Build low-latency, high-reliability trading, risk, and analytics systems for fintech applications. Translate quantitative models into production software, collaborate with quants and traders, implement market data and FIX systems, and optimize high-throughput concurrent applications. The role requires expertise in financial markets, risk and P&L attribution, performance tuning, and quantitative development, along with strong communication, code review, design review, and mentoring responsibilities.
Quantitative Developer – Remote
Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
Job Title: Quantitative Developer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $75,000–$100,000 Annually
Experience Required: 6+ years
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.
Job Summary
We are seeking an experienced Quantitative Developer to build low-latency, high-reliability trading, risk, and analytics systems for fintech applications. In this role you will partner closely with quants and traders to translate mathematical models into production-quality software that meets strict performance, accuracy, and operational requirements. The ideal candidate will combine strong software engineering skills with solid quantitative fundamentals and deep familiarity with financial markets, instruments, and risk management practices. In this role you will work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions, and will be expected to raise the bar through code review, design review, and mentorship of more junior engineers. The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production.
Required Qualifications
Would you like to know more about this opportunity? For immediate consideration, please send your resume to [email protected]. Learn more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer.
Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
Job Title: Quantitative Developer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $75,000–$100,000 Annually
Experience Required: 6+ years
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.
Job Summary
We are seeking an experienced Quantitative Developer to build low-latency, high-reliability trading, risk, and analytics systems for fintech applications. In this role you will partner closely with quants and traders to translate mathematical models into production-quality software that meets strict performance, accuracy, and operational requirements. The ideal candidate will combine strong software engineering skills with solid quantitative fundamentals and deep familiarity with financial markets, instruments, and risk management practices. In this role you will work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions, and will be expected to raise the bar through code review, design review, and mentorship of more junior engineers. The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, or a related quantitative discipline.
- Six or more years of software engineering experience, with significant time in fintech.
- Strong programming skills in C++, Java, or Python (preferably more than one).
- Solid grounding in financial markets, instruments, and basic quantitative methods.
- Hands-on experience building low-latency, high-throughput systems.
- Experience with market data systems and FIX protocol implementations.
- Strong understanding of risk and P&L attribution.
- Experience with high-performance computing patterns and concurrency.
- Excellent debugging, profiling, and performance-tuning skills.
- Strong communication and documentation skills.
- Experience with derivatives pricing libraries (QuantLib).
- Familiarity with kdb+/q or similar columnar tick databases.
- Exposure to GPU-accelerated pricing or risk computation.
- Experience with cloud-native fintech architectures.
- Advanced degree in a quantitative discipline.
Would you like to know more about this opportunity? For immediate consideration, please send your resume to [email protected]. Learn more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer.
Similar Jobs
Fintech • Financial Services • Cryptocurrency • NFT • Web3
Build and operate high-throughput data pipelines, analytics engines, analytical databases, and AI platforms for quantitative trading teams. Develop streaming and batch systems, trading metrics, time-series models, monitoring, RAG pipelines, prompt-management tools, and production AI agents. The role requires strong Python and Java engineering, AWS and Kubernetes expertise, advanced SQL, financial data experience, and a focus on reliability, scalability, data integrity, and performance.
Top Skills:
A2AAirflowAmpsApache FlinkSparkAWSBigQueryCi/CdClickhouseGitGrafanaJavaJenkinsKafkaKubernetesLanggraphLinuxLlmopsMcpMongoDBPythonRagRest ApiSnowflakeSQLTradingviewWebsocket
Artificial Intelligence • Generative AI
Lead development of ML components for medical image reconstruction: define training/evaluation pipelines and metrics, productionize models (inference performance, monitoring, safe fallbacks), collaborate on hybrid physics-ML algorithms, and build tooling for experimentation and rigorous verification.
Top Skills:
Agentic-ScimlData AssimilationDenoisersEnsemble MethodsGpusKalman FilteringLearned RegularizersMedical Image ReconstructionNeural OperatorsPhysics-Informed Neural Networks (Pinns)Scientific ComputingSignal ProcessingVariational Methods
Automotive
Develop signals to measure the performance of the Waymo driver, analyze data, improve metric quality, and collaborate on evaluation products for autonomous driving software.
Top Skills:
C++Machine LearningPythonSQL
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine



