Jake Mannix Email & Phone Number

Seattle, WA, US

Bentonville, Arkansas, US

Helping advance the state of the art of retail AI, at the world's largest retailer.

slowest rolling "stealth startup" you ever did see!(ie mostly consulting)

Advising early stage (pre-seed/seed) tech startups in the AI/ML space

Sunnyvale, CA, US

Helping shape the future of Machine Learning Infrastructure on which all of LinkedIn's AI-based applications and features are built.Initially responsible for the technical vision and architecture for the infrastructure-side of a company-wide (~dozen teams across 3 top-level engineering orgs) project to enable "embedding-based retrieval" (vector similarity.

Caldwell, ID, US

LLM Crash Course: Introduction to LoRA and Agentic ApplicationsIntroduced ML, Deep Learning, and transformers to CS undergraduates, focusing on implementation and practical use with PyTorch, including fine-tuning Phi2, building simple RAG pipelines, and working with LangChain.

Caldwell, ID, US

"The Software Industry: A Crash Course"Teaching graduating seniors the fun joys of git, code reviews, TDD (or not), CI/CD, Service Oriented Architecture, micro-services vs macro-services, and all the things they don't teach you in school. Just in time to terrify them before going out into the industry:)

San Francisco, California, US

Responsible for the long-range vision of AI and Search at Salesforce.Mentoring, helping hire, guide the Virtual Architecture Teams toward building the right Search and AI infrastructure where intelligent data-driven applications are powerful, scalable, and easy to build, regardless of whether it's done by a specialized internal team of ML Engineers and.

San Francisco, California, US

As the Search Relevance organization expanded to include the Einstein Language Intelligence and Einstein Platform Apps teams, my role expanded with it, to design and lead implementation of generic recommender and search applications in composable ways, incorporating more deep learning-based models for language-understanding, text embedding, and.

San Francisco, California, US

Lead the technical vision for the Search Relevance organization, including the following teams:* Search Ranking* Search Query Understanding* Search Data and Analytics* Search Intelligence PlatformLots of fun projects building up our model training platform, migrating from simple linear models stored as JSON blobs in Oracle tables to sophisticated deep.

San Francisco, California, US

Head up company-wide efforts around scalable data processing and applied machine learning infrastructure in the context of search and related data-driven products, bridging the gap between R&D and product engineering. My primary focus was bringing the "intelligence" to intelligent semantic search for the enterprise: get the right actionable enterprise data.

San Francisco, California, US

Search, relevance, ranking, applied NLP and machine learning to search and recommender products on top of an open source stack (Lucene/Solr, ZooKeeper, Spark/MLLib, Mahout, etc).

Seattle, WA, US

Data infrastructure engineering and applied machine learning to help scale out applying NLP techniques on semantic search over a corpus of scientific articles, launched in the fall of 2015: http://www.semanticscholar.org/Scala, Akka, Spark, ElasticSearch, etc.

San Francisco, CA, US

Multiple roles, variety of teams. Fun stuff. See specific role positions below for more details.Tech Lead, User Modeling:Built and lead a team of distributed-systems and machine learning engineers responsible for understanding Twitter's "interest graph", taking tweet text, links, and the social graph, and using a variety of classification and topic.

Wilmington, Delaware, US

Served as Chair of Mahout's Project Management Committee, helping make sure that ASF processes are followed by the large and varied Mahout community, involving not only technical advice and help for new users (as all contributors do), but advising users regarding regarding proper use of Apache copyrights and trademarks, and advocating for Mahout adoption.

Wilmington, Delaware, US

The Apache Giraph project is a fault-tolerant in-memory distributed graph processing system which runs on top of a standard Hadoop installation, and is capable of running any standard Bulk Synchronous Parallel (BSP) operation over any large generic data set which can be represented as a graph, and is a loose implementation of Google's Pregel.

Wilmington, Delaware, US

Helping build an open-source, commercial friendly licensed, scalable machine learning library. Have focused on improving our bayesian topic modeling work (e.g. LDA) and linear algebra primitives, as well as adding dimensional reduction components for NLP and recommender systems.

Sunnyvale, CA, US

One of the primary architects of the (original - long since replaced, several times over!) distributed, real-time, faceted people search platform you most likely used to find this profile.Helped justify, scope out, and build a new engineering team inside of LinkedIn's analytics-engineering organization: from two initial engineers, we built a Recommendation.

Directed architectural vision for all things Search-related, from redesigning, developing, and maintaining a high-availability query-expanding job-post (full-text) search engine (as a replicated Tomcat+Lucene+Spring+mySQL-based web service), to R&D of next-generation conceptual applicant/position matching technology, using a ngram-based.

Menlo Park, California, US

Performed theoretical high energy physics and cosmology research for Stanford University's Institute for Theoretical Physics: developed and tested inflationary cosmology simulation software, with C++/optimized ASM for the computational back-end, Hibernate / MySQL datastore, and Jakarta Struts MVC (Servlet + JSP) for front-end web presentation. Computed.

Seattle, WA, US

RealServer streaming audio/video development in C++

Seattle, WA, US

Client and Server streaming audio/video streaming applications

Member of the inaugural class (2 students picked each year) of visiting graduate fellows at the newly formed Kavli Institute for Theoretical Physics (coincident with the Strings '99 Conference), working with Philip Argyres and his student on string theoretic representations of 4d SCFTs which allowed for a geometric proof of electric-magnetic duality in.

Phd, Physics

Ms, Mathematics

Phd, Physics

Bs, Mathematics