What do we want you to do:
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 such as architecture, tooling, and best practices
Provide technical mentorship to the larger ML Subject Matter Expert community
What would help make your case:
6 10 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
[Preferred] Experience working with Apache Spark to process large-scale distributed datasets
[Preferred] Experience working with the Databricks platform
[Preferred] 4+ years 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.
Disclaimer : This job posting has been aggregated from external source. Role detailscontentand availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
📌 Ml Architect Hyderabad
🏢 DataNimbus
📍 Hyderabad
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