Remote ML Product Engineer - On-Chain AI Pipelines
Ritual
Town of Poland (NY)
Hybrid
USD 120.000 - 180.000
Vollzeit
14 Tage+
Eine vollständige Bewerbung in einer Minute
Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.
Schaffe es an den ATS-Filtern vorbei
Benefits dieser Stelle
Annual discretionary bonus
100% premiums covered on healthcare
Aggressive 401k match
Participation in virtual and in-person events
Zusammenfassung
A pioneering AI infrastructure company is seeking a Machine Learning Product Engineer to work on innovative applied machine learning projects. You will be engaged in automating Data ETL pipelines, deploying ML models, and developing customer-facing products. The ideal candidate has software engineering experience, familiarity with Python and ML frameworks, and an interest in open-source products. Enjoy a highly competitive compensation package, including health benefits and flexibility for remote/hybrid working arrangements.
Qualifikationen
Experience with automation of Data ETL pipelines.
Proven track record in deploying machine learning models.
High level of end-to-end ownership and self-direction.
Aufgaben
Scale model inference and handle predictions at scale.
Design and implement data and ML pipelines throughout the lifecycle.
Collaborate with cross-functional teams on product development.
Kenntnisse
Software engineering experience
Machine learning model serving
Python
PyTorch
TensorFlow
Open-source stacks
DataOps
MLOps
Machine learning architecture
Tools
CUDA
ROCm
TinyML
Triton
HuggingFace
Jobbeschreibung
A pioneering AI infrastructure company is seeking a Machine Learning Product Engineer to work on innovative applied machine learning projects. You will be engaged in automating Data ETL pipelines, deploying ML models, and developing customer-facing products. The ideal candidate has software engineering experience, familiarity with Python and ML frameworks, and an interest in open-source products. Enjoy a highly competitive compensation package, including health benefits and flexibility for remote/hybrid working arrangements.
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