/Jobs

We're a small, ambitious team building the science of organic alignment. We hire for depth, ownership, and the drive to work on the hardest problems in AI. If that's you, we'd love to hear from you.

ISoftware Engineer

San Francisco, CA · Full-time

The Role

We're looking for a Software Engineer who thinks like a scientist and operates like a founder. You'll own entire systems end-to-end: from identifying what to build, to designing and implementing solutions, to measuring impact and iterating. This isn't a role where you wait for specs — you generate clarity from ambiguity and ship with conviction.

You're also fluent in modern AI tools and use them to multiply your output. We expect engineers here to be exceptionally productive and to leverage that productivity toward bigger problems, not just faster typing.

What You'll Do

• Own products end-to-end. Define what to build based on user needs and business goals. Design the technical approach. Build it. Ship it. Measure it. Improve it.
• Apply analytic rigor to feature decisions. Design experiments properly. Understand what your data can and can't tell you.
• Move fast with quality. We ship frequently and learn from real usage. Balance speed with craft.
• Leverage AI tools aggressively. We expect you to operate at 2–5x the productivity of a traditional engineer.
• Collaborate with a small, excellent team. Low process, high ownership, direct feedback.

What We're Looking For

• Deep analytical background. Graduate work in a quantitative field (CS, physics, etc.), research experience, or equivalent depth from industry.
• Full-stack capability with multi-language strength. Comfortable across the stack — backend services, data pipelines, frontend when needed. Python and C++.
• Strong customer instincts. You understand why something should be built, not just how.
• AI-native workflow. You already use AI tools daily and have opinions about how to use them effectively.
• Ownership mentality. You see problems, propose solutions, and drive them to completion.

Compensation

We hire based on impact, not years of experience. Compensation reflects your expected contribution. This covers a range of experience levels including what would be considered staff and principal engineer at larger organizations.

IIApplied Research Scientist

San Francisco, CA · Full-time

The Role

We're looking for an Applied Research Scientist to own applied research on organic AI alignment end-to-end. You'll choose the question, design the environment configs and evaluations, implement experiments, analyze results, and turn what works into reusable systems. In this role, research and execution go hand in hand: you generate clarity from ambiguity and produce conclusions that survive contact with reality.

This role is focused on training new model families. You should be comfortable reasoning from first principles about architectures, losses, optimization, curricula, scaling behavior, and failure modes. You'll help train a new generation of RL approaches: systems that can stream, adapt, grow, and keep learning over time.

You're fluent in modern AI tools and use them across coding, literature review, experiment design, analysis, and writing. You use that leverage to take on harder problems, not just to iterate faster.

What You'll Do

• Choose and run high-leverage experiments. Translate model-training and alignment questions into concrete architectures, tasks, curricula, evaluations, and experiments; run them, interpret them, and iterate.
• Train new deep learning architectures from scratch. Work with novel model substrates, loss functions, data mixtures, recurrent computation, graph structure, and scaling recipes to discover what actually trains.
• Run rigorous experiments. Use ablations, baselines, controls, and statistical judgment. Understand what your data can and can't tell you.
• Diagnose training behavior. Read learning curves, gradients, activations, memory traces, ablations, and failure cases to understand whether a result is an architecture issue, optimization issue, data issue, evaluation issue, or implementation bug.
• Build research infrastructure that changes what we can know. Design multi-agent tasks, curricula, metrics, dashboards, and analysis workflows that surface real signal.
• Turn research into working systems. Write production-quality Python and C++ when needed, integrate with training and evaluation pipelines, and make your ideas reusable by the rest of the team.
• Move fast with scientific discipline. Learn from real runs, real agents, and real users. Know when to prototype quickly and when the foundation matters.
• Leverage AI tools aggressively. Use AI assistants, coding agents, and research tools to operate beyond traditional throughput.
• Collaborate with a small, strong team. Low overhead, high ownership, direct feedback, and rigorous technical discussion.

What We're Looking For

• Deep analytical and research background. Graduate work or equivalent research depth in ML, reinforcement learning, CS, physics, math, complex systems, or another quantitative field.
• Strong deep learning and ML/RL instincts. You understand neural architecture design, optimization, loss functions, training dynamics, evaluation, reward design, generalization, baselines, and failure modes.
• Deep learning implementation depth. You have trained nontrivial models end-to-end, debugged unstable runs, designed or modified architectures, and are comfortable working below the paper abstraction level when needed.
• Interest in architectures beyond standard transformer stacks. Experience with recurrent models, sequence modeling, graph neural networks, message passing, world models, memory systems, multimodal models, or reinforcement learning is especially relevant.
• Systems fluency. Comfortable building, debugging, and scaling the tooling your research needs. Python and C++.
• Scientific taste. You choose questions that matter, design experiments that can answer them, and notice when a result is beautiful but probably wrong.
• AI-native workflow. You already use AI tools daily and have opinions about how to supervise them effectively.
• Ownership mentality. You see problems, propose research programs, and drive them to completion.

Compensation

Level and compensation are calibrated to the scope and impact expected from the role. The range spans experience levels that larger organizations might label senior, staff, principal, or research scientist.

IIISoftware Engineer — Contractor

Remote · Global · From $60/hr

The Role

We're seeking a remote contract software engineer to build high-quality systems and tools. You'll work independently on diverse engineering challenges that support our research and product development, focusing on scalability, performance, and clean architecture. Ideal for self-directed engineers who thrive with autonomy.

Key Responsibilities

• Design and implement robust, scalable software systems
• Build tools and infrastructure to support research and development workflows
• Optimize system performance
• Collaborate asynchronously with team members to translate requirements into technical solutions
• Write clean, maintainable code with appropriate testing and documentation

Requirements

• Strong software engineering background with demonstrated experience building complex systems independently
• Ability to work autonomously and manage projects from conception to delivery
• Strong written communication skills for remote collaboration
• Comfortable working across time zones and managing asynchronous workflows

Nice to Have

• Experience with machine learning, data science, or AI systems
• Familiarity with distributed computing
• Background in data visualization or analytics tools

Softmax is an equal opportunity employer. We welcome applicants of all backgrounds, identities, and experience levels.