Machine Learning Engineer – Co-op

Ancestry

Machine Learning Engineer Co-op developing ML, LLM, and AI-agent solutions for Ancestry, a family-history platform. Optimizing models, MLOps workflows, and intelligent customer experiences.

Posted 8/11/2026part-timeRemote • 🇺🇸 United StatesEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying machine learning and large language models, with a strong focus on optimizing model performance and integrating generative AI technologies. Proficient in building MLOps workflows and collaborating with cross-functional teams to deliver scalable AI solutions.

Highest-signal resume keywords

Machine Learning DevelopmentLarge Language Model IntegrationPython ProficiencyMLOps Workflow DevelopmentGenAI and LLM Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningLarge Language ModelsPythonTensorFlowPyTorchScikit-learnGenAILLM Fine-tuningReinforcement LearningScalable Code Development

Tools & Technologies

Cloud PlatformsML Development ToolsML Deployment ToolsLangChainAutoGenVector DatabasesFAISSPineconeOpenSearchHuggingFace

Industry Keywords

MLOpsModel Inference OptimizationRetrieval-Augmented GenerationAgentic FrameworksData ScienceStatisticsQuantitative Field

Tech Stack

Tools & technologies

CloudJavaNode.jsPythonPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

Develop and deploy machine learning and large language models
Build and optimize AI agents to enhance automation and decision-making
Optimize model inference speed, storage efficiency, and scalability for real-world applications
Develop pipelines and MLOps workflows to streamline model training, evaluation, and deployment
Contribute to ML, LLM, and agent evaluation and monitoring platform
Experiment with new ML, LLM, and agent technologies
Integrate ML and Generative AI models
Enable ML/LLM-powered applications
Collaborate with data scientists, engineers, and product teams on scalable ML solutions

Requirements

What you’ll need

Currently pursuing an advanced degree (Master's or PhD preferred) in Computer Science, Data Science, Statistics, Mathematics, Linguistics, Engineering, or related quantitative field with a strong data focus
Proficient in Python
Familiarity with ML libraries such as TensorFlow, PyTorch, or Scikit-learn
Experience with GenAI, LLMs, and agentic frameworks such as LangChain and AutoGen
Ability to write clean, efficient, and scalable code
Experience with cloud platforms, ML development tools, and ML deployment tools
Active student in a master's or PhD program
Familiarity with NodeJS or Java is nice to have
Familiarity with LLM fine-tuning, retrieval-augmented generation (RAG), vector databases (FAISS, Pinecone, OpenSearch), LLM optimization, VLLM, HuggingFace, or reinforcement learning techniques is nice to have

Benefits

Comp & perks

Location-flexible work approach: work from home, nearest office, or hybrid, subject to location restrictions and role requirements
Reasonable accommodations for qualified individuals with disabilities