Top 234 Financial Quant Engineer Jobs

Applied ML Systems Engineer - Finance - NEW YORK - UNITED STATES
Park Lane Recruitment —New York, NY
- $250,000 - $350,000 a year
- Full-time
- Computer science
- Computer Science
- System design
- Health insurance
- 401(k) matching
Quick Apply
Principal Quantitative Engineer, Investments Technology
Liberty Mutual —Boston, MA
- $128,000 - $225,000 a year
- Full-time
- Hybrid work
- Computer science
- Computer Science
- 5 years
Principal Quant Developer (MLOps)
Fidelity Investments —Jersey City, NJ
- $107,000 - $216,000 a year
- Full-time
- Computer Science
- System design
- Office
- Loan repayment program
- Tuition reimbursement
Principal Quant Developer
Fidelity Investments —Smithfield, RI
- $107,000 - $216,000 a year
- Full-time
- Computer science
- Computer Science
- Master's degree
- Loan repayment program
- Tuition reimbursement
Principal Quant Developer
Fidelity Investments —Jersey City, NJ
- $107,000 - $216,000 a year
- Full-time
- Computer science
- Computer Science
- Master's degree
- Loan repayment program
- Tuition reimbursement
Principal Quant Developer
Fidelity Investments —Durham, NC
- $107,000 - $216,000 a year
- Full-time
- Computer science
- Computer Science
- Master's degree
- Loan repayment program
- Tuition reimbursement
Principal Quant Developer (MLOps)
Fidelity Investments —Boston, MA
- $107,000 - $216,000 a year
- Full-time
- Computer Science
- System design
- Office
- Loan repayment program
- Tuition reimbursement
Blockchain Analyst (US)
Inca Digital, Inc. —Remote
- Remote
- Background check
- English
- Mid-level
- Health insurance
- Dental insurance
Quick Apply
KDB / Quant Developer (Python) - Trading & Analytics Focus
EPAM Systems, Inc. —Remote
- $160,000 - $240,000 a year
- Remote
- Senior level
- Python
- Health savings account
- AD&D insurance
Assistant Financial Controller (Government Projects & DCAA Compliance)
Inca Digital, Inc. —Remote
- Remote
- Background check
- CPA
- 5 years
- Health insurance
- Dental insurance
Quick Apply
NLP Engineer
Point72 —New York, NY
- $150,000 - $250,000 a year
- Computer science
- Computer Science
- Mid-level
Quant Researcher
Frec Markets, Inc. —San Francisco, CA
- $200,000 - $300,000 a year
- Full-time
- Computer Science
- Office
- AWS
- Dental insurance
- 401(k)
Senior AI and Quant DevTech Engineer
NVIDIA —New York, NY
- $152,000 - $287,500 a year
- Full-time
- Hybrid work
- Computer Science
- 5 years
- System design
Senior Quantitative Data Engineer
Intone Networks —Remote
- Contract
- Senior level
- AI
Agent Engineer
Moment —New York, NY
- $250,000 - $325,000 a year
- Full-time
- System design
- Research
- Mid-level
- Dental insurance
- Vision insurance
Quick Apply
Founding Engineer
David Joseph & Company —New York, NY
- $175,000 - $250,000 a year
- Full-time
- Computer Science
- 5 years
- Mid-level
Quick Apply
Security Engineer
Moment —New York, NY
- $200,000 - $325,000 a year
- Full-time
- Mid-level
- Office
- AWS
- Dental insurance
- Vision insurance
Quick Apply
Infrastructure/Data Engineer
MLabs —New York, NY
- $180,000 - $320,000 a year
- Full-time
- Hybrid work
- DevOps
- System design
- Senior level
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Design Engineer
Moment —New York, NY
- $175,000 - $275,000 a year
- Full-time
- Mid-level
- Office
- 3 years
- Dental insurance
- Vision insurance
Quick Apply
Trading, Investment & Optimization - QuantAI Engineer (Hybrid)
Accenture —Irving, TX
- $59,100 - $188,100 a year
- Full-time
- Computer Science
- System design
- Windows
- Paid holidays
- Disability insurance

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Applied ML Systems Engineer - Finance - NEW YORK - UNITED STATES

Park Lane Recruitment
New York, NY

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Job Details

Full-time
$250,000 - $350,000 a year

Benefits

Health insurance
401(k) matching
Prescription drug insurance

Qualifications

AI models
Rapid prototyping
Developing large-scale AI models
Prototype creation
Model training
Prototypes

Full Job Description

Applied ML Systems Engineer - Finance
Systems Engineer
UNITED STATES

Applied ML Systems Engineer - Finance

- NEW YORK
- UNITED STATES

Salary: $250,000 - $350,000 base + guaranteed Year 1 bonus (could be 100% to 500%) + sign-on. Total comp is elite tier.

Primary Skills - pytorch, programming, mit, ml, gpu, python, cuda, deep learning, machine learning

Secondary Skills - technical demonstrations, prototyping, model architecture, decision-making, model design, mathematics, ai, experimentation, full stack

Work Experience - 3-15 yrs

Remote Status - No Remote

Client Willing to Sponsor - Yes

Degree - University - Bachelor's Degree/3-4 Year Degree

Major - Only Computer Science, Machine Learning, Mathematics, or a related quantitative field

Relocation Paid - Yes

Recruit From - Nationwide

Salary Details:
Overall Comp - $500,000 - $1.5m
Base salary $250,000 - $300,000 + Guaranteed Bonus + Relocation

Job Description:
Applied ML Systems Engineer - Finance (New York)
A confidential, highly capitalized financial institution in midtown Manhattan is building out a specialized engineering group focused on accelerating its use of modern machine learning across the organization. This is not a bank, not a startup - it is a well-established, technology-first firm where engineering and research are central to the business, not support functions. They need someone who lives in the gap between research papers and running systems. The kind of engineer who reads a new arxiv paper on Monday and has a working version running on GPUs by Thursday - not to publish, but to prove whether it's worth building for real.

