Staff ML Engineer: End-to-End Model Training & Deployment

Parallel; San Francisco (CA); On-site; USD 120,000 - 150,000; Full time

Benefits offered by this job

Competitive salary

Generous equity

Visa sponsorships

401K plans

Daily lunch & office snacks

Dinner at the office

Unlimited vacation

Caltrain pass reimbursement

Job summary

Parallel is seeking a professional who will own the training pipeline behind models that support both the search stack and agents. Responsibilities include building pathways from product usage to high-quality training data, rigorously fine-tuning models, and shipping them for high-traffic usage.

The ideal candidate should have a strong grasp of modern training models, especially in the realms of transformer architectures and data curation, ensuring applied research benefits millions of users.

Qualifications

• Deep intuition on modern models and training including transformer fine-tuning.
• Experience with data curation and ensuring label quality.
• Strong understanding of how ranking, retrieval, and agent behavior inform one another.

Responsibilities

• Own the training pipeline behind models for search and agents.
• Build the path from product usage to high-quality training data.
• Fine-tune and evaluate models rigorously, ensuring they are safe for traffic.

Skills

Deep intuition on modern models and training

Transformer fine-tuning

Data curation

Label quality

Understanding of ranking and retrieval

Job description

Parallel is seeking a professional who will own the training pipeline behind models that support both the search stack and agents. Responsibilities include building pathways from product usage to high-quality training data, rigorously fine-tuning models, and shipping them for high-traffic usage.

The ideal candidate should have a strong grasp of modern training models, especially in the realms of transformer architectures and data curation, ensuring applied research benefits millions of users.