Staff Machine Learning Engineer
At a glance
Senior Machine Learning Engineering role at Bjak. Remote, United States · full-time · no salary stated · we estimate $180,000–$246,250 across the United States.
Bjak has not published a salary for this role. The figure below is our estimate, not theirs.
remoteroles summary, based on the employer's posting.
What you'll do
- Build ML systems from data preparation and model training through evaluation, serving and deployment
- Create pipelines to train and fine-tune large language models, then assess their quality and reliability
- Improve inference speed, throughput, GPU use and operating cost
- Prepare and validate datasets, then keep production models and infrastructure running through monitoring and troubleshooting
- Set technical direction, review designs and code, and work with research and application teams on production model quality
What you bring
- At least eight years building software or ML systems, including machine learning used in production
- Strong Python skills and practical use of PyTorch or JAX
- Experience training, adapting and evaluating large machine learning models
- Background operating GPU-based training or inference and understanding distributed computing, data pipelines and ML infrastructure
- Ability to shape ML architecture, solve complex production problems and provide technical guidance to ML engineers
Who this fits
This senior role suits an experienced ML engineer who can combine hands-on production work with technical leadership. The position is remote in the United States.
From the employer
About the Role
There are over 5 billion users using basic applications today such email, notes, tasks, calendar and they're not AI-native. Our mission is to build proactive applications for anyone in the world, who are not used to complex prompting. We aim to bring intelligence to conversations, errands, organising and workflows, with minimal to no prompting.
Our first application is an agent-first mobile communication app. We believe building applications that users use daily for communication, coordination and collaboration needs will help integrate AI into their lives. The net effect is to eliminate misinformation, achieve low coordination costs, enable high quality tasks and collaboration at scale with minimal or little prompting.
Role
Design and build ML systems covering data processing, model training, evaluation, inference and deployment
Develop training and fine-tuning pipelines for large language models
Build evaluation frameworks to measure model quality, reliability and performance
Optimise inference systems for latency, throughput, GPU utilisation and cost
Develop data pipelines for collecting, processing and validating training and evaluation datasets
Deploy, monitor and troubleshoot ML models and infrastructure in production
Make architecture decisions and guide engineers through technical design and code reviews
Work with research and application engineering teams to improve model performance in production
Requirements
8+ years of software engineering or machine learning engineering experience, including production ML systems
Strong Python programming skills and hands-on experience with PyTorch or JAX
Experience training, fine-tuning and evaluating large machine learning models
Experience building and operating GPU-based training or inference systems
Strong understanding of distributed computing, data pipelines and ML infrastructure
Experience optimising model performance, inference latency and resource utilisation
Ability to design ML system architecture, review code and resolve complex production issues
Experience providing technical leadership to ML engineers
Nice to Have
Experience with large language models, transformers and distributed model training
Experience with inference frameworks such as vLLM or TensorRT-LLM
Experience with synthetic data generation, data curation and model evaluation pipelines
Experience deploying ML systems for consumer applications
Machine Learning Engineering work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
Machine Learning EngineeringRemote
Find me workBy the team behind remoteroles.