Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Member of Technical Staff | Machine Learning
Menlo Park · Menlo Park, United States
Live, first seen by us 20 days ago- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Engineering — team source
Department: Engineering
From the employer’s posting
Before you apply
- Work authorization
- Sponsors visas
What you’ll work on
Full postingAt Poesis, machine learning and artificial intelligence open the door to improved alpha discovery, higher quality decision-making and intelligent risk management.
Find predictive signals in large financial, fundamental and alternative datasets.
Find predictive signals in large financial, fundamental and alternative datasets
Design experiments and evaluations that separate real improvements from noise
Build reproducible ML research systems for fast experimentation
Turn promising research into production models and signals
Use real-world outcomes to find where models and agents can improve
From the employer’s posting
At Poesis, machine learning and artificial intelligence open the door to improved alpha discovery, higher quality decision-making and intelligent risk management. We’re looking for a Member of Technical Staff (Machine Learning) to build the models, signals, and evaluation tools that make this possible. This is an opportunity to test new ideas against complex, real-world financial data and see the impact of your work on actual investment decisions.
Find predictive signals in large financial, fundamental and alternative datasets.
Design experiments and evaluations that separate real improvements from noise.
Build rigorous, reproducible ML research systems for fast experimentation.
Turn promising research into production models and signals that hold up over time.
Use real-world outcomes to understand where models and agents can improve.
What you’ll bring
All qualificationsCore experience
- Experience developing, evaluating, and deploying ML models in production
- Strong quantitative judgment and experience with large, complex datasets
- BS, MS, or PhD in Computer Science or related field, or equivalent practical experience
- Ownership of open-ended research problems
- Current legal authorization to work in the US
Qualification wording
You’ve developed, evaluated, and deployed ML models in production.
You have strong quantitative judgment and experience working with large, complex datasets.
BS, MS, or PhD in Computer Science or a related field, or equivalent practical experience.
You can take ownership of open-ended research problems and use evidence to decide what to pursue next.
Current legal authorization to work in the US required
Education & alternatives
- You can take ownership of open-ended research problems and use evidence to decide what to pursue next. - BS, MS, or PhD in Computer Science or a related field, or equivalent practical experience. Location
Benefits in the posting
Full benefits wording- We offer excellent medical, dental, and vision coverage, alongside a strong benefits package that includes catered lunches, commuter benefits, and more.
- Nice to Have
From the employer’s posting.
About Poesis
Whoever builds the leading intelligence for finance will create far more than returns.
In the employer’s words · Read in context · Company website ↗
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 15, 202620 days ago
- Recorded sightings
- 18
- Last seen by us
- Nov 3, 2026
- Employer says posted
- Oct 13, 2026
- Reposted
- once since Jun 12, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
How this job compares
Time since we first saw it
Day 20
Similar jobs usually come down between day 6 and day 69.
From 4,296 similar postings that came down. Coming down is not always a hire.
Poesis is hiring
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- 50% of open jobs were reposted
See how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.
Your next step
Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.
Applying through Ashby
- No account needed. “Autofill from resume” at the top of the form fills the key fields from your file.
Already applied? Track this application
Has Poesis posted this job before?
Yes. We’ve followed one other Member of Technical Staff | Machine Learning job there since June 2026. It came down after 121 days.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
About Poesis
Whoever builds the leading intelligence for finance will create far more than returns. Poesis is the AI-native investment firm running autonomous agents that predict markets, construct portfolios, and manage risk. Our founders managed institutional capital at Capital Group ($3T AUM) and led enterprise ML at Goldman Sachs and Amazon. We're building a new type of firm, where live capital is the training ground for an intelligence that compounds with every signal.
About the Role
At Poesis, machine learning and artificial intelligence open the door to improved alpha discovery, higher quality decision-making and intelligent risk management. We’re looking for a Member of Technical Staff (Machine Learning) to build the models, signals, and evaluation tools that make this possible. This is an opportunity to test new ideas against complex, real-world financial data and see the impact of your work on actual investment decisions.
Challenges You'll Work On
Find predictive signals in large financial, fundamental and alternative datasets.
Design experiments and evaluations that separate real improvements from noise.
Build rigorous, reproducible ML research systems for fast experimentation.
Turn promising research into production models and signals that hold up over time.
Use real-world outcomes to understand where models and agents can improve.
About You
You’ve worked at a frontier AI lab, agentic startup, high-growth technology company, leading investment manager, or similar organization.
You’ve developed, evaluated, and deployed ML models in production.
You understand how models fail, how evaluation design shapes outcomes and how to distinguish promising results from noise.
You have strong quantitative judgment and experience working with large, complex datasets.
You can take ownership of open-ended research problems and use evidence to decide what to pursue next.
BS, MS, or PhD in Computer Science or a related field, or equivalent practical experience.
Location
Hybrid, 3 days per week on-site at our office in Menlo Park, CA. Relocation allowance available.
Benefits
We offer excellent medical, dental, and vision coverage, alongside a strong benefits package that includes catered lunches, commuter benefits, and more.
Current legal authorization to work in the US required; continuing work visa sponsorship available for full-time employees.
Nice to Have
Experience developing ML or AI systems using financial, fundamental, alternative, or time-series data.
Familiarity with quantitative investing, portfolio construction, or risk management.
Experience applying modern AI systems to financial documents (filings, transcripts, etc).
Working at Poesis
As an early team member, you’ll help shape not just the product, but how the company operates. Your decisions will have lasting impact across the business. You’ll build from first principles, with no legacy systems, or entrenched processes slowing you down. Our team is made up of people from elite companies and universities who are low ego, collaborative, and excited to build together.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Menlo Park, United States
Location Hybrid, 3 days per week on-site at our office in Menlo Park, CA. Relocation allowance available. Benefits
- Work authorization
We offer excellent medical, dental, and vision coverage, alongside a strong benefits package that includes catered lunches, commuter benefits, and more. Current legal authorization to work in the US required; continuing work visa sponsorship available for full-time employees. Nice to Have