD best practices and production model monitoring. Familiarity with cloud platforms (AWS, Databricks) and ML tooling (MLFlow, TensorFlow, Kubernetes). Strong collaboration and communication skills, with a product-oriented mindset. A bias toward action and a "roll up your sleeves" attitude-ideal for a dynamic startup environment. Salary and Benefits: Meaningful Equity & Financial Upside Fully Remote (with hybrid options in Boston, SF Bay Area, Seattle, NYC) How to Apply: Please register your interest by submitting your CV via the Apply link on this page. Desired Skills and Experience: Machine Learning Engineering, AdTech, Personalization, Recommender Systems, MLOps, CI/CD, Airflow, Spark, Python, AWS
Senior Staff Machine Learning Engineer Remote Up to $350,000 + Equity Company: A fast-growing, mission-driven tech company in the behavioral modeling and personalization space is seeking a Senior Staff/Technical Lead Machine Learning Engineer to join and lead a team. Their platform leverages one of the largest consented behavioral datasets in the US to deliver private-by-design AI solutions for top global brands and platforms. The team is made up of seasoned ML professionals from Top Companies, and they are partnered with major cloud providers to bring novel AI products to market. This role will be central to building and scaling ML-powered products, with a focus on ad optimization and recommendation systems . Role: Design, build, and deploy end-to-end machine learning models focused on ad optimization, personalization use cases and recommendation systems . Develop ML pipelines and production systems that leverage rich behavioral signals to drive user value and business ROI. Partner with product and R&D teams to ideate and execute on high-impact, ML-first product strategies. Lead experimentation and model evaluation in a fast-paced, data-rich environment. Contribute to the development of scalable infrastructure using tools like Airflow , Spark , and CI/CD platforms. Work cross-functionally to bring zero-to-one ML products to market and continuously refine them post-launch. Stay on the pulse of emerging ML techniques in RecSys, behavioral modeling, and model optimization. Requirements: MSc or PhD in a STEM field. Proven experience building and deploying machine learning systems in a commercial setting. Strong background in AdTech or recommender systems (RecSys) - with a clear understanding of personalization, targeting, or user intent modeling. Hands-on experience with orchestration tools ( Airflow , Bazel ), data infrastructure ( Spark , SQL , Scala , or Python ). DevOps knowledge including CI/CD best practices and production model monitoring. Familiarity with cloud platforms (AWS, Databricks) and ML tooling (MLFlow, TensorFlow, Kubernetes). Strong collaboration and communication skills, with a product-oriented mindset. A bias toward action and a "roll up your sleeves" attitude-ideal for a dynamic startup environment. Salary and Benefits: $300,000 - $350,000 base salary Meaningful Equity & Financial Upside Fully Remote (with hybrid options in Boston, SF Bay Area, Seattle, NYC) How to Apply: Please register your interest by submitting your CV via the Apply link on this page. Desired Skills and Experience: Machine Learning Engineering, AdTech, Personalization, Recommender Systems, MLOps, CI/CD, Airflow, Spark, Python, AWS
Desired Skills and Experience
Ads, RecSys
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