Machine Learning Engineer, Ad Bidding Optimization

To achieve our ambitious goals, we’re looking for a Machine Learning Engineer to join our Marketing Technology team. This team is responsible for building systems that empower and enhance the company's marketing efforts and strategies. The person in this role will help shape marketing strategies, enhance customer experiences, and optimize marketing campaigns. They will be responsible for leveraging data and advanced algorithms to improve the performance and efficiency of advertising campaigns with the goal of maximizing the return on investment (ROI) for ad spend and delivering targeted ads to the right audience.

Grammarly’s engineers and researchers have the freedom to innovate and uncover breakthroughs—and, in turn, influence our product roadmap. The complexity of our technical challenges is growing rapidly as we scale our interfaces, algorithms, and infrastructure. You can hear more from our team on our technical blog.

As Machine Learning Engineer on the Marketing Technology team, you will transform the way marketing is done  will improve data‑driven decision‑making, enhance customer experiences, and optimize marketing campaigns, ultimately leading to improved business outcomes and higher customer satisfaction.

In this role you will:

• Drive business impact by building scalable end‑to‑end machine learning solutions for challenging marketing problems.
• Help marketing teams make data‑driven decisions.
• Personalize marketing efforts, tailoring content and offers to individual customers.
• Promote excellence and best practices across the Machine Learning team in research, implementation, tooling, and system design.
• Work cross‑functionally with various teams:
  Marketing, Marketing Analytics, Data Science, ML Infrastructure, and Product to name a few.
• Effectively communicate technical machine learning results in a business context where most people are not machine learning experts.

• Embodies our EAGER values—ethical, adaptable, gritty, empathetic, and remarkable.
• Is inspired by our MOVE principles, which are the blueprint for how things get done at Grammarly: move fast and learn faster, obsess about creating customer value, value impact over activity, and embrace healthy disagreement rooted in trust.
• Is able to collaborate in person 2 weeks per quarter, traveling if necessary to the hub where the team is based.
• Has solid software engineering fundamentals, including knowledge of classical algorithms and data structures.
• Has a solid understanding of the principles and best practices of developing software systems on a large scale.
• Has the ability to apply machine learning algorithms to ad optimization tasks effectively.
• Has strong knowledge of probability and statistics.
• Has expertise in Python, its ecosystem, and Python‑based ML tools and frameworks.
• Has experience in Ad Optimisation domain: knowledge of different types of ad channels, multi‑channel budget allocation, key marketing performance metrics.

• Professional growth:
  We believe that autonomy and trust are key to empowering our team members to do their best, most innovative work in a way that aligns with their interests, talents, and well‑being. We support professional development and advancement with training, coaching, and regular feedback.
• A connected team:
  Grammarly builds a product that helps people connect, and we apply this mindset to our own team. Our remote‑first hybrid model enables a highly collaborative culture supported by our EAGER (ethical, adaptable, gritty, empathetic, and remarkable) values. We work to foster belonging among team members in a variety of ways. This includes our employee resource groups, Grammarly Circles, which promote connection among…