Emburse

Senior AI Engineer

Emburse

full-time

Posted on:

Origin:  • 🇺🇸 United States • Massachusetts

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Job Level

Senior

Tech Stack

KerasOpen SourcePySparkPythonPyTorchReactScalaSDLCSparkSQLTableauTensorflow

About the role

  • Design, develop, and deploy AI solutions to automate expense and invoice management processes and solve complex optimization problems
  • Build and train machine learning models, develop algorithms, and integrate AI systems into existing software and infrastructure
  • Translate product design requirements into pipeline of heuristic and stochastic algorithms
  • Perform exploratory data analysis for product feasibility studies and ground truth testing
  • Execute SQL queries and/or python scripts to manipulate, analyze and visualize data
  • Implement explainable AI solutions and rationalize model inferences
  • Follow SDLC processes, adopt agile-based processes/meetings and peer code-reviews
  • Work with machine learning engineer/architect to deploy data products into production
  • Follow and understand legal data use restrictions
  • Contribute to algorithm library development and design for ML, NLP and XAI
  • Deliver product pipelines for deployment to production
  • Build applications that integrate third party and self-hosted foundation models
  • Fine tune open source foundation models (LLMs, VLMs) with proprietary data
  • Develop autonomous AI inference and tool use orchestration using ReAct AI agents
  • Provide root cause analysis for machine learning model inference
  • Complete data analysis or processing tasks as directed and document data product end to end design and development
  • Perform data annotation, labeling and other related data generation activities
  • Provide thought leadership, present data product updates and trainings, mentor and lead others as project lead

Requirements

  • BS in Statistics, Mathematics, Computer Science or another quantitative field (Graduate degree preferred)
  • At least 6 years experience manipulating data sets and building GLM/regression models, ensemble decision trees and neural networks
  • Demonstrated hands-on experience with foundation models, GenAI and agents (1-2 years ideal)
  • 6+ years of experience developing data science products
  • Strong experience using and optimizing common python machine and deep learning libraries such as Scikit learn, PyTorch, TensorFlow, Keras, MXNet and Spark MLlib
  • Experience using statistical computer languages (Python, R, Scala, SQL, etc.) to manipulate data and draw insights from large data sets
  • Hands-on generative AI development Experience using foundation models (LLMs, VLMs)
  • Experience with model fine tuning of open source foundation models with proprietary data
  • Experience leveraging AI metrics for monitoring and value tracking
  • Knowledge of AI Agent frameworks with recent hands-on experience building an AI agent able to autonomously use data stores, tools and other AI models to solve inquiries
  • Deep knowledge of data science concepts and related product development lifecycle
  • Working knowledge of machine learning tuning optimization procedures
  • Experience working with and creating data architectures
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.)
  • Excellent written and verbal communication skills for coordinating across teams
  • A drive to learn and master new technologies and techniques
  • Preferred: Experience with big data analytical frameworks such as Spark/PySpark
  • Preferred: Experience analyzing data from 3rd party providers: Google Knowledge Graph, Wikidata, etc.
  • Preferred: Experience visualizing/presenting data for stakeholders using: Looker, PowerBI, Tableau, etc.
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