Senior Machine Learning Engineer

About the role

This role involves designing and implementing machine learning models to enhance various aspects of the Bluesky social network. Key responsibilities include improving personalized content recommendations, optimizing search functions, detecting spam, and labeling topics. The successful candidate will work with a large open dataset, including the Bluesky social graph and its content, to deliver accurate user experiences.

The position requires conducting machine learning tests and experiments, meticulously documenting findings for future iterations, and continuously training, retraining, and monitoring ML systems to ensure ongoing effectiveness. A critical component of the role is operating and running these machine learning systems at scale within production environments, ensuring robust and reliable performance.

Success in this role means consistently improving user experience on the federated social network through effective ML solutions. This involves a focus on rapid experimentation and a deep understanding of data structures and software architecture. The engineer will contribute to Bluesky's mission of transitioning the social web from platforms to protocols by empowering users through advanced ML capabilities.

The anticipated base salary range for this position is between $221,000 and $405,000 USD, excluding equity, with the final amount dependent on location, experience, and skills.

Skills that matter here

• Python: Proficiency in Python is required for developing and implementing machine learning models and systems.
• PyTorch: Experience with PyTorch and its related modules is necessary for building and training machine learning models.
• recommendations: The role focuses on designing ML models to improve personalized content recommendations for users.
• search: Machine learning systems will be developed to enhance search functionality within the social network.
• data structures: Familiarity with data structures is needed for designing efficient ML systems and handling large datasets.
• high-scale technologies: Experience with high-scale technologies is important for operating machine learning systems in production environments.

Who this role suits

• A person who thrives on rapid experimentation and is adept at documenting findings for iterative improvements.
• Someone with a strong background in machine learning or data science, specifically in recommendations and search.
• An individual comfortable working with large, open datasets and operating ML systems at scale.
• A collaborative team member with strong communication skills, able to interface with cross-functional teams.

From the employer

Key Responsibilities

• Design and implement machine learning models to improve personalized content recommendations, search, spam detection, topic labeling, and more.
• Work with the giant open dataset, the Bluesky social graph, and its content.
• Run machine learning tests and experiments, documenting findings and results for future iterations.
• Ensure algorithms deliver accurate user recommendations and optimized experiences.
• Train, retrain, and monitor machine learning systems to maintain model effectiveness.
• Operate and run machine learning systems at scale in production environments.

Required Qualifications

• 3+ years of recent experience in machine learning or data science roles, with a focus on recommendations and search.
• Proficiency in Python and experience with PyTorch and related modules.
• Willingness and a knack for rapid experimentation.
• Familiarity with data structures, data modeling, and software architecture.
• Experience with high-scale technologies.

Nice to Have

• Experience in recommendation systems, user behavior modeling, and social graph analysis.
• Familiar or proficient with Golang — our ML code interfaces with it heavily.
• Experience with Ray, BigQuery, and Postgres.
• Ability to extend and optimize existing machine learning libraries and frameworks.
• Strong communication skills and a collaborative mindset for working with cross-functional teams.

Compensation

The anticipated base salary range for this position is $221,000 – $405,000 USD, excluding equity. Equity will be considered in the total compensation package. Final base salary will be based on the individual’s geographic location, as well as experience level, skill set, training, licenses, and certifications.

We’re a fully remote team, but an overlap of working hours with PST is required. Proximity and willingness to travel to Seattle is a plus. Health, dental, and vision insurance included.