Applied ML Engineer (AI)

Location: San Francisco, United States; on-site

Salary: $170,000–$280,000 per year

Company

hirify.global builds a software intelligence product that helps leaders understand how products and codebases evolve, using code as the source of truth.

What you will do

• Build and improve machine learning systems that power core AI capabilities.
• Create and maintain evaluation datasets, benchmarks, labeling strategies, and evaluation methodologies.
• Design experiments, train and fine-tune models, and analyze results to drive product decisions.
• Apply reinforcement learning techniques, including RLHF, RLAIF, GRPO, PPO, and DPO where appropriate.
• Research new methods and stay current with reinforcement learning and open-source model developments.
• Partner with product and backend engineering teams to integrate models into production and build ML pipelines and tooling.

Requirements

• 3+ years of experience in applied machine learning, AI, or related engineering roles.
• Experience building, training, fine-tuning, or evaluating modern ML models in production or research environments.
• Practical experience with reinforcement learning or reinforcement learning for LLMs.
• Strong skills in dataset creation, curation, evaluation, experimentation, and results analysis.
• Familiarity with LLMs, reasoning models, and the open-source model ecosystem.
• Strong software engineering skills and experience building reliable ML pipelines and tooling.

Nice to have

• Experience with Golang, the primary backend language.
• Large-scale distributed training, preference optimization, synthetic data generation, or evaluation frameworks.
• Experience with GCP infrastructure, Temporal, or internal ML tooling.

Culture & Benefits

• Early-stage startup environment with a flat organizational structure and high individual ownership.
• Fast-paced work with evolving priorities and broad responsibility across the product.
• Collaboration with founders, engineering, and product teams.
• Product and infrastructure stack includes TypeScript, React, Golang, Temporal, GCP, Postgres, Terraform, and custom AST code walkers.