Staff Software Engineer, Machine Learning (Safety) San Francisco, CA

ESR Healthcare; San Francisco (CA); On-site; USD 272,000 - 306,000; Full time

Job summary

A leading technology company is looking for a Staff Software Engineer specializing in Machine Learning Safety to lead the Safety ML team. Candidates should have over 5 years of experience in ML engineering, including 2 years focusing on Trust & Safety. The role involves guiding technical strategy, collaborating cross-functionally, and developing high-impact ML solutions to improve platform safety. This full-time position offers a competitive salary ranging from $272,000 to $306,000 along with equity and benefits.

Qualifications

• 5+ years of experience in ML engineering or applied ML roles.
• 2+ years of experience in applying ML in Trust & Safety.
• Ability to develop scalable ML systems and manage projects from ideation to production.

Responsibilities

• Serve as technical lead and mentor for the Safety ML team.
• Drive the team's technical strategy and roadmap.
• Collaborate across functions to enhance safety solutions.

Skills

Machine Learning Engineering

Python programming

Collaboration

Creativity in problem-solving

Education

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics or related field

Tools

PyTorch

JAX

TensorFlow

Job description

Staff Software Engineer, Machine Learning (Safety)

San Francisco, CA

Overview

We are seeking an accomplished and experienced Staff Machine Learning Engineer – Safety ML to join our dynamic team. As a technical lead of the Safety ML team, you will be responsible for designing, developing, and maintaining our data and AI/ML infrastructure and services. You will collaborate with cross‑functional teams, including data scientists, software engineers, MLEs and product managers, to deliver modern and cutting‑edge solutions that improve safety on the platform. This role reports to the Senior Manager of Machine Learning, Safety.

What You’ll Be Doing

• Serve as the team’s technical lead and mentor, guiding ICs through design, experimentation, and implementation while raising the technical bar.
• Define and drive the Safety ML team’s technical strategy and roadmap.
• Set the bar in technical reviews, including code, design, and architecture, ensuring the team builds scalable, robust, and high‑quality ML systems.
• Collaborate cross‑functionally with product, data science, policy, legal, and engineering partners to align on safety goals and deliver effective solutions.
• Tackle the most complex and high‑impact challenges in safety, including adversarial abuse, harmful content detection, and evolving threat vectors.
• Develop cutting‑edge safety techniques, applying state‑of‑the‑art ML to detect and prevent harm while staying ahead of emerging abuse patterns.
• Influence the company’s direction on safety, clearly communicating trade‑offs and technical constraints to senior leadership and stakeholders.

What You Should Have

• 5+ years of experience in ML engineering or applied ML roles.
• 2+ years of experience applying ML in Trust & Safety to counter adversarial actors.
• Strong coding skills in Python and fluency in ML frameworks such as PyTorch, JAX, or TensorFlow.
• Proven experience building performant machine learning systems at scale and having driven the execution of large, impactful projects from ideation to production.
• Ability to think from first principles, approaching complex problems with creativity, clear reasoning, and pragmatic solutions.
• A growth mindset: seeking feedback, reflecting on decisions, and continuously improving.
• Excellent communication and collaboration skills, with a history of partnering effectively across engineering, data science, legal, policy, and product teams.
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, or a related field (Physics, Math, Operations Research, etc.).

Compensation

The US base salary range for this full‑time position is $272,000 to $306,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job‑related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.