Biomedical engineer Jobs in Bathurst, NB
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Biomedical engineer • bathurst nb
Last updated: 3 days ago
As a remote, hourly paid R Engineer, you will review AI-generated responses and generate high-quality R and data-analysis-focused content, evaluating the reasoning quality and step-by-step problem-...Show moreLast updated: 30+ days ago
Electrical Design Engineer or Engineer In Training.BUILD YOUR CAREER AT POWER PRECISION.Power Precision is contributing to the clean energy transition.
The team at Power Precision designs and builds...Show moreLast updated: 30+ days ago
NA Engineering Intern - FLV - Summer 2026.Florenceville- Bristol NB Canada.In every role McCainers are ambitious curious and passionate about creating exceptional work experiences - together.With a...Show moreLast updated: 3 days ago
Remote R Engineer - AI Trainer
SuperAnnotateBathurst, New Brunswick, CARemote
Full-time
Electrical Design Engineer or Engineer In Training
Power PrecisionBathurst, NB, CanadaFull-time
Engineer Internship
McCain FoodsBathurst, New Brunswick, CanadaFull-time +2
- Salmon Arm, BC (from $ 58,886 to $ 235,000 year)
- Niagara Falls, ON (from $ 41,366 to $ 194,036 year)
- Laval, QC (from $ 29,250 to $ 161,860 year)
- Edmonton, AB (from $ 95,590 to $ 156,849 year)
- King City, ON (from $ 38,361 to $ 156,579 year)
- New Westminster, BC (from $ 36,311 to $ 156,531 year)
- New Glasgow, NS (from $ 36,311 to $ 156,531 year)
- Newmarket, ON (from $ 69,994 to $ 152,271 year)
- Kawartha Lakes, ON (from $ 94,107 to $ 147,500 year)
- Mississauga, ON (from $ 56,704 to $ 146,655 year)
Remote R Engineer - AI Trainer
SuperAnnotateBathurst, New Brunswick, CA30+ days ago
Job type
- Full-time
- Remote
Job description2+ years of hands-on experience using R for data analysis, statistics, or data science work. Strong proficiency in R programming, including data wrangling, functional programming patterns, and writing reusable functions or packages. Solid grounding in applied statistics, including regression, inference, and model validation, with practical experience implementing these methods in R. Experience building end-to-end analyses in R that include data cleaning, exploratory analysis, modeling, and visualization. Familiarity with common R ecosystems such as tidyverse, data.table, and ggplot2, and the ability to choose appropriate tools for a given task. Professional experience in a data-focused role such as data scientist, statistician, quantitative analyst, or similar. Minimum Bachelor’s degree in Statistics, Mathematics, Computer Science, or a closely related quantitative field. Significant experience using large language models (LLMs) to assist with coding, analysis design, and code review in R. Excellent English writing skills with the ability to document analyses and explain complex statistical ideas clearly to non-experts. Previous experience with AI data training or model evaluation is strongly preferred, and Minimum C1 English proficiency is required.
As a remote, hourly paid R Engineer, you will review AI-generated responses and generate high-quality R and data-analysis-focused content, evaluating the reasoning quality and step-by-step problem-solving behind each solution. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify errors in statistical methodology or data-wrangling workflows; fact-check analytical results; write expert-level explanations and model solutions that demonstrate correct use of R; and rate and compare multiple AI responses based on correctness and reasoning quality. This contract role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate that provides AI training data for many of the world’s largest AI companies and foundation model labs, directly helping to improve the world’s premier AI models.
Key Responsibilities :
- Develop AI Training Content : Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
- Optimize AI Performance : Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
- Ensure Model Integrity : Test AI models for potential inaccuracies or biases, validating their reliability across use cases.
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