Machine Learning Engineer

About 8090 - The Software Industrial Complex has evolved into a bloated, expensive ecosystem that burdens enterprises with unnecessary complexity and inefficiency. Co-founded and led by Chamath Palihapitiya, we are building a Software Factory that delivers fully-managed and hosted software purpose-built for each customer.

About the Role - We are seeking an analytical engineer to join our fast-moving technical team. You have a track record of delivering production-grade ML solutions and are comfortable working with uncertainty in real-world systems. Your background includes ML engineering, data science, or deploying agentic systems at scale. What sets you apart is your ability to operationalize, monitor, and systematically improve probabilistic systems—moving beyond prototyping to robust, scalable deployment.

At 8090, Improvement Engineering is a distinct practice: we focus on enabling and accelerating measurable improvement for AI-driven, probabilistic systems. You will develop tools, frameworks, and processes that allow our teams to rigorously evaluate, iterate, and optimize deployed models and algorithms.

Responsibilities

• Build production-grade agentic systems that evolve with best practices and push the frontier of what’s possible
• Rigorously test and QA agent behaviors to uncover edge cases and ensure reliability in real-world conditions
• Collaborate with product and engineering teams to design and implement measurement strategies for ML models, LLMs, and other probabilistic algorithms
• Build and maintain tools for offline experimentation, A/B testing, and model validation at scale
• Develop processes and automation to manage the ML lifecycle, including retraining, evaluation, and deployment pipelines
• Communicate technical findings clearly and concisely to engineering and non-technical stakeholders to inform decision making and foster best practices

Required Skills

• Meaningful experience with deploying and managing LLMs and advanced ML systems in production environments
• Proven ability to design, execute, and iterate on model evaluation strategies, including offline metrics, online experimentation, and statistical analysis
• Deep understanding of concepts such as model drift, calibration, uncertainty quantification, monitoring, and feedback loops
• Proficient with Python, data processing libraries, and ML experiment tracking and orchestration tools
• Demonstrated ownership and end-to-end problem solving: able to identify gaps, acquire new skills as needed, and deliver robust solutions
• Excellent communication and documentation skills; able to clearly articulate technical concepts and collaborate effectively across teams

What Sets a Candidate Apart

• You have well-developed opinions on the current landscape of LLM evaluation and tuning tools and can speak to their strengths, gaps, and trade-offs from practical experience.
• Professional experience in DevOps and cloud infrastructure, with a strong working knowledge of GitHub Actions, Docker, and AWS CDK.
• Experience designing resilient, observable ML systems that remain robust as scale and complexity grow.

Pay range and compensation package - Expected compensation (US-based employees): $100,000 - $250,000 annual salary + stock and/or stock option awards + benefits. We offer competitive pay and benefits. Compensation may vary depending on many individualized factors, including location, job-related knowledge, skills, and experience. Details of the compensation package, including benefits (medical, dental, vision, 401K, …), will be provided if and when a candidate receives an offer of employment.

Equal Opportunity Statement - 8090 is an Equal Opportunity employer. All qualified applicants will be considered for employment without regard to any factor, including veteran status and disability status, protected by applicable federal, state, or local laws. Visa Information - We do not provide new work visa sponsorship. This position is only open to candidates who are citizens, permanent residents or are transferring an existing H-1B, O-1, L-1, or TN Visa.