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Quant Swe Jobs (NOW HIRING)

... related quantitative field with 3+ years of experience in applied AI, machine learning, or ... SWE etc. Communicate results and insights effectively to partners and senior leaders, as well as ...

Research Engineer

San Francisco, CA · On-site

$180K - $250K/yr

MS or PhD in ML, CS, or a related quantitative field - or equivalent demonstrated research ... Experience with agent or multimodal benchmarks (OSWorld, MMMU, WebArena, SWE-bench, or similar) or ...

Showing results 21-26

Quant Swe information

See salary details

$11K

$129.7K

$198K

How much do quant swe jobs pay per year?

As of Sep 14, 2026, the average yearly pay for quant swe in the United States is $129,666.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,500.00 and $138,500.00 per year, depending on experience, location, and employer.

What is a quant SWE?

Quant Swe, short for Quantitative Software Engineer, are professionals who develop and maintain software systems used in quantitative finance. They combine expertise in programming, mathematics, and finance to build tools for data analysis, trading algorithms, and risk management. Quant Swe roles often require knowledge of programming languages such as Python, C++, or Java, and familiarity with financial markets and mathematical modeling. These engineers collaborate closely with quantitative analysts and traders to implement models and ensure high-performance computing solutions.

What are the key skills and qualifications needed to thrive as a quant SWE?

To thrive as a Quantitative Software Engineer, you need strong programming skills (often in Python, C++, or Java), a solid foundation in mathematics and statistics, and typically a degree in computer science, mathematics, engineering, or a related field. Familiarity with specialized tools like MATLAB, NumPy, Pandas, and version control systems, as well as experience with financial data platforms, is often required. Analytical thinking, attention to detail, and effective communication are essential soft skills for collaborating within cross-functional teams and delivering robust solutions. These skills and qualities are critical for building, optimizing, and maintaining complex models and systems that drive financial decision-making.

What are some common challenges faced by quant SWEs when working with large-scale financial data sets?

Quantitative Software Engineers often encounter challenges related to the volume, velocity, and variety of financial data. Ensuring data integrity and accuracy is critical, as small discrepancies can significantly impact trading strategies. Additionally, optimizing algorithms for speed and scalability to process real-time market data is essential, often requiring close collaboration with data engineers and quantitative analysts. These professionals must also stay updated with the latest technologies to efficiently manage and analyze complex data environments.

What is the difference between Quant Swe vs Quant Analyst?

AspectQuant SweQuant Analyst
Required CredentialsDegree in Math, CS, or Engineering; often requires programming skillsDegree in Finance, Economics, Math; may require certifications like CFA
Work EnvironmentTechnical, coding-focused, often in tech or finance firmsResearch-driven, financial modeling, client interaction
Employer & Industry UsagePrimarily in hedge funds, prop trading, quant firmsInvestment banks, asset management, hedge funds
Common Search & ComparisonYesYes

Quant Software Engineers focus on developing and maintaining trading algorithms and systems, emphasizing programming and technical skills. Quant Analysts analyze financial data, develop models, and support trading strategies. While both roles require strong quantitative skills, Quant Swe are more technical and coding-oriented, whereas Quant Analysts focus on financial analysis and modeling.

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What cities are hiring for Quant Swe jobs?

Cities with the most Quant Swe job openings:

What states have the most Quant Swe jobs?

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What are popular job titles related to Quant Swe jobs?

For Quant Swe jobs, the most frequently searched job titles are:

Infographic showing various Quant Swe job openings in the United States as of September 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $129,666 per year, or $62.3 per hour.

