Senior Machine Learning Engineer

Haystack News - Miami, FL

Full-time - Senior

Miami, FL

Broadcasting and Content Providers

About the position

As a Senior Machine Learning Engineer at Haystack News, you will play a crucial role in enhancing user experiences through advanced algorithm improvements. This position involves leveraging your expertise in machine learning and data analytics to significantly boost user engagement and retention, thereby directly influencing the success of our product. You will collaborate with a team of dedicated professionals in a dynamic environment, where your contributions will have a meaningful impact on the future of news consumption.

Responsibilities

• Work cross-functionally to translate business problems into ones that can be solved using machine learning.
• Apply analytical skills to dive deep into data to find key insights that would impact the business.
• Develop machine learning models to make recommendations and influence the product roadmap.
• Collaborate with team members to develop key metrics to achieve business outcomes.
• Design, execute, and analyze experiments to prove product change attribution.

Requirements

• 5+ years of professional experience with at least 3 years building large-scale recommender systems.
• Track record of shipping models to real-world applications and making an impact.
• Experience building and deploying online ML algorithms (e.g. contextual bandits).
• Master's degree in Computer Science, Mathematics, Electrical Engineering, Statistics, or Operation Research.
• Proficient in programming in Python; additional programming experience in Java, JavaScript, or C++ is a plus.
• Experience with deep learning and familiarity with tools such as PyTorch or TensorFlow.
• Familiarity with common machine learning algorithms, such as GBDT, XGBoost, Random Forest, Logistic Regression.
• Experience with SQL (e.g. postgres, snowflake, etc).

Nice-to-haves

• 2+ years of applied research experience (including research work during PhD).
• Experience working with LLMs, Semantic Search and text embeddings (e.g. BERT).