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@genomequest.com
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2 phones found area 844 and 508
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Jun Wan is listed as Builder, Deep Learning and LLM at Amazon, based in Cambridge, Massachusetts, United States. AeroLeads shows a work email signal at genomequest.com, phone signal with area code 844, 508, and a matched LinkedIn profile for Jun Wan.
Jun Wan previously worked as Software Development Manager, Amazon General Intelligence Foundations at Amazon and Software Development Manager, Alexa AI - Natural Understanding at Amazon. Jun Wan holds Master Of Science - Ms, Computer Science from Umass Boston.
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AeroLeads found 1 current-domain work email signal for Jun Wan. Compare company email patterns before reaching out.
I am an experienced software engineering leader, with rich and solid hands-on experience. My passion is to build AI systems and deliver value to business. My current focus is building high performance and large scale deep learning solutions. At Amazon, I ran teams in Alexa and later AGI org. My first team manages, scales, secures hundreds of petabytes of datasets used by thousands of modelers to train ML models. I then moved to NLU and lead a team to develop cutting edge deep neural network training and inference tools used by Alexa Runtime serving hundreds of millions customers. Since 2023, I have been leading my team to create AI model inference solutions, and launched Alexa’s first production LLM inference engine meeting strict latency budget in Sept 2023, followed by Bedrock Titan model launch in May 2024, and Amazon Nova models in Nov. 2024 which achieved best latency in the industry as measured by 3rd party. At Jobcase, I managed to fill knowledge gap quickly (cloud computing and ML), and built a small team. Together we built a data lake and a ML platform from scratch. I also built production ML models and became a contributor to the Tensorflow Open Source project.I joined SunQuest as Principal Engineer, and got promoted to run the 15+ people product development team in 5 months. I released quality software classified as medical device. During 13+ years at GenomeQuest, I started in a 3-person US team, innovated and built the majority of technologies. The product is used by 18 out of the top 20 pharma and all five top agrochemical companies worldwide for their mission critical IP business processes. Throughout my career, I recruited and led teams successfully delivered many commercial software products supporting critical needs for companies large and small. I am very pragmatic, and I enjoy finding effective and incremental solutions to problems, and don’t let perfect get in the way of releasing something impactful quickly.SKILLS:* Lead commercial software development team. Perform any or all roles of team leader, architect, manager.* Machine Learning: LLM Inference, Transformers, Tensorflow, PyTorch, DNN, model runtime.* AWS Cloud technologies, Data Lake, Spark, Kafka, SageMaker, CloudWatch.* Relational database, Object oriented design and patterns.* NoSQL. Cassandra, DynamoDB, Apache Ignite, Redis.* Bioinformatics applications, LIMS, Sequence analysis. NGS data analysis.* Java, Python, Spark, Javascript/Angular2, PHP, Scala, Groovy/Grails, Solr, Cassandra, Docker, CSS, Spring, MySQL, K8s, and many other 3-letter acronyms.
Listed skills include Software Development, Perl, Bioinformatics, Agile Methodologies, and 45 others.
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Seattle, WA, US
[06/2023 – pres] Since 2023, I led my team onto a new charter in generative AI - to optimize the LLM inference performance (latency, throughput and cost). Starting from scratch, we launched Alexa’s first LLM inference engine in 9 months, meeting very strict latency requirements for natural conversational experience. Our inference engines are now powering.
Seattle, WA, US
My team developed cutting edge deep neural net (DNN) training toolkit used by hundreds of NU scientists in Alexa AI to develop intelligent models (multilingual, multimodal, large language models, multi-turn, etc.) for many NLP tasks (classification, semantic parsing, generative, NER, etc.). We use a config-driven approach (low/no code), enable model's.
Seattle, WA, US
Run a team that develops tools to manage the hundreds of peta bytes of Alexa data, improve scaling, privacy, access and compliance. We constantly deal with billions or trillions of things. * Developed data caching service for ASR model training with dataset size in the order of many peta bytes.* ASR model training optimization* Contributed to the delivery.
Cambridge, MA, US
* Led a small team, hands-on developed an end-to-end machine learning platform. * The platform supports datasets querying, feature engineering, model training, evaluation, model deployment (off-line batch processing and on-line real time), model maintenance (retraining, logging, performance monitoring).* Data scientists have the interactive notebook for.
UK, Europe, North America And India, GB
* Run the software development of Mitogen Analysis (FDA regulated medical device), with one major release.* Drive integration between multiple SunQuest Mitogen products.* Improve the architecture and technology standards across the product portfolio Mentor the team, code whenever I can.
UK, Europe, North America And India, GB
* Architect and Develop features for GeneInsight and Uniconnect Product lines. * Java ecosystem - Java, EJB, CDI, JBoss Wildfly, JPA, JAX-WS, Maven.* Javascript ecosystem - Angular 2, AngularCli, Angular Grid, TypeScript, Polymer, Dragula, NPM, Grunt, Bower.* Adobe - Flex, ActionScript, Spark DataGrid.* Dev Tools - Eclipse, WebStorm, FlashBuilder.
Boston, MA, US
* Managed to spend 50% time coding.* Created new product LifeQuest 1.0, from product ideation, to general market release. LifeQuest is a modern full text semantic search web app for worldwide life science patents, www.lifequestlive.com. We used technologies including Solr, Cassandra, Activemq, Java, Java Avro, Groovy/Grails, Tomcat, Zookeeper, Maven.
Boston, MA, US
* Released a new technology platform that helps researchers mine, manage, and share their sequence data.* Released GenomeQuest developer APIs* Increased system scalability by providing distributed computing support to all NGS analyses, allowing jobs to run up to available hardware capacity.* GenomeQuest became a mission-critical system in 16 of the top 20.
Boston, MA, US
* Took over the GenomeQuest product at its infancy, leading a small team to re-engineer it into a commercial grade software product, using LAMP stack.* Set up software engineering best practices, including a series of tools and procedures to manage software life cycle: bug tracking, internal developer documentation, source code version control, automated.
* "Top 25% performer" of the company; Highest rating in annual review for productivity.* Developed Laboratory Information Management System (LIMS) that enables the in-house high-throughput screening efforts.* Developed integrated genetic sequence analysis pipeline, From raw sequencing output (chromatograms) to informative scientific reports. Improved the.
* Develop Java web application and Oracle database to power an online exchange market for life science licensing opportunities.* SQL, stored procedure, and database performance tuning. Cut down the response time by 20% in one instance.* Java, Oracle, Applet, Java Swing, PL/SQL, Servlet, JSP, Weblogic, EJB, XML, XSLT, Visual Cafe, Ant build tool.
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Jun Wan works for Amazon.
Jun Wan is listed as Builder, Deep Learning and LLM at Amazon.
AeroLeads has found 1 work email signal at @genomequest.com for Jun Wan at Amazon.
AeroLeads has found 2 phone signal(s) with area code 844, 508 for Jun Wan at Amazon.
Jun Wan is based in Cambridge, Massachusetts, United States while working with Amazon.
Jun Wan has worked for Amazon, Jobcase, Inc., Sunquest Information Systems, Gq Life Sciences (Formerly Genomequest), and Phylos.
You can use AeroLeads to view verified contact signals for Jun Wan at Amazon, including work email, phone, and LinkedIn data when available.
Jun Wan holds Master Of Science - Ms, Computer Science from Umass Boston.
Jun Wan is listed with skills including Software Development, Perl, Bioinformatics, Agile Methodologies, Databases, Linux, Genomics, and Software Design.
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