Your days will look different from week to week. Some weeks you'll be deep in GPU kernels trying to shave training time. Other weeks you'll be whiteboarding system designs with researchers who have ideas but need an engineer to make them real. The constant is that everything you build gets used - this is not a lab environment where prototypes sit on a shelf. What the work actually looks like:

You'll spend significant time in low-level performance work - writing custom GPU code, optimizing memory usage, finding the bottlenecks that keep models from training at the speed the business needs
When the research team identifies a promising new technique, you're the person who builds the first working version and stress-tests it against real data to see if the theory holds up in practice
You'll own the design of training infrastructure - figuring out how to let researchers run more experiments faster, without blowing up compute costs or introducing instability
Some of your prototypes will graduate into production systems that run continuously. You'll be involved in that transition, making sure the thing you built in a week can survive running for a year
You'll have real input into which technical directions the group pursues - this isn't a ticket-taking role. If you see a better approach, you're expected to make the case and build the proof

The team is small and senior. Everyone ships. There are no layers between you and the people making decisions about what to build next.

Qualifications

You've actually built ML systems that went to production - not just trained models in notebooks. You know the difference between "it works on my machine" and "it works at scale, reliably, for months" - I must see clear evidence of "ML Systems," "Training Infrastructure," "Distributed Training," "GPU Optimization," "Model Performance" etc on your resume
Must be, or have, worked for: Google (especially Brain, DeepMind, Ads ML, Infra); Meta (FAIR, Infra, Recsys); Amazon (AWS AI, Alexa AI); Apple (ML platform teams); Microsoft (Azure AI, Research, Core AI); AI Labs: OpenAI, Anthropic, Cohere, Mistral, DeepMind; Top Quant / Trading Firms: Two Sigma, Jane Street, Hudson River Trading, Jump Trading, Tower Research, IMC, DRW; High-End Startups: Scale AI, Databricks, Snowflake, Stripe (ML + infra roles), Airbnb / Uber
Seeking ML Engineers, Infra Engineers on ML systems, and training / performance / distributed systems
Candidates with strong undergraduate academic pedigree. Must be from: MIT, Stanford, Harvard, Princeton, Caltech, UC Berkeley, Carnegie Mellon, University of Chicago, Columbia, Cornell, UPenn, Yale, UCLA, UC San Diego, Georgia Tech, University of Washington, UT Austin, University of Michigan, Duke, Northwestern with Degree in CS, Math, Physics, EE, or a related quantitative field and advanced coursework, research involvement, systems, or ML-heavy projects. Ideally with publications, strong internships during undergrad, and evidence of building things, not just studying them
You're comfortable working at the hardware level when needed - GPU programming, memory optimization, custom kernels. You don't treat the infrastructure as someone else's problem
You can move fast without cutting corners. The ability to prototype quickly is essential, but so is knowing when something needs to be built properly
You've partnered with researchers before and know how to translate "I think this architecture might work" into "here's a running system that proves it does (or doesn't)"
You stay current with ML research not because someone tells you to, but because you're genuinely curious about what's new and how it could be applied

Technical environment includes: Python, PyTorch, JAX, CUDA, and related GPU computing tools. Experience with distributed training and large-scale data pipelines is valuable.

Why is This a Great Opportunity
The compensation alone makes this worth a conversation - base salary is $250k - $350k, and there's a guaranteed bonus in your first year on top of that, plus a sign-on. Total comp is genuinely best-in-class.
But the real draw is the work itself. You'll be solving problems that most ML engineers only read about. The datasets are massive and proprietary, the compute budget is effectively uncapped for good ideas, and the people around you are operating at an extremely high level.

This is also a firm that actually values engineers - not just as support for the research team, but as equals who shape the technical direction. Your prototypes don't go into a backlog; they get evaluated and deployed, often within weeks.
Benefits are comprehensive: 401(k) matching, sign-on bonus, medical/prescription coverage, wellness reimbursement, family building support, and charitable gift matching.

If you're the kind of engineer who wants to work on hard problems that matter, with people who are the best at what they do, in an environment where what you build has immediate real-world consequences - this is it.

IND123

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Financial Quant Engineer jobs

Applied ML Systems Engineer - Finance - NEW YORK - UNITED STATES

Principal Quantitative Engineer, Investments Technology

Principal Quant Developer (MLOps)

Principal Quant Developer

Principal Quant Developer

Principal Quant Developer

Principal Quant Developer (MLOps)

Blockchain Analyst (US)

KDB / Quant Developer (Python) - Trading & Analytics Focus

Assistant Financial Controller (Government Projects & DCAA Compliance)

NLP Engineer

Quant Researcher

Senior AI and Quant DevTech Engineer

Senior Quantitative Data Engineer

Agent Engineer

Founding Engineer

Security Engineer

Infrastructure/Data Engineer

Design Engineer

Trading, Investment & Optimization - QuantAI Engineer (Hybrid)

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