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Artificial Intelligence • Information Technology • Natural Language Processing • Software • Business Intelligence • Generative AI
The role involves developing and optimizing machine learning models, collaborating with teams, and building scalable data pipelines to enhance customer experiences at Qualtrics.
Top Skills:
Artificial IntelligenceC#JavaMachine LearningPythonPyTorchTensorFlow
Artificial Intelligence • Digital Media • eCommerce • Marketing Tech • Software
As a Senior Machine Learning Engineer, you will design and productionize machine learning models, collaborate with teams, and maintain high quality code.
Top Skills:
AWSKubeflowMachine LearningTensorFlow
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Healthtech • Other • Sales • Software • Analytics • Conversational AI
The Senior Machine Learning Engineer will develop AI agents for healthcare workflows, collaborating with various teams to enhance patient engagement and automate processes using cutting-edge technology.
Top Skills:
AirflowAWSDagsterHugging FaceLangchainPythonSQLTensorFlowTypescript
The Search Ads team constantly pushes the boundaries of general search engine monetization across multiple apps within our ecosystem, building a globally leading Search Ads monetization system. At the Search Ads team, you will have the chance to work on large-scale distributed storage and architecture, NLP, Rank, and IR related problems. You will be also deeply involved in the innovation and optimization of our Ad format, creative display, and the ROI of ads delivery. We are looking for candidates who brave difficulties, share a passion for tackling complexity and developing our Search Ads product from 0 to 1 with a world-class team of passionate engineers.
What You'll Do:
- Participate in the development of a large-scale Ads system
- Responsible for relevance model and strategy optimization, such as semantic matching models, active learning, text/photo/video multi-model, ranking strategy, etc
- Participate in the development and iteration of Ads algorithms by using Machine Learning
- Work on NLP (Natural Language Processing) capability improvement and query understanding, such as query classification, seq2seq, NER (Named Entity Recognition), knowledge graph, bidword optimization, etc
- Work on CTR/CVR model estimation accuracy, data analysis, modeling, feature engineering
- Research and develop Ads pacing algorithms, ads traffic control, etc
- Partner with product managers and product strategy & operation team to define product strategy and features
- BS degree in Computer Science, Computer Engineering or other relevant majors
- Experience with one or more general purpose programming languages including but not limited to: Go, C/C++, Python
- 5+ years of experience in and a good understanding of one of the following domains: Search, Ads, Recommendation, Monetization Products, Shopping Products.
- Experience with one or more of the following: Machine Learning, Deep Learning, NLP, ranking systems, recommendation systems
- Ability to think critically and formulate solutions to problems in a clear and concise way
- Solid communication and collaboration skills with the ability to work effectively with internal teams in a cross-cultural and cross-functional environment
What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
