Lead Machine Learning Engineer

As our Lead Machine Learning Engineer, you will be the pioneering hire in our Creative Insight’s ML division, laying the foundation for a team that will grow to include additional ML engineers. You will collaborate closely with our existing team of software engineers to ideate, implement, and integrate ML technologies that analyze ad content performance and optimize audience targeting and modeling. You will be at the forefront of these initiatives, overseeing them from the initial concept stage all the way through to prototyping and implementation, in addition to conducting experiments. You will not throw anything over a wall, nor will you be expected to catch anything thrown.

Responsibilities

• • Develop and implement machine learning models to predict and analyze the performance of digital advertisements.
  • Utilize statistical analysis and ML techniques to understand the correlation between ad content and audience engagement.
  • Lead the ideation, design, and execution of data-driven projects that enhance our ability to target audiences more effectively.
  • Innovate and implement ML solutions that can scale across various platforms and customer segments.
  • Establish metrics and evaluation frameworks to assess the effectiveness of ML models.
  • Wear an MLOps hat: monitor and maintain AI/ML Models in production, determining, for example, when to retrain or replace an existing model.
  • Leverage Generative AI to (for example) deliver AI-assisted asset generation workflows based on historical asset performance. 
  • Mentor and lead a growing team of ML engineers, fostering a collaborative and results-driven environment.

Skills & Experience

• • Master’s or Ph.D. in Computer Science, Machine Learning, Statistics, or a related field.
  • Minimum of 5 years of experience in machine learning, data science, or a similar role, with a proven track record of deploying models in production environments.
  • 2+ years of experience leading and mentoring engineers
  • Strong expertise in programming languages such as Python and ML libraries like TensorFlow, PyTorch, or scikit-learn.
  • Experience in advanced predictive modeling, natural language processing, or computer vision.
  • Deep understanding of machine learning algorithms, including supervised and unsupervised learning, deep learning, and neural networks (inc. Transformers).
  • Familiarity with Generative AI systems.
  • Experience with data manipulation and analysis using SQL, pandas, or similar tools.
  • Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
  • Strong hands-on experience applying Software Engineering principles and practices (e.g. source code control, API design, and design patterns) to machine learning models (and other probabilistic workflows).
  • Excellent communication and leadership skills to lead project teams and interface with clients and stakeholders.

Desirable Attributes

• • Prior experience in digital marketing or advertising technology.
  • Familiarity with cloud computing services like AWS, Google Cloud, or Azure.
  • A deep passion to create a “graph-of-thought” LLM workflow using a DAG (or DAG-like) execution engine.

Last updated on Aug 22, 2024