菲利普Boltuzic
验证专家 in 工程
机器学习工程师和开发人员
Filip is a machine learning engineer with several years of professional experience. He's worked on large-scale problems at Amazon Web服务 as a software developer and built natural language processing models as a research associate at the University of Zagreb. Filip's main interests are machine learning and natural language processing, 重点是建立文本分类模型.
Portfolio
Experience
Availability
首选的环境
Java, Git, Linux, Docker, Apache Solr, Django, PyTorch, Pandas, NumPy, Scikit-learn, Python
最神奇的...
...machine learning model I've developed was an LSTM and CRF model to segment text into argumentative claims as part of my Ph.D. thesis.
工作经验
研究顾问
在线自由职业机构
- 调查、研究和记录软件中的缓存方法.
- Reproduced the most popular caching methods for predicting time-to-live from research papers.
- Built a simulator and reinforcement learning model which tries to solve TTL prediction for object caching.
AI和ML开发人员
Aggieland软件公司
- Developed a large language model (LLM) LangChain bot to generate software requirements.
- Built and deployed to the cloud a multi-process application exposed via an API that can chat with a user to generate software requirements.
- Collaborated with two teams to integrate the LLM app via APIs to provide both web and mobile application access to the LLM app.
AI Expert
PD4 Solutions LLC
- Developed an LLM-based solution to determine which scientific articles are related to user-inputted free-text criteria.
- Evaluated the LLM solution performance and demonstrated metrics proving considerable improvement over the previously implemented solution.
- Worked with ML engineers to deploy solutions and define an optimal architecture for applying the LLM solution.
高级数据科学家
Lionbridge自由撰稿人(通过Newfire Global Partners)
- Developed a machine learning sequence labeling model on text data that achieved above 0.9 F1 score.
- Decreased inference time on a previously developed machine learning model without sacrificing their F1 score.
- Used PySpark and Databricks to perform a large-scale data analysis that the company employed to drive future business decisions.
- Developed multiple highly scalable Python web services that are currently serving production traffic.
数据科学工程师
BJS
- Developed prototype product recommenders which showed customer purchasing patterns.
- 构建简单的AWS Lambda函数来执行ETL工作流.
- Worked with PySpark on large sets of data (>100GB of historical purchases).
机器学习工程师
Alchemy V Ltd(通过Toptal)
- Created a marketing slogan text generator using 拥抱的脸 transformers/text generation pipelines and customer-provided data.
- Created a data ingestion and reporting process via multiple Google Cloud services: BigQuery, 云计算功能, 云终端, 和Dataproc.
- 将现有的R报告代码移植到Python web服务中.
自然语言处理顾问
格兰维尔知识管理(通过Toptal)
- 开发了一个刮板下载一个大型(约20,000) and diverse legal documents (1990 until today) from a European public repository.
- Used machine learning to build a text classification model to automatically classify categories based on document content.
- Created a dataset of legal documents and used it to train and evaluate the built machine learning text classification model. Shared results via Google collab such that customers can interactively try the model performance with their held-out data.
研究助理
萨格勒布大学的实验室
- 开发了克罗地亚法律文件的搜索引擎.
- Built a named entity recognition model in PyTorch by combining LSTM with a CRF.
- Mentored several students doing intern projects and wrote my master thesis on natural language processing.
软件开发工程师
亚马逊网络服务(AWS)
- Contributed to developing a scalable time-series database solution in Java and C++, 它每秒处理大约100万个请求.
- 担任团队scrum主管和产品负责人.
- Designed and implemented a network correlation engine microservice to handle networking events from the entire Amazon network (patent award http://patents.justia.com/inventor/filip-boltuzic).
商业智能分析师
萨格勒巴卡联合信贷银行集团
- Developed SQL reports to determine the promising retail strategies in a data warehouse.
- Built an interactive tool in Java to speed up the processes in Oracle Data Integrator.
- Developed small web applications for the accounting department, using PL/SQL and Oracle Apex.
Experience
克罗地亚法律文件搜索引擎
I was the lead developer on this project and proposed the system's architecture as a set of microservices. 文档在Solr中存储和索引, whereas the Django front end served requests and communicated with Solr.
零售额预测
Skills
Other
自然语言处理(NLP), GPT, 生成预训练变压器(GPT), 人工智能(AI), 机器学习, Back-end, OpenAI GPT-3 API, 数据分析, Azure砖, 检索增强生成(RAG), 聚类算法, 聚类, 分类算法, 文本分类, Torch, 网页抓取, 谷歌合作实验室(Colab), 谷歌BigQuery, 文本生成, Web服务, 开放神经网络交换(ONNX), 神经网络, Research, 学生参与, 监督式机器学习, 时间序列, 自回归综合移动平均线(ARIMA), LangChain, OpenAI, 强化学习, 深度强化学习, Algorithms, 编程, Heuristics, 优化, 进化计算, 遗传算法, 卷积神经网络(CNN), 排序算法, 模式识别, 语言模型, 无监督学习, Big Data, 非结构化数据分析, 大型语言模型(llm), Llama 2, FastAPI, 提示工程, OpenAI GPT-4 API
Languages
Python, SQL, Haskell, Java, c++， R
库/ api
Scikit-learn, NumPy, Pandas, PyTorch, 谷歌云API, SpaCy, 自然语言工具包(NLTK), PySpark, LSTM, Spark ML
Tools
Vim Text Editor, Solr, Apache Solr, Git, Oh My Zsh, Boto, Jupyter, LaTeX, Azure机器学习
Paradigms
数据科学, Anomaly Detection, Agile, Scrum, Business Intelligence (BI)
Platforms
亚马逊网络服务(AWS)、Linux、Docker、Databricks、SolrCloud
Frameworks
Django, Scrapy
Storage
Elasticsearch, Google Cloud, JSON
Education
Ph.D. 自然语言处理专业
萨格勒布大学-萨格勒布，克罗地亚
计算机科学硕士学位
萨格勒布大学-萨格勒布，克罗地亚
伊拉斯谟计算机科学交流学习
KTH皇家理工学院-斯德哥尔摩，瑞典
计算机科学学士学位
萨格勒布大学-萨格勒布，克罗地亚
认证
卷积神经网络
Coursera
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