Member of Technical Staff, Model Training

Parallel Web Systems; California; On-site; USD 180,000 - 250,000; 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 a web infrastructure company seeking a senior ML engineering role focused on building and maintaining the training pipeline for models powering both search and agent systems. You will drive data curation, model fine-tuning, and rigorous evaluation to ensure high-quality training data for production.

Our team operates fully in-person across our Palo Alto HQ and San Francisco office, collaborating to push the boundaries of large-scale AI systems used by millions of users.

Qualifications

• Deep intuition on modern models and training.
• Experience with transformer fine-tuning, data curation, and label quality.
• Ability to align research with product and systems used by millions.

Responsibilities

• Own the training pipeline behind models powering both search and agent stacks.
• Build paths from real product usage to high-quality training data; fine-tune and evaluate models.
• Ship trained models safely to traffic used by millions.

Skills

Model training

Transformer fine-tuning

Data curation

Label quality

Ranking & retrieval

Agent behavior

Job description

About us

Parallel is a web infrastructure company. Our products are used by leading businesses in sales, marketing, insurance, and coding to build best-in-class AI agents with flexible and powerful programmatic access to the web.

We’ve raised $230 million from Kleiner Perkins, Sequoia, Index Ventures, Spark Capital, Khosla Ventures, First Round, and Terrain to build the web for AIs. We’re currently valued at $2 billion and we’re forming a world-class team of engineers, designers, marketers, sellers, researchers, and operational experts to achieve our mission.

Job: You will own the training pipeline behind the models that power both Parallel’s search stack and Parallel’s agents. On the search side, that means the rankers, classifiers, and query models that surface the right information. On the agent side, that means the models that help our agents plan, reason, and execute high-value tasks over web data. You will build the path from real product usage to high-quality training data, fine-tune and evaluate these models rigorously, and ship them safely to traffic used by millions.

You: Have deep intuition on modern models and training, including transformer fine-tuning, data curation, and the craft of label quality. Think rigorously about how ranking, retrieval, and agent behavior inform one another, and how to train models that serve all three. You care about your research being applied to product and systems that millions use.

Life at Parallel

Our team works fully in-person , between our Palo Alto HQ and San Francisco office. We’re a flat, talent-dense organization dedicated to solving technical and creative problems.

We seek like-minded individuals who share our passion for applying science, creativity, and consistency to big and complex problems with equally big outcomes. These are our values:

• Own customer impact: It’s on us to ensure real-world outcomes for our customers.




• Obsess over craft: Perfect every detail because quality compounds.




• Accelerate change : Ship fast, adapt faster, and move frontier ideas into production.




• Create win-wins : Creatively turn trade-offs into upside.




• Make high-conviction bets : Try and fail. But succeed an unfair amount.

Compensation & benefits

• Competitive salary




• Generous equity




• Visa sponsorships




• 401K plans




• Daily lunch & office snacks




• Dinner at the office




• Unlimited vacation




• Caltrain pass reimbursement