Senior Machine Learning Engineering Manager - Gen AI

Working Nomads; Canada; On-site; CAD 120,000 - 160,000; Full time

Job summary

A renowned technology firm is looking for an engineering manager to lead a team in developing their AI product, Dash. The role involves fostering a high-performing engineering team, driving product growth, and utilizing data to guide decisions. Candidates should have over 10 years in software engineering and at least 5 in management, along with expertise in machine learning applications. This is an opportunity to impact a rapidly growing product and innovate within a collaborative environment.

Qualifications

• 10+ years of software engineering experience.
• At least 5 years in direct management roles.
• Proficient in ML, NLP, LLM, and GenAI.

Responsibilities

• Lead and develop a high-performing team of engineers.
• Drive product monetization and revenue generation.
• Utilize data and insights to inform decisions.

Skills

Software engineering

Machine Learning

Data-driven decision making

Mentoring

Team leadership

Education

MS or PhD in Computer Science or related technical field

Job description

The Dropbox team is growing, and we're looking for an engineering manager to support this growth. In this role, you'll lead a team of engineers to build one of Dropbox’s newest AI offerings, Dash. Our team culture rewards a bias for action, engineering partnership in defining the product, and discipline in how we develop. You'll thrive in our team if you love chasing impact, working through ambiguity, and creating a culture of innovation. Dash is one of the fastest growing products at Dropbox and we need an extraordinary leader to scale the great work we are already doing and to diversify our efforts to continue to grow the business.

Lead and develop a high-performing team of engineers, fostering individual ownership, and driving impactful outcomes.

Shape and advance the future of Dash, driving product monetization and revenue generation for Dropbox.

Utilize data and insights to make informed decisions that significantly impact the company.

Foster operational excellence, streamline processes, and eliminate redundancies to ensure team agility.

Cultivate a collaborative culture within the team that embodies Dropbox's values.

Provide strategic direction and proactively anticipate scaling challenges through long-term planning.

Define team’s OKRs and manage the executions.

Work closely with business partners and peer teams for project priorities and requirements

Manages system’s operational health, including on-call duties and connections with external gateway partners.

Define the growth paths and opportunities for team members.

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

Requirements

MS degree or PhD in Computer Science or related technical field involving coding (e.g., physics or mathematics), or equivalent technical experience

10+ years of software engineering experience, with at least 5+ years in direct management roles.

Proficient in the latest advancements in ML, NLP, LLM, and GenAI.

Drive and ability to move forward in spite of ambiguity with a bias for action.

Proven expertise in the application of ML techniques to address practical challenges in real-world scenarios, spanning AI Agents, Chatbots, Search, or Information Retrieval domains.

Strong emphasis on using data-driven insights to guide decision-making processes, including A/B testing and experimentation.

Proven track record of setting visionary goals and delivering iterative progress.

Exceptional analytical capabilities to optimize solutions in complex and dynamic environments.

Ability to mentor and guide team members to maximize their impact.

Preferred Qualifications

Experience building 0→1 ML consumer facing products is a huge plus: an ideal candidate has done 0→1 products at large (dropbox-level) scale