Machine Learning Engineer

About Poesis

Poesis is an AI-first investment firm creating autonomous systems that forecast markets, build portfolios, and oversee risk. The company’s founders previously handled institutional assets at Capital Group and led enterprise machine learning at Goldman Sachs and Amazon. The vision is to build a new kind of investment business where live capital helps train an intelligence system that improves as new signals arrive.

About the Role

This position is for a seasoned Machine Learning Engineer who can help create the models, signals, and evaluation methods that drive investment decisions across the platform. You will work through the full ML lifecycle, from research and experimentation to model and agent development, production deployment, and ongoing refinement. The role offers substantial ownership over both technical research and real-world system performance.

Responsibilities

• Move quickly from idea to implementation by building and refining machine learning models, signals, and research prototypes.
• Plan and execute experiments that measure model quality, agent behavior, and downstream investment impact.
• Create reliable, repeatable pipelines for feature creation, training, validation, and evaluation.
• Analyze large financial, fundamental, and alternative datasets to uncover predictive patterns and improve model performance.

Required Competencies

• At least 5 years of experience in machine learning engineering or a closely related discipline.
• Background at a frontier AI lab, agentic startup, major hedge fund, large technology company, or a comparable environment.
• Strong Python and SQL ability, with hands-on experience handling large datasets.
• Track record of building, testing, and deploying ML models in production.
• Experience creating reproducible research processes and experimentation frameworks.
• Working knowledge of modern AI systems, including LLMs, model evaluation, and agent workflows.
• Ability to use coding agents such as Claude Code, Codex, or similar tools effectively.
• BS, MS, or PhD in Computer Science or a related field, or equivalent practical experience.

Preferred Competencies

• Experience building ML and AI systems with financial, fundamental, alternative, or time-series data.
• Exposure to quantitative investing, portfolio construction, or risk management.
• Experience with PyTorch or TensorFlow, plus AI workflows for processing financial documents such as filings and transcripts.

Location and Work Setup

This role is hybrid, with three in-office days per week in Menlo Park, California. A relocation allowance is available.

Benefits

The package includes medical, dental, and vision coverage, catered lunches at the Menlo Park office, commuter benefits, and additional perks.

Eligibility

Candidates must already have authorization to work in the United States. Full-time employees may also receive continuing work visa sponsorship.

Working at Poesis

As an early hire, you will help shape both the product and the operating style of the company. Your work will have long-term influence across the business. The environment is built from first principles, without legacy systems or entrenched processes holding the team back. The company values people who are collaborative, humble, and excited to build alongside strong peers from leading organizations and universities.

Compensation

The expected pay range is $200,000 to $280,000 per year.