Member of Technical Staff, Model Training
Own the training pipeline for search and agent models, building from product usage data through fine-tuning and evaluation to production deployment. Requires deep expertise in transformer fine-tuning, data curation, and training models for ranking, retrieval, and agent behavior.
About the job
Responsibilities
- Own the training pipeline behind the models that power Parallel’s search stack and agents
- Build rankers, classifiers, and query models that surface the right information for search
- Develop models that help agents plan, reason, and execute high-value tasks over web data
- Build the path from real product usage to high-quality training data
- Fine-tune and evaluate models rigorously
- Ship models safely to traffic used by millions
Requirements
- Deep intuition on modern models and training, including transformer fine-tuning, data curation, and label quality
- Rigorous thinking about how ranking, retrieval, and agent behavior inform one another
- Ability to train models that serve ranking, retrieval, and agent use cases
- Passion for applying research to product and systems used by millions
Skills
Transformer Fine-Tuning, Data Curation, Model Evaluation, Ranking Models, Retrieval Models, Agent Behavior Modeling, Label Quality
Similar jobs
ML Engineering jobs
LangChain
New York, NYBuild and teach reliable AI agent systems through customer workshops, technical content, guidance, and reference implementations. The role requires strong Python and agent-development experience plus a background delivering customer-facing technical training.
Roboflow
San Francisco, CA
Build reinforcement-learning environments, evaluations, datasets, and scalable infrastructure for frontier AI capabilities. The role suits a high-agency generalist engineer with experience in agents, evaluations, or RL workflows and strong communication skills.
Beacon Biosignals
Boston, MADevelop and productionize machine- and deep-learning algorithms for biosignal and EEG data used in medical devices, clinical development, and diagnostics. The role requires 4+ years of industry experience, DSP and statistics expertise, PyTorch proficiency, and familiarity with regulated environments and production ML practices.
Applied Intuition
Sunnyvale, CA
Develop and deploy ML-first behavior prediction and planning systems for autonomous vehicles, forecasting the motion and interactions of road users. Requires a bachelor's degree, deep learning lifecycle expertise, and at least three years of production software experience with C++ or Python.
Fab2
Austin, TXBuild the AI platform behind fab2, including model infrastructure, agent systems, evaluations, and tools for engineering and fab operations. The role requires strong production software engineering skills and comfort working across frontend, backend, infrastructure, and data.