Applied ML Engineer ($170k-$280k + Equity) at Macroscope

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Job Title

Applied ML Engineer

Salary

$170k-$280k + Equity

Company Description

Macroscope is a San Francisco-based startup building infrastructure for agent-powered software development, backed by Lightspeed, Thrive Capital, and Google Ventures. Founded by repeat exited entrepreneurs from Periscope and Magic Pony, the team is creating tools that allow engineers to direct fleets of agents with automated code review and verification.

Job Description

As an Applied ML Engineer at Macroscope, you will own the machine learning lifecycle for our agentic software development infrastructure. You will focus on training and fine-tuning LLMs using advanced reinforcement learning techniques like GRPO and DPO. By building high-quality evaluation datasets and rigorous benchmarks, you'll drive model improvements that empower engineers with unprecedented leverage.

Location

San Francisco, USA

Why this role is remarkable

• You will perform deep technical work in reinforcement learning (RLHF, DPO, GRPO) and model training, moving beyond simple API wrappers to build core agentic infrastructure.
• Macroscope is led by veteran founders who previously exited Periscope and Magic Pony, and is supported by top-tier investors including Lightspeed, Thrive Capital, and Google Ventures.
• You'll receive significant early-stage equity (0.25%-0.5%) at a valuation that offers massive upside compared to later-stage competitors, working in a high-agency, flat-structured environment.
  
  

What You Will Do

• Train and fine-tune LLMs using reinforcement learning techniques such as GRPO, DPO, and PPO to improve reasoning and code generation capabilities.
• Design and curate high-quality evaluation datasets and benchmarks to rigorously measure model performance and guide product-driven experimentation.
• Collaborate with backend engineers to integrate custom models into production using a stack featuring Golang, Temporal, and custom-built AST code walkers.
  
  

The ideal candidate

• Has 3+ years of experience in applied ML, specifically building, fine-tuning, or evaluating modern models in production or research environments.
• Possesses hands-on experience with reinforcement learning for LLMs (RLHF, RLAIF, or similar) and a deep understanding of training dynamics and reward shaping.
• Demonstrates strong software engineering skills and a high-agency mindset, comfortable building reliable ML pipelines in a fast-paced, in-office San Francisco startup.
  
  

Who are Jack & Jill?

Ok, I'll go first. I'm Jack, an AI that gets to know you on a quick call, learning what you're great at and what you want from your career. Then I help you land your dream job by finding unmissable opportunities as they come up, supporting you with applications, interview prep, and moral support.

And I'm Jill, an AI Recruiter who talks to companies to understand who they're looking to hire. Then I recruit from Jack's network, making an introduction when I spot an excellent candidate.

How does this work?

• Jack's an AI agent for job searching and career coaching. He works for you.
• Jill is the AI recruiter working for the company. She recruits from Jack's network.
• If it's a match and the company wants to meet you, they'll make the intro. In the meantime, if you'd like, Jack will send you excellent alternatives.
  
  

We never post fake jobs

This isn't a trick. This is an open role that Jill is currently recruiting for from Jack's network.

Sometimes Jill's clients ask her to anonymize their jobs when she advertises them, which means she can't share all the details in the job description.

We appreciate this can make them look a bit suspect, but there isn't much we can do about it.

Give Jack a spin! You could land this role. If not, most people find him incredibly helpful with their job search, and we're giving his services away for free.