Senior Manager, Machine Learning

Who You'll Be Leading

As a Senior Engineering Manager in Data Science, you will lead a cross-functional team of engineers and machine learning engineers to build innovative machine learning services that power the next generation of experiences for smart homes.With their support, you'll be responsible for large-scale solutions that integrate products and services across our ecosystem and it will be your creative thinking in system and service design that creates unique and seamless experiences for our customers. Your expertise will help shape our future by influencing the overall strategy, driving system architecture and establishing best practices in software development.

How You’ll Make an Impact

• Foster a positive, supportive and inclusive work environment.
• Hire and develop a team of software engineers and machine learning engineers—providing coaching, mentoring, motivation, and technical guidance.
• Build high-quality, efficient and scalable services powered by our machine learning products.
• Integrate data science services with products and systems across our ecosystem.
• Lead system architecture design that reduces complexity and enables extendibility and reusability.
• Manage the full ML development life cycle and tooling – from problem framing, data wrangling, and model development, to deployment, monitoring, and maintenance
• Continuously improve engineering practices—balancing speed, quality, and business impact.
• Build effective agile practices that deliver robust solutions on time and on budget.
• Lead execution of project plans, delivery commitments and risk mitigation.
• Help evaluate the feasibility of initiatives through quick prototyping with respect to performance, quality, time and cost.
• Build strong partnerships with cross-functional teams and contribute to deliver unique customer experiences.

What You’ll Bring to the Table:

We've built the following list as a guideline for some of the skills and interests of our development team - but we strive to build our team with members from a diverse background and skill set, so if any combination of these apply to you, we would love to chat!

• A well established history of building efficient and scalable systems and services for machine learning products.
• Experience managing a team of engineers.
• Expertise in building low latency, high performance services.
• Experience with implementing end-to-end scalable solutions in the cloud.
• Excellent communication skills, both written and verbal.
• Experience communicating with technical and non-technical stakeholders across multiple business units.
• Experience with agile and other program management methodologies.
• You proactively identify upcoming risks, issues and bottlenecks within your team and across departmental boundaries.
• You thrive in a fast-paced, ambiguous, and high-stakes environment.
• You are a smart, curious, and analytical person with a bias for action.

Just so you know: The hired candidate will be required to complete a background check.

What Technologies We Use:

• Python, dbtLabs, SQL, GitHub Actions (CI/CD)
• Google Cloud Platform: BigTable, BigQuery, Pub/Sub, Dataflow, Dataproc, Airflow, Kubeflow etc.
• Terraform, Docker, MLOps Platform (VertexAI, Sagemaker and MLFlow)

What happens after you apply:

Application review. It will happen. By an actual person in Talent Acquisition. We get upwards of 100+ applications for some roles, it can take a few days, but every applicant can expect a note regarding their application status.

Interview Process:

• Round 1: A 30-minute phone call with a member in Talent Acquisition
• Round 2: A 60-minute virtual interview with the Hiring Manager – expect technical, behavioural and situational questions
• Round 3: A 2 part interview of an hour each focussing on a System Design and Coding exercise followed by an hour of deep dive technical Q&A