Senior Machine Learning Engineer - California, United States - Acceler8 Talent

Description

About Us:

Your journey as a Senior ML Engineer is not just about engineering; it's about pioneering. You will spearhead the development of novel software systems designed to empower data scientists and engineers across the spectrum. Your mission will be to diagnose and rectify the crux of dataset issues, ultimately amplifying the intrinsic value of data through cutting-edge Generative AI technology.

The Role:

Embrace the challenge of working with diverse datasets, including text, structured/tabular, and image/video, sourced from varied industries. Your work will lay the foundation for large-scale modeling infrastructure within a startup environment poised for explosive growth—from zero to one.

Key Responsibilities:

• Erect robust cloud infrastructure tailored for ML projects spanning a rich variety of datasets.
• Spearhead large-scale Data/AI initiatives with enterprise customers, steering projects from concept to production.
• Take charge as an individual contributor tech lead in a dynamic ML team, driving innovation and operational excellence.
• Employ algorithmic ingenuity to enhance datasets, tapping into the latest advancements in Foundation models.

Your Expertise:

This Senior ML Engineer position demands a seasoned professional with no less than 5 years of concentrated experience in ML. Beyond academics, your experience should be steeped in the real-world rigors of machine learning infrastructure, encompassing vast datasets, steadfast model serving, and comprehensive cloud infrastructure management. Your toolkit includes:

• Python mastery, with fluency in pandas, scikit-learn, numpy, and Jupyter.
• Expertise in PyTorch/PyTorch Lightning, Hugging Face, and relational databases.
• Proficiency in AWS, Docker, and Git, coupled with CI/Testing practices such as Jenkins.

What Sets You Apart:

• A PhD in Machine Learning.
• A track record of significant research publications or contributions to open source.
• Experience with Sagemaker, MLflow, Ray.
• Proficiency with ELT tools, data cleaning tools, and data-centric AI tools like Cleanlab or LangChain and LLMOps stack.

Keywords: Data-Centric AI, Generative AI, Large Language Models, MLOps, Cloud Infrastructure, Python, PyTorch, Hugging Face, AWS, Docker, Git, Jenkins, Sagemaker, MLflow, Ray, Data Cleaning, Foundation Model, Sagemaker, Vertex AI