Data / ML infrastructure engineer with experience building production-scale ingestion systems, ML pipelines, validation frameworks, and internal engineering tools.
Currently at Protege, working on healthcare data ingestion and normalization across large EHR and imaging datasets, with Dagster-based orchestration, schema validation, drift monitoring, and production pipeline reliability improvements.
I was previously at Mastercard, where I worked as a machine learning engineer on consumer engagement and merchant-offer forecasting systems: feature pipelines, propensity models, training/inference workflows, Delta Lake migrations, and React/TypeScript dashboards for model performance and production insights.
I’m looking for data engineering, ML platform / ML infrastructure, applied ML engineering, or full-stack roles where the work benefits from strong data/ML systems experience and product-minded engineering.
Outside of work, I like playing guitar, photographing birds, and watching old episodes of Carl Sagan’s Cosmos.
This is incredible! I've seen many recreations of classic software on the web, but the attention to detail and authenticity here surpasses astonishment and enters the orbit of pure, creative insanity. (Atkinson would no doubt be pleased.)
Kudos to you for the time and effort you put into this — and all the more for bringing it to a stage where you could share it with the rest of us. I’d love to read a blog post about this project someday!
I have experience in front-end development and machine learning. I'm looking for a front-end or full-stack role, potentially in a position where I can leverage my DS/ML experience as well. In my current job, I'm building a recommendation system for matching cardholders with personalized merchant reward campaigns. I've also utilized my front-end experience to build internal dashboards for the aggregation and display of model performance metrics.
I have experience in front-end development and machine learning. I'm looking for a front-end or full-stack role, potentially in a position where I can leverage my DS/ML experience as well. In my current job, I'm building a recommendation system for matching cardholders with personalized merchant reward campaigns. I've also utilized my front-end experience to build internal dashboards for the aggregation and display of model performance metrics.
I have experience in front-end development and machine learning. I'm looking for a front-end or full-stack role, potentially in a position where I can leverage my DS/ML experience as well. In my current job, I'm building a recommendation system for matching cardholders with personalized merchant reward campaigns. I've also utilized my front-end experience to build internal dashboards for the aggregation and display of model performance metrics.
I have experience in front-end development and machine learning. I'm looking for a front-end or full-stack role, potentially in a position where I can leverage my DS/ML experience as well. In my current job, I'm building a recommendation system for matching cardholders with personalized merchant reward campaigns. I've also utilized my front-end experience to build internal dashboards for the aggregation and display of model performance metrics.
I have experience in front-end development and machine learning. I'm looking for a front-end or full-stack role, potentially in a position where I can leverage my DS/ML experience as well. In my current job, I'm building a recommendation system for matching cardholders with personalized merchant reward campaigns. I've also utilized my front-end experience to build internal dashboards for the aggregation and display of model performance metrics.
I'm a software engineer with 2 years of experience working in ML and front-end development. I'm looking for a front-end or full-stack role, potentially in a position where I can also leverage my experience in DS/ML.
In my current job, I'm working on a recommender system for matching cardholders with personalized merchant reward campaigns. I've also worked on transaction forecasting, i.e. predicting consumer spend at merchants based on factors such as their historical transactions, seasonal trends, and geolocation. I've also built internal web dashboards to aggregate and display performance metrics from our models.
I also really enjoy working on front-end personal projects. I built Karektar, a web app for designing exportable custom bitmap fonts, which was actually featured on Hacker News (https://news.ycombinator.com/item?id=37629119). I'm also currently working on a faithful recreation of PC Paintbrush -- the Windows 3.0 version of Paint -- on the web (https://github.com/nishanthjayram/paintbrush).
I have experience in front-end development and machine learning. I'm looking for a front-end or full-stack role, potentially in a position where I can leverage my DS/ML experience as well. In my current job, I'm building a recommendation system for matching cardholders with personalized merchant reward campaigns. I've also utilized my front-end experience to build internal dashboards for the aggregation and display of model performance metrics.
I have experience in front-end development and machine learning. I am looking for a front-end or full-stack role, potentially in a position where I can also leverage my background in machine learning and data science. As part of my current job, I'm working on developing a recommendation system for matching customers with personalized, card-linked offers; while leveraging my front-end background to develop internal dashboards to summarize and display model performance metrics.
Remote: Yes; also open to Bay Area hybrid
Willing to relocate: No
Technologies: Python, SQL, PySpark, Dagster, AWS, Delta Lake, PyTorch, TensorFlow, TypeScript, React, PostgreSQL, Snowflake
Résumé/CV: https://newtrino.ink/resume.pdf
LinkedIn: https://www.linkedin.com/in/nishanth-jayram/
Email: [[email protected]](mailto:[email protected])
Data / ML infrastructure engineer with experience building production-scale ingestion systems, ML pipelines, validation frameworks, and internal engineering tools.
Currently at Protege, working on healthcare data ingestion and normalization across large EHR and imaging datasets, with Dagster-based orchestration, schema validation, drift monitoring, and production pipeline reliability improvements.
I was previously at Mastercard, where I worked as a machine learning engineer on consumer engagement and merchant-offer forecasting systems: feature pipelines, propensity models, training/inference workflows, Delta Lake migrations, and React/TypeScript dashboards for model performance and production insights.
I’m looking for data engineering, ML platform / ML infrastructure, applied ML engineering, or full-stack roles where the work benefits from strong data/ML systems experience and product-minded engineering.
Outside of work, I like playing guitar, photographing birds, and watching old episodes of Carl Sagan’s Cosmos.