Applied AI Engineer

Cupertino, CA

Apple
Computer and Electronic Product Manufacturing • 10K+ employees

$184K - $277K/yr

Full-time

Medical, Dental, Retirement

Re-posted 5 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 685 frontline employees who took The Breakroom Quiz


Job description

Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there's no telling what you could accomplish.
Apple’s Sales organization generates the revenue needed to fuel our ongoing development of products and services. This, in turn, enriches the lives of hundreds of millions of people around the world. We are, in many ways, the face of Apple to our largest customers.
Description
Apple's US Decision Intelligence (DI) team is looking for a talented individual who is passionate about crafting, implementing, and operating AI solutions that have a direct and measurable impact on Apple Sales and its customers.
We’re looking for a hands-on Applied AI Engineer with strong software development skills and a passion for applying LLMs and Agentic workflows to real-world business problems. You will strengthen our team’s capabilities in machine learning, and foundational AI development. This role will drive innovation in building scalable ML and AI solutions that enhance our internal AI products intelligence, improve automation, and expand our AI-driven capabilities across business domains. The ideal candidate combines deep technical expertise in machine learning, statistical modeling, and AI framework development with strong problem-solving and interpersonal skills, ensuring effective collaboration and measurable impact in a fast-paced environment.","responsibilities":"Work at the intersection of applied AI and business operations -translating frontier engineering research into practical, scalable features for AI products.
Design and develop agentic AI systems that reason, plan, and act across tools and modalities.
Translate research into production-ready tools by partnering with platform engineers to productionize your methods into SDKs and APIs.
Prototype and evaluate novel approaches, combining research exploration with hands-on engineering to translate innovations from concept to production.
Build scalable pipelines for multi-modal agent input, memory, and semantic routing.
Work closely with partner teams to build, iterate, and adapt innovative solutions in a dynamic, product-focused environment.
Partner closely with data science, engineering, and sales ops to embed context-aware intelligence in decision-making tools.
Lead technical decision-making on infrastructure components, embedding safety mechanisms (e.g., autonomy sliders, grounding checks, model monitoring).
Collaborate closely with business teams to incorporate AI into their weekly cadences.
Preferred Qualifications
Strong experience articulating and translating business questions into AI solutions.
Hands-on industry experience shipping LLM-powered products or features.
Experience with personalization, recommendation systems, or commerce intelligence.
Experience with anomaly detection and causal inference models.
Sound communication skills - adept at messaging domain and technical content, at a level appropriate for the audience. Strong ability to gain trust with stakeholders and senior leadership.
Familiarity with embedding, retrieval algorithms, agents, and data modeling for vector development graphs.
Other complementary technologies for distributed systems architecture and asynchronous messaging, agent communication, and catching like RabbitMQ, Redis, and Valkey are preferred.
Experience working with monitoring and observability tools (e.g., Prometheus, OpenTelemetry, Weights & Biases).
Minimum Qualifications
PhD in Computer Science, Statistics, Mathematics, AI, or a related quantitative field with 3+ years of experience in applied AI, machine learning, or statistical modeling.; or MS with 6+ years of experience in applied AI, machine learning, or statistical modeling.
Experience with rapid prototyping, reproduction, and validation of research ideas.
Proven ability to translate complex research ideas into scalable, production-level AI solutions.
Demonstrated ability to work across the research-to-production spectrum: you have taken experimental or prototype code and made it robust, scalable, and usable by others.
Comfort with ambiguity. Ability to architect a full orchestrator and business context layer for sales.
Proficiency in Python (FastAPI, LangChain, or similar frameworks), context engineering, and RESTful API design.
Ability to build relationships and collaboration opportunities within Channel Sales and with other orgs i.e AIML, SWE etc.
Communicate results and insights effectively to partners and senior leaders, as well as both technical and non-technical audiences.
Hands-on experience with LLM APIs, embeddings, vector databases, and agentic workflows.
Proven experience working with LLMs and GenAI frameworks (LangChain, LlamaIndex, etc.).
Solid grounding in data structures, async programming, and pipeline orchestration.
Ability to balance competing priorities, long-term projects, and ad hoc requirements in a fast-paced, dynamic, constantly evolving business environment.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $277,600, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976