M
M Rizly
About
Detail
Farmingdale, New York, United States
Contact M regarding:
Flexible work
Starting at
USD65/hour
Résumé
Jobs
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- mSenior Machine Learning EngineermCards IncFeb 2024 - Current (2 years 4 months)• Built several GenAI Applications using both closed source LLMs as well as open source LLMs in Entity Extractions, Q&A, Data Analysis, Code Generation, Content Generation, Intent Detection etc. • Successfully delivered 30+ PoCs and 10+ MVPs in domain of GenAI, Computer Vision and NLP. • Standardized CI/CD and IaC with Terraform on SageMaker and EKS. • Set up model observability and drift detection using LangSmith. • Led a team of 10 ML engineers and provided expert guidance and mentorship. • Built Airflow and Kafka data pipelines for feature engineering, training, and experimentation. • Created a deep learning model for credit risk assessment, improving accuracy by 30% compared to traditional methods. • Built LLM evaluation pipelines using
- IGenerative AI EngineerImutoJul 2020 - Dec 2023 (3 years 6 months)• Spearheaded the creation of a large-scale page graph system to enhance web search quality, improving document relevance and search engine efficiency for millions of queries per second. • Leveraged TensorFlow and Keras to develop deep learning models, resulting in a 40% acceleration in model training times. • Designed an enhanced fraud detection system using ensemble learning methods, which reduced false positives by 20% and saved the company over $5M in potential fraud losses per year. • Contributed to the optimization of entity sparse representations and enhanced the health of recommendation systems, improving user engagement and overall recommendation quality. • Designed LangChain agentic workflows for a healthcare client, saving an est
Machine Learning EngineerEnvoyNov 2016 - Jun 2020 (3 years 8 months)• Conducted A/B tests on machine learning models in production, resulting in a 30% improvement in model performance and a 10% increase in conversion rates for the marketing team. • Developed CNN models for medical MRI and CT scan analysis, achieving 95.7% validation accuracy. • Designed and maintained RAG search infrastructure using FAISS and Pinecone. • Utilized Python and SQL for data analysis and machine learning model creation, increasing efficiency by 30%.
Education
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- UBachelor of Science, Computer ScienceUniversity of Engineering and Technology (UET)Sep 2012 - Jun 2016 (3 years 10 months)