As a Senior Machine Learning Engineer, you will design and maintain ML systems for content recommendations, search, and spam detection, while augmenting user experience and system performance.
About Us:
Bluesky's mission is to transition the social web from platforms to protocols. We're building a federated social network where users have more power. Our team has decades of combined experience building distributed applications.
Role Overview:
As a Senior Machine Learning Engineer at Bluesky, you will design, develop, and maintain machine learning systems for various parts of our stack. You will work on systems that directly impact the user's experience on the network, whether through content recommendation, search, spam detection, or automated labeling. Your work will augment the team's abilities to make the network a good place for all our users.
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
We're especially excited if you:
- Experience in recommendation systems, user behavior modeling, and social graph analysis.
- Familiar or proficient with Golang, our ML code interfaces with it heavily.
- Have 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.
We’re a fully remote team, but an overlap of working hours with PST is required, and for this role, proximity and willingness to travel to Seattle is a plus. Please note, there may be an on-site component to these interviews. We offer health, dental, and vision insurance. If you want to work with an excellent team and help define the future of social, we encourage you to apply.
To learn more about us, check out:
- bsky.social
- atproto.com
Additional notes:
- 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 for this role will be based on the individual’s geographic location, as well as experience level, skill set, training, licenses and certifications.
Similar Jobs
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
Design, deploy, and maintain end-to-end ML-driven risk solutions at scale to detect and prevent fraud, abuse, and credit risk. Lead technical decisions, build ML tooling and processes, apply state-of-the-art models and third-party data, investigate emerging risk patterns, and collaborate with platform and cross-functional teams to ensure reliable real-time model operation.
Top Skills:
AirflowAWSCi/CdContainerizationGCPKerasMlflowModeMySQLNumpyPandasPrefectPysparkPythonPyTorchScikit-LearnSnowflakeTableauTensorFlowVertex AiXgboost
Blockchain • Fintech • Mobile • Payments • Software • Financial Services
Design, deploy, and maintain end-to-end ML risk solutions at scale to detect and prevent fraud, merchant risk, and credit loss. Partner with cross-functional teams, lead technical decisions, build ML tooling, monitor models in production, and investigate emerging abuse patterns to improve detection and decisioning.
Top Skills:
AirflowAWSCi/CdContainerizationGCPKerasMlflowModeMySQLNumpyPandasPrefectPysparkPythonPyTorchScikit-LearnSnowflakeTableauTensorFlowVertex AiXgboost
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Design, build, and deploy generative AI solutions (LLMs, RAG, Agentic AI) for the Pharmacy domain. Collaborate with pharmacists and capability teams, containerize projects, implement CI/CD, validate and optimize models, maintain code quality and security, and support production environments on cloud platforms while working Eastern Time hours and participating in on-call rotations.
Top Skills:
Agentic AiAWSAzureCi/CdGitGitGithub ActionsGCPKerasLangchainLanggraphLarge Language Models (Llms)PythonPyTorchRetrieval-Augmented Generation (Rag)TensorFlow
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
