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Machine Learning Engineer Intern - Research

3 hours, 54 minutes ago
United States
Internship
Junior
Machine Learning Engineer
Software Development
Docker Kubernetes LLM Machine Learning MLOps Python PyTorch Statistics Transformers
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Good At Numbers

Good At Numbers

Good At Numbers specializes in utilizing artificial intelligence to convert fragmented business data into comprehensive dashboards and predictive analytics, enabling leaders to make informed decisions swiftly.

Internet Software & Services
View All Jobs 2

Description

  • Design and run experiments across retrieval, ranking, context construction, tool use, grounded generation, evaluation, anomaly detection, forecasting, and optimization workflows.
  • Improve the quality, reliability, latency, and observability of ML and LLM-driven features.
  • Build reproducible evaluation workflows for model behavior, answer quality, grounding, failure analysis, and regression testing.
  • Help productionize research work through pipelines, APIs, services, monitoring, versioning, and deployment workflows.
  • Improve MLOps practices around experiment tracking, prompt and model versioning, dataset versioning, testing, rollout safety, and post-deployment monitoring.
  • Collaborate closely with software and platform engineers to ship ML systems that are measurable and production-ready.
  • Move work from experiments into production code and support the path from research to deployment.
  • Contribute to debugging and validation of model and system behavior using statistics, benchmarking, and error analysis.

Requirements

  • 3–4 years of relevant experience preferred through research labs, internships, startups, open-source work, or production ML systems.
  • Strong software engineering ability and comfort writing production-quality code.
  • Strong Python skills preferred.
  • Experience with machine learning experimentation, evaluation, and debugging preferred.
  • Experience with LLMs, retrieval systems, vector search, ranking, prompt/tool workflows, or agent-style systems preferred.
  • Experience with MLOps practices such as experiment tracking, versioning, model testing, deployment, and monitoring preferred.
  • Comfort with statistics, error analysis, benchmarking, and translating ambiguous research ideas into shippable systems.
  • Strong communication skills and the ability to document tradeoffs, assumptions, and results.
  • Experience with PyTorch, Transformers, or modern ML tooling is a nice to have.
  • Experience with vector databases, RAG systems, or evaluation harnesses is a nice to have.
  • Experience with time-series forecasting, causal analysis, anomaly detection, or optimization systems is a nice to have.
  • Experience with Docker, Kubernetes, cloud infrastructure, or batch/orchestration systems is a nice to have.
  • Publications, benchmark work, or strong public repos/writeups are a nice to have.
  • Applicants must be authorized to work in the United States for the full internship period and based in the U.S. during the internship; visa sponsorship is not available.

Benefits

  • Paid 12-week summer internship from May through July 2026.
  • Compensation of $30/hour.
  • Remote role based in the United States.
  • Full-time schedule of 40 hours per week.

Interested in this position?

Apply directly on the company website

Apply Now

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