Machine Learning Engineer Job at Harnham, New York, NY

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  • Harnham
  • New York, NY

Job Description

Role Type: Machine Learning Engineer

Reporting to: Director of Data Science (role we are currently recruiting for #174682)

Location: Hybrid(New York, Fort Worth, Ann Arbor), OR remote

Travel Expectation: at least 4x a year to visit with teams

Time zone: flexible - team works across multiple time zones

Salary: $190 -$215 base + 5%-10% bonus

Join our team as a Machine Learning Engineer, where you'll drive innovation and business impact by developing and deploying machine learning models. You will collaborate with cross-functional teams, including data scientists and software engineers, to create solutions for complex business challenges.

Key Responsibilities:

  • Design, develop, and deploy machine learning models to solve business problems (e.g., recommendation systems, NLP, predictive analytics).
  • Work closely with stakeholders to translate requirements into data-driven solutions.
  • Collect, preprocess, and analyze data to optimize model performance.
  • Monitor and maintain model performance in production environments.
  • Stay up-to-date with the latest in machine learning research and technologies.
  • Collaborate across teams to drive actionable insights and business decisions.

Qualifications:

  • Bachelor's degree in Computer Science, Engineering, Mathematics, or related field (Master's/PhD preferred).
  • 3+ years of experience developing and deploying machine learning models in production.
  • Strong programming skills (Python, Go, Perl) and experience with tools like TensorFlow, Docker, AWS, and Databricks.
  • EXTENSIVE adtech/ad auctioning experience
  • Experience in mode based modeling
  • Expertise in data preprocessing, feature engineering, and model evaluation.
  • Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
  • Strong problem-solving, communication, and collaboration skills.

Nice to Have:

  • Experience with Agile/Scrum methodologies and interdisciplinary teams.

Job Tags

Flexible hours,

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