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    Machine Learning Engineer - San Francisco, United States - Commit Partnership

    Commit Partnership
    Commit Partnership San Francisco, United States

    2 weeks ago

    Default job background
    Description
    About the company:
    • Company Size - 25 People
    • Approx Funding - $30M
    • Company Stage - Series A
    • Backed by: Databricks Ventures, Bain Capital Ventures, Menlo Ventures
    • Industry - AI, ML, Databases, DCAI
    • Founding year
    • Tech Stack/Technologies: Python, PyTorch, Hugging Face, and LangChain for AI and ML innovation. AWS, Docker, and Git support deployment and collaboration. Jenkins, Sagemaker, MLflow, and Ray enhance continuous integration and scalable computing. Tools for ELT and data cleansing are also integral to the workflow.
    We're looking for a Machine Learning Engineer to:
    • Develop cutting-edge models for a leading AI platform alongside MIT PhDs, who are veterans of the top tech companies in the world.
    • Pioneer novel software systems for the rapidly growing field of data-centric AI. The platform has several tools that automatically find & fix issues in datasets.
    • Use the latest tooling and ML models at a dynamic startup to create the best cloud-based solutions for our current and future customers.
    • Collaborate on interdisciplinary projects, combining ML expertise with software engineering to create innovative solutions for complex data challenges.
    • Contribute to open-source projects and publish research in top ML conferences as you push the boundaries of DCAI.
    • Engage with enterprise customers to understand their data challenges and provide tailored AI solutions.
    What you'll need:
    • A Bachelor's or Master's degree in Computer Science, Engineering, or related field from a highly recognized university.
    • 4+ years of professional software engineering in a fast-paced, product-focused environment developing and deploying ML models.
    • Deep understanding of open-source libraries, frameworks, and systems combined with experience in data pre-processing, feature engineering, model selection, and evaluation.
    • Active GitHub contributions, with projects over 1000 stars or as a main contributor to a notable repo.
    • Expertise with machine learning frameworks such as TensorFlow, Keras, or PyTorch.
    • Previous early-stage employee or founder experience at a venture-backed tech company is strongly preferred.
    • Desire and ability to learn quickly, take professional initiative, and work in a fast-paced environment.
    What you'll get:
    • Competitive Salary with significant equity in an early stage pioneer of DCAI backed by top investors.
    • Comprehensive benefits include premium health insurance, Unlimited PTO, Unlimited Sick Days, Parental leave, and more.
    • Unique travel allowance.
    • Unprecedented career progression opportunities.
    • The opportunity to work with brilliant founders, solving some of the most complex data problems in the world.
    Compensation:
    • $140,000 - $200,000 a year
    • Compensation is salary + meaningful equity in an early stage venture backed startup commensurate with experience.
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