Skills: Machine Learning, Research Engineering, Experiment Design, Deep Learning, Computer Vision, NLP, CV, Cloud Computing, Demand Forecasting, Propensity Modeling, MLOps.
Bio:
Hi! I am a software engineer who has worked in ML engineering and data science for the past five years. I have previously worked on pricing, recommendation systems, CV & NLP classifiers, propensity models, experiment design, and A/B tests; setting up training environments in research settings and translating research code into production pipelines. I've also been involved in setting up MLOps infra - CI/CD, data preprocessing, retraining, and inference pipelines, logging, and model monitoring.
Am open to fully remote positions, either in the US or UK/Europe time zones. Should I work on US time zones, I plan to relocate to align with Eastern time.
This app is very cool! In walkie talkie mode, you may want to tweak the UI to make it clearer when the microphone is listening and when it's not. I saw the microphone icon changes color, but a stronger visual hue may help. Google translate may be a good point of reference - in its conversation mode the shape of the microphone icon changes when the mic is active. I've also noticed that my message is sometimes cut short when translated, it only translates the first half.
AGI safety from first principles [1] is a good write-up.
You can read more about instrumental convergence, reward misspecification, goal mis-generalization and inner misalignment, which are some specific problems AI Safety people care about, by glossing through the curricula of the AI Alignment Course [2], which provides pointers to several relevant blogposts and papers about these topics.
AGI safety from first principles [1] is a good write-up.
You can read more about instrumental convergence, reward misspecification, goal mis-generalization and inner misalignment, which are some specific problems AI Safety people care about, by glossing through the curricula of the AI Alignment Course [2], which provides pointers to several relevant blogposts and papers about these topics.
Location: London, UK
Remote: Yes
Willing to relocate: No
Résumé/CV: https://drive.google.com/file/d/1RKujIZVQiBm1zPw8sUvOK7HFE89...
Email: ssosarippe at gmail dot com
LinkedIn: https://www.linkedin.com/in/-sebastian-sosa/
Technologies: Python, PyTorch, Ray, sklearn, Pandas, SQL, Docker, GCP, FastAPI
Skills: Machine Learning, Research Engineering, Experiment Design, Deep Learning, Computer Vision, NLP, CV, Cloud Computing, Demand Forecasting, Propensity Modeling, MLOps.
Bio: Hi! I am a software engineer who has worked in ML engineering and data science for the past five years. I have previously worked on pricing, recommendation systems, CV & NLP classifiers, propensity models, experiment design, and A/B tests; setting up training environments in research settings and translating research code into production pipelines. I've also been involved in setting up MLOps infra - CI/CD, data preprocessing, retraining, and inference pipelines, logging, and model monitoring.
Am open to fully remote positions, either in the US or UK/Europe time zones. Should I work on US time zones, I plan to relocate to align with Eastern time.