Position: Engineering Manager, Machine Learning
Company: Grammarly
Category: Data Science
Experience required: 5y
English level: upper

**Your impact**

As Engineering Manager, you will lead the Machine Learning Engineering team and collaborate across multiple offices with research scientists, computational linguists, and product managers to ship delightful user experiences across various interfaces. You will influence and fundamentally change the way Grammarly engineering delivers ML-powered features.

**In this role, you will:**

- Guide the team to operating services at internet scale with high availability and reliability.
- Propose and implement the best engineering and research practices for scaling ML-powered features at Grammarly, with a goal to enable fast iteration of and efficient experimentation with novel features.
- Help drive engineering-wide initiatives with other engineering leaders.
- Act as an effective manager by being a strong advocate and promoter for the team.
- Contribute to and influence the ML infrastructure roadmap based on the feedback from internal customers.
- Build and enhance consumer and enterprise intelligence features in Grammatical Error Correction (GEC) and text semantics, such as tone and summarization.

**We’re looking for someone who**

- Embodies our EAGER values—is ethical, adaptable, gritty, empathetic, and remarkable.
- Has a strong track record of building and managing productive engineering teams.
- Derives satisfaction in helping the team accomplish audacious goals.
- Has hands-on experience as a senior engineer.
- Has experience translating a high-level strategy and roadmap into an execution plan.
- Can effectively set and communicate priorities for themselves and their team.
- Can successfully coordinate, empower, and direct multiple stakeholders, details, and timelines toward a specific goal.
- Thrives managing through the roadmap ambiguity and unique problem-solving associated with new product ideas—by balancing ownership of mission-critical systems and building features around a loosely defined roadmap.
- Stays up-to-date with the quickly evolving field of natural language processing (NLP), tracking industry trends while focusing on building production systems.
- Brings a solid understanding of ML development lifecycle and tools, including some domain experience with ML, deep learning, or NLP.
- Holds a master’s degree in computer science, engineering, or math.