Staff Machine Learning Engineer, Ads Targeting Platform

Key Skills

3D data processing, Apache Cassandra, Apache Flink, Apache Kafka, Argo, AWS, C++, Clustering, Docker, Elasticsearch, Google BigQuery, Google Cloud Platform (GCP), Java Programming, Machine learning techniques, Postgres, Python Programming, PyTorch, REDIS, Scala Programming, SPARK Programming, TensorFlow

Job Description

We're seeking a Staff Machine Learning Engineer to join our Ads Targeting Platform team. Ads Targeting provides advertisers with tools that allow them to reach Redditors across multiple dimensions and drive advertiser outcomes. As the Ads Targeting Platform team, we aim to build systems for creating and defining shared standards, low-latency infrastructure, and ML capabilities for all Ads Targeting initiatives. As a leader of this team, you will help us scale our systems to serve more advertisers, allow a faster rollout of new targeting product offerings, and enable more sophisticated targeting logic leveraging ML capabilities.

Responsibilities:

• you will build out storage, serving, forecasting, and ML Infra unifying across Targeting products, enable Targeting products with the economy of scale, and raise the bar for system reliability, resilience, and cost-effectiveness via better observability and monitoring.
• You will be responsible for the quality and technical approach within the team; partner with other leads in direction setting, planning, and overseeing eng designs and executions; establish and contribute to the group’s culture and processes.
• Unifying an ElasticSearch cluster for various targeting products like Dynamic Product Ads and Contextual Keyword Targeting, building out embedding training and serving infra to accelerate Lookalike modeling and ANN (Approximate Nearest Neighbor) Search, improving Audience Forecasting, and creating observability tooling for targeting funnel metrics.

Required Qualifications:

• 7+ years of experience building high-throughput, low-latency real-time services
• Experience with ML Infra like model & feature serving, large-scale offline computation, or embedding infra is required
• Experience leading large engineering teams and collaborating with cross-functional partners is required
• Experience with Ads Targeting / Serving platform / Search is preferred
• Experience with data-intensive applications (DB, cache, batch / stream processing) is preferred
• Experience working on a machine learning modeling framework like Tensorflow or PyTorch is a strong bonus

Preferred Qualifications:

• Significant experience in one or more general-purpose programming languages like Java, Python, Go, Scala, C++ or similar 
• Data processing frameworks like Spark, Flink, Kafka, Druid, etc.
• A cloud service provider like AWS or GCP
• Tools: Kubernetes, Drone, CircleCI, Spinnaker, Argo, Airflow, Docker, Thrift
• Datastores: ElasticSearch / Amazon OpenSearch, Redis, Postgres, Cassandra, BigQuery
• An machine learning modeling framework like Tensorflow or PyTorch (Preferred)

Benefits:

• Comprehensive Health benefits
• 401k Matching
• Workspace benefits for your home office
• Personal & Professional development funds
• Family Planning Support
• Flexible Vacation (please use them!) & Reddit Global Days Off
• 4+ months paid Parental Leave
• Paid Volunteer time off

Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base pay range for this position is:

$210,200—$315,300 USD

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