Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...
Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...
Machine Learning Engineer
Parkersburg, WV · On-site
Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...
Machine Learning Engineer
Parkersburg, WV · On-site
Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...
Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face. * Proficiency in designing and deploying machine learning models, particularly in ...
Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face. * Proficiency in designing and deploying machine learning models, particularly in ...
Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face. * Proficiency in designing and deploying machine learning models, particularly in ...
Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face. * Proficiency in designing and deploying machine learning models, particularly in ...
Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research communities ...
Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research communities ...
Research Intern on Generative and Protective AI for Content Creation
Parkersburg, WV · On-site +1
$50/hr
Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research communities ...
Research Intern on Generative and Protective AI for Content Creation
Parkersburg, WV · On-site +1
$50/hr
Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research communities ...
Pytorch Developer information
What is a PyTorch developer?
What are the key skills and qualifications needed to thrive as a PyTorch developer, and why are they important?
What is the difference between Pytorch Developer vs Machine Learning Engineer?
| Aspect | Pytorch Developer | Machine Learning Engineer |
|---|---|---|
| Required Credentials | Bachelor's or higher in CS, experience with PyTorch | Bachelor's or higher in CS, data science, or related field, with ML experience |
| Work Environment | Research labs, AI startups, tech companies focusing on deep learning | Tech companies, finance, healthcare, often involving deployment and scaling ML models |
| Industry Usage | Primarily in AI research and development teams | Across industries implementing ML solutions in production |
While both roles require knowledge of machine learning and experience with PyTorch, a Pytorch Developer mainly focuses on developing and optimizing deep learning models using PyTorch. A Machine Learning Engineer often has a broader scope, including deploying, maintaining, and scaling ML models across various platforms and industries.
What are some common challenges PyTorch developers face when deploying machine learning models to production environments?
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Full-time
Re-posted 21 days ago
Job description
About Us
We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.
We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.
What You'll Be Working On
You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.
Must-Have Skills
3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production
Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)
Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior
Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives
Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)
Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination