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Senior ML Engineer

  • Posted 16 days ago
  • Be among the first 10 applicants

Job Description

Responsibilities

  • Build and increase customer data science workloads and apply the best MLOps to productionize these workloads across a variety of domains.
  • Develop LLM solutions on customer data such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, and content generation.
  • Advise data teams on several data science topics such as architecture, tooling, and best practices.
  • Provide technical mentorship to the larger ML Subject Matter Expert community.

Requirements

  • 6 years of hands-on industry data science experience, using typical machine learning and data science tools including pandas, MLflow, scikit-learn, gensim, nltk, and TensorFlow/PyTorch.
  • Experience building production-grade machine learning deployments on AWS, Azure, or GCP, including drift monitoring.
  • Experience with the latest techniques in natural language processing including vector databases, fine-tuning LLMs, and deploying LLMs with tools such as HuggingFace, LangChain, and OpenAI.
  • Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research) or equivalent practical experience.
  • Experience communicating and teaching technical concepts to non-technical and technical audiences alike.
  • Passion for collaboration, life-long learning, and driving value through ML.
  • Experience working with Apache Spark to process large-scale distributed datasets.
  • Experience working with the Databricks platform.
  • 5+ years of customer-facing experience in a pre-sales or post-sales role.
  • Can meet expectations for technical training and role-specific outcomes within 3 months of hire.

This job was posted by Nitya Raj from DataNimbus.

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About Company

Job ID: 152033231

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