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Internship Aws Machine Learning Jobs in Kansas (NOW HIRING)

Accenture

Lead AI / ML Engineer

Overland Park, KS · On-site

$101K - $133K/yr

Developing and deploying machine learning models and AI solutions. At least 2 from the following ... Understanding and working knowledge of cloud services and platforms (e.g., AWS, Azure, Google Cloud ...

SolvdUS, Inc

Director of Data Engineering

Lenexa, KS · On-site +1

Implement and maintain infrastructure as code using AWS CloudFormation * Ensure deployments, monitoring, and operational processes are automated and repeatable * Support AI and machine learning ...

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AI Data Strategy Engineer / Applied Scientist, LLM Data

Propio

Overland Park, KS • On-site

Other

Re-posted 4 days ago

Propio rating

6.1

Company rating: 6.1 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

367th of 485 rated business services

Job description

Description

Propio Language Services is a provider of the highest quality interpretation, translation, and localization services. Our people take pride in every resource we offer, and our users always have access to cutting-edge technology, exceptional support, and collaborative user experiences. We are driven by our passion for innovation, growth, and bridging communication gaps in a diverse world. If you're passionate about delivering technology-driven solutions and building lasting client relationships while contributing to client growth, Propio could be the ideal place for you.


We are building AI-powered systems that enhance multilingual communication, improve interpreter workflows, and support next-generation AI applications across text, speech, and multimodal experiences.


Propio is hiring an AI Data Strategy Engineer / Applied Scientist, LLM Data to own the data strategy, curation pipelines, annotation workflows, and evaluation datasets that power our multilingual AI systems.


This is a hands-on technical role for someone who understands how to manage the full AI data lifecycle, from acquisition, curation, annotation, and quality control to evaluation datasets and post-training data, to directly improve model performance.


The ideal candidate can build scalable data pipelines, design high-quality annotation and QA processes, identify model failure modes, and close performance gaps through targeted data acquisition, curation, and synthetic data generation.


Key Responsibilities:

  • Define the end-to-end data roadmap for multilingual and multimodal AI systems, including text, speech, translation, interpretation, low-resource languages, and agentic AI workflows.
  • Design and build dataset curation pipelines for training, post-training, and evaluation, including cleaning, deduplication, filtering, PII redaction, quality scoring, sampling, balancing, and versioning.
  • Create annotation schemas, labeling guidelines, QA rubrics, golden datasets, and reviewer workflows for multilingual, speech, translation, and agentic AI data.
  • Build evaluation datasets and benchmarks, analyze model failure modes, and translate performance gaps into targeted data improvements.
  • Support post-training data workflows such as SFT, instruction tuning, preference data, RLHF/DPO-style data, reward model data, and synthetic data generation.
  • Use modern annotation tools and AWS-based data infrastructure to scale secure, traceable, and compliant AI data workflows.


Requirements


  • Bachelor's degree in Computer Science, Machine Learning, Data Science, Computational Linguistics, Linguistics, Statistics, or a related field, or equivalent practical experience. 
  • 4+ years of experience in AI data, ML data operations, NLP data engineering, applied ML, speech/translation data, or LLM data workflows. 
  • Strong hands-on experience with Python, SQL, and dataset curation pipelines. 
  • Experience with annotation workflows, QA rubrics, evaluation datasets, or human-in-the-loop data processes. 
  • Familiarity with multilingual NLP, speech data, translation data, low-resource languages, conversational AI, or agentic AI datasets. 
  • Working knowledge of AWS data and ML tools such as S3, Glue, SageMaker, Bedrock, Lambda, Step Functions, EKS/ECS, IAM, or KMS. 
  • Strong communication skills and ability to work with ML engineers, applied scientists, product teams, linguists, data teams, and vendors. 

Preferred Qualifications

  • Master's or PhD in Computer Science, Machine Learning, NLP, Computational Linguistics, Data Science, Statistics, or a related field. 
  • Experience with LLM post-training workflows such as SFT, instruction tuning, preference data, RLHF, DPO, reward modeling, or evaluation data generation. 
  • Experience with synthetic data generation, active learning, weak supervision, LLM-as-judge workflows, or automated data quality scoring. 
  • Experience with modern annotation and data platforms such as Labelbox, Scale AI, Prodigy, Argilla, Snorkel, Humanloop, or custom internal tooling.  


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