Moscow, ID · On-site
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Moscow, ID · On-site
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Pocatello, ID · On-site
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Pocatello, ID · On-site
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Meridian, ID · On-site
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Meridian, ID · On-site
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Boise, ID · On-site
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Boise, ID · On-site
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Rexburg, ID · On-site
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Rexburg, ID · On-site
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Nampa, ID · On-site
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Nampa, ID · On-site
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Idaho Falls, ID · On-site
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Idaho Falls, ID · On-site
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
| Aspect | Senior Full Stack Machine Learning Engineer | Data Scientist |
|---|---|---|
| Credentials | Bachelor's/Master's in CS, Data Science, or related; experience with ML frameworks | Bachelor's/Master's in Statistics, Data Science, or related; strong analytical skills |
| Work Environment | Develops end-to-end ML applications, integrates backend and frontend | Analyzes data, builds models, visualizes insights |
| Industry Usage | Tech, finance, healthcare, where deploying ML models is essential | Research, analytics, consulting across various sectors |
While both roles involve working with data and machine learning, the Senior Full Stack Machine Learning Engineer focuses on building and deploying complete ML solutions, including frontend and backend integration. In contrast, Data Scientists primarily analyze data and develop models to generate insights. The engineer's role is more application-oriented, whereas the Data Scientist's role is more research and analysis-focused.
Moscow, ID • On-site
Full-time
Re-posted 24 days ago
Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch
Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment orchestration
Run and scale training experiments on cloud or HPC (AWS, GCP, SLURM, Ray), and debug throughput, stability, and convergence issues
Build evaluation harnesses and benchmark infrastructure, with held-out sets and contamination controls, so results are trustworthy
Read eval signal and training curves to determine whether a change actually helped, and feed findings back to the research and environment teams
Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics
Implement methods from recent ML papers quickly and turn them into production-grade systems
