Machine Learning and AI Engineer - New York
toggleai
10 months ago
Full-time
On-site
New York
$180,000 - $300,000 USD yearly
AI
Moneyboard classification: Published range reaches threshold
Reported USD annual base: $180,000–$300,000
Original source: Greenhouse
You have built real AI systems that ship, break, and get fixed under pressure.
You care less about model demos and more about decisions that move capital.
You want your work used daily by professional investors, not buried in notebooks.
You are comfortable owning hard problems end to end.
If you want a calm job optimizing benchmarks, this is not it.
The Role, In Plain English
You will build and evolve the AI systems that power Reflexivity’s investment insights.
This role exists because off-the-shelf models and generic pipelines are not enough.
You will work at the intersection of reasoning engines, proprietary data, and real market impact.
Your work directly affects how investors understand earnings, risk, and market catalysts.
What You’ll Be Responsible For
Design, fine-tune, and deploy ML and LLM-driven systems used in production by professional investors
Build and maintain inference pipelines that are fast, observable, and reliable
Integrate OpenAI, Gemini, and Anthropic models into reasoning and knowledge systems
Work closely with backend engineers to productionize models in Golang-based services
Improve signal quality, not just model accuracy
Review code and designs with a bias toward long-term maintainability
What “Good” Looks Like in This Role
After 3 months:
You understand the product, data flows, and investor use cases deeply. You ship meaningful improvements.
After 6 months:
You own major parts of the AI stack. Your work improves insight quality and latency measurably.
After 12 months:
You are a technical reference point for AI decisions. You raise the bar for how AI is built at Reflexivity.
Who You Are (Must-Haves)
5 plus years building ML or applied AI systems in production
Startup experience working on a core product, not a side project
Strong Python skills and experience integrating with backend systems
Hands-on experience with AI-assisted coding tools like Cursor or Claude Code
Fintech experience or strong personal investment background
Comfortable owning outcomes, not just tasks
Nice-to-Haves (Not Deal Breakers)
Experience with LLM reasoning systems or knowledge graphs
Exposure to Golang-based ML integrations
Prior experience supporting investor-facing products
How We Work
In-office team with high trust and high ownership
Direct communication, minimal process, strong opinions backed by data
Engineers are expected to think about product impact, not just code
We move fast when it matters and slow down when correctness matters more
Why This Role Is Worth Your Time
Direct influence on how professional investors make decisions
Hard problems at the edge of AI, data, and finance
Real ownership and technical autonomy
Senior peers who care about quality and outcomes
Compensation & Practicalities
Base salary: $180,000 to $300,000 depending on experience
Equity included
In-office role based in New York
No agency candidates
Salary Range
$180,000—$300,000 USD
Reported USD annual base: $180,000–$300,000
Original source: Greenhouse
You have built real AI systems that ship, break, and get fixed under pressure.
You care less about model demos and more about decisions that move capital.
You want your work used daily by professional investors, not buried in notebooks.
You are comfortable owning hard problems end to end.
If you want a calm job optimizing benchmarks, this is not it.
The Role, In Plain English
You will build and evolve the AI systems that power Reflexivity’s investment insights.
This role exists because off-the-shelf models and generic pipelines are not enough.
You will work at the intersection of reasoning engines, proprietary data, and real market impact.
Your work directly affects how investors understand earnings, risk, and market catalysts.
What You’ll Be Responsible For
Design, fine-tune, and deploy ML and LLM-driven systems used in production by professional investors
Build and maintain inference pipelines that are fast, observable, and reliable
Integrate OpenAI, Gemini, and Anthropic models into reasoning and knowledge systems
Work closely with backend engineers to productionize models in Golang-based services
Improve signal quality, not just model accuracy
Review code and designs with a bias toward long-term maintainability
What “Good” Looks Like in This Role
After 3 months:
You understand the product, data flows, and investor use cases deeply. You ship meaningful improvements.
After 6 months:
You own major parts of the AI stack. Your work improves insight quality and latency measurably.
After 12 months:
You are a technical reference point for AI decisions. You raise the bar for how AI is built at Reflexivity.
Who You Are (Must-Haves)
5 plus years building ML or applied AI systems in production
Startup experience working on a core product, not a side project
Strong Python skills and experience integrating with backend systems
Hands-on experience with AI-assisted coding tools like Cursor or Claude Code
Fintech experience or strong personal investment background
Comfortable owning outcomes, not just tasks
Nice-to-Haves (Not Deal Breakers)
Experience with LLM reasoning systems or knowledge graphs
Exposure to Golang-based ML integrations
Prior experience supporting investor-facing products
How We Work
In-office team with high trust and high ownership
Direct communication, minimal process, strong opinions backed by data
Engineers are expected to think about product impact, not just code
We move fast when it matters and slow down when correctness matters more
Why This Role Is Worth Your Time
Direct influence on how professional investors make decisions
Hard problems at the edge of AI, data, and finance
Real ownership and technical autonomy
Senior peers who care about quality and outcomes
Compensation & Practicalities
Base salary: $180,000 to $300,000 depending on experience
Equity included
In-office role based in New York
No agency candidates
Salary Range
$180,000—$300,000 USD