Open Positions
Founding Engineer - Software
San Francisco, CA / Remote
Full-time
Join us as a founding software engineer and help build the infrastructure for custom evaluation and post-training of AI agents. You'll work directly with our founding team to build scalable systems that enable reliable real-world AI agents.
Responsibilities
- •Design and implement scalable infrastructure for custom AI evaluation systems
- •Build tools and platforms for post-training workflows and alignment techniques
- •Develop data processing pipelines for evaluation datasets and feedback loops
- •Create APIs and interfaces for real-world agent deployment and monitoring
- •Optimize performance and cost of cloud-based ML workloads
- •Contribute to open-source projects and research implementations
Requirements
- •2+ years of software engineering experience
- •Strong background in Python and modern web technologies
- •Knowledge of distributed systems and cloud infrastructure (AWS, GCP, or Azure)
- •Experience with data engineering, ETL pipelines, or ML infrastructure
- •Strong problem-solving skills and ability to work in a fast-paced startup environment
- •Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)
What We Offer
- •Competitive salary plus meaningful equity package
- •Comprehensive medical benefits and generous PTO
- •Flexible work arrangements
- •Learning and development budget
- •Direct impact on company direction and technical decisions
- •High ownership and the opportunity to make a career-defining impact
Founding Engineer - Research (Post-training)
San Francisco, CA / Remote
Full-time
Join us as a founding research engineer focused on post-training and help advance the state of AI alignment and evaluation. You'll work on novel approaches to RLHF, preference learning, evaluation methodologies, and alignment techniques while building reliable real-world AI agents.
Responsibilities
- •Conduct research on novel post-training techniques (RLHF, DPO, reward modeling, etc.)
- •Develop custom evaluation frameworks and benchmarks for real-world AI agents
- •Design and implement alignment strategies for reliable agent behavior
- •Build reinforcement learning systems for complex agent environments
- •Contribute to research papers and technical publications
- •Collaborate with engineering team to productionize research innovations
Requirements
- •Preferred Masters or PhD in Computer Science, AI, or related field (or equivalent research experience)
- •Strong programming skills in Python and deep experience with ML frameworks (PyTorch/JAX)
- •In-depth understanding of reinforcement learning, RLHF, and post-training methods
- •Research experience in alignment, evaluation, RL, or related domains
- •Track record of publications in top-tier conferences (NeurIPS, ICML, ICLR, etc.) or strong research experience
- •Ability to work independently and collaborate effectively in a research environment
- •Strong written and verbal communication skills
What We Offer
- •Competitive salary plus meaningful equity package
- •Comprehensive medical benefits and generous PTO
- •Flexible work arrangements
- •Learning and development budget
- •Direct impact on company direction and research agenda
- •High ownership and the opportunity to make a career-defining impact
Founding Engineer - Infra
San Francisco, CA / Remote
Full-time
Join us as a founding infrastructure engineer and help build the robust, scalable systems that power post-training workloads and software development. You'll design and implement infrastructure for RLHF, evaluation pipelines, and real-world agent deployment at scale.
Responsibilities
- •Design and implement scalable infrastructure for post-training workloads (RLHF, reward modeling)
- •Build compute infrastructure for large-scale evaluation and agent testing environments
- •Optimize GPU utilization and cost management for training and inference
- •Develop CI/CD pipelines and deployment automation for ML systems
- •Implement monitoring, logging, and observability for agent behavior and system performance
- •Ensure system security, reliability, and disaster recovery for production agents
Requirements
- •3+ years of infrastructure engineering experience
- •Strong background in cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)
- •Knowledge of distributed systems, networking, and security best practices
- •Experience with ML infrastructure, training/inference optimization, or GPU clusters
- •Strong problem-solving skills and ability to work in a fast-paced startup environment
- •Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)
What We Offer
- •Competitive salary plus meaningful equity package
- •Comprehensive medical benefits and generous PTO
- •Flexible work arrangements
- •Learning and development budget
- •Direct impact on company direction and infrastructure decisions
- •High ownership and the opportunity to make a career-defining impact
Software Engineer Intern
San Francisco, CA / Remote
Internship
Join us as a software engineering intern and gain hands-on experience building infrastructure for AI evaluation, alignment, and post-training. You'll work alongside our founding team to develop evaluation platforms, agent deployment systems, and tools for reliable real-world AI.
Responsibilities
- •Assist in developing evaluation infrastructure and data processing pipelines
- •Contribute to building tools for post-training workflows and alignment
- •Help develop APIs and interfaces for agent deployment and monitoring
- •Work on data pipelines for evaluation datasets and feedback collection
- •Participate in code reviews and learn best practices
- •Contribute to open-source projects and technical documentation
Requirements
- •Currently pursuing Bachelor's or Master's degree in Computer Science, Engineering, or related field
- •Strong programming skills in Python and familiarity with modern web technologies
- •Basic understanding of machine learning concepts and frameworks
- •Experience with version control (Git) and collaborative development
- •Strong problem-solving skills and eagerness to learn
- •Ability to work independently and collaborate effectively in a team environment
- •Previous internship or project experience in software development preferred
What We Offer
- •Competitive internship compensation
- •Flexible work arrangements
- •Learning and development opportunities
- •Mentorship from experienced founders and engineers
- •Direct impact on real-world AI systems
- •Potential for full-time conversion
Research Engineer Intern (Post-training)
San Francisco, CA / Remote
Internship
Join us as a research engineering intern focused on post-training and dive deep into cutting-edge AI alignment and evaluation research. You'll work alongside our founding team to explore novel approaches to RLHF, preference learning, evaluation methodologies, and building reliable real-world AI agents.
Responsibilities
- •Assist in conducting research on post-training techniques (RLHF, DPO, reward modeling)
- •Help develop novel evaluation frameworks and benchmarks for AI agents
- •Implement and experiment with alignment and safety methods
- •Work on reinforcement learning systems for agent environments
- •Contribute to research papers and technical publications
- •Learn from experienced researchers and contribute to team knowledge sharing
Requirements
- •Preferably pursuing Master's or PhD in Computer Science, AI, or related field
- •Strong programming skills in Python and experience with ML frameworks (PyTorch preferred)
- •Understanding of deep learning fundamentals, RL, and post-training methods
- •Research experience or coursework in alignment, RLHF, evaluation, or related AI domains
- •Strong analytical and problem-solving skills
- •Ability to work independently and collaborate effectively in a research environment
- •Previous research experience or publications preferred but not required
What We Offer
- •Competitive internship compensation
- •Flexible work arrangements
- •Learning and development opportunities
- •Mentorship from experienced founders and researchers
- •Direct impact on AI alignment and evaluation research
- •Potential for full-time conversion
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