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Algorithmic Trading Jobs in California (NOW HIRING)

A track record of building quantitative systems that run in production -- algorithmic trading, portfolio optimization, market making, or risk systems at a trading firm, asset manager, fintech, or ...

A track record of building quantitative systems that run in production -- algorithmic trading, portfolio optimization, market making, or risk systems at a trading firm, asset manager, fintech, or ...

Experience communicating complex algorithm design decisions and technical trade-offs in writing to both engineering and non-engineering stakeholders Preferred Qualifications: * Experience with data ...

Senior Algorithms Engineer

Sunnyvale, CA · On-site

$124K - $170K/yr

Partner with hardware, firmware, and system teams on requirements, architecture, and performance trade-offs * Document algorithm design, assumptions, and validation results for internal and customer ...

Senior Algorithms Engineer

Sunnyvale, CA · On-site

$130K - $200K/yr

Partner with hardware, firmware, and system teams on requirements, architecture, and performance trade-offs * Document algorithm design, assumptions, and validation results for internal and customer ...

DSP Algorithms Engineer

Del Rey, CA · On-site

$137K - $160K/yr

Job #219547 Chipton-Ross is seeking 2 DSP Algorithms Engineers (Level 4) for a contract opportunity ... Performing trade studies * Supporting integration and test of our payloads and spacecraft from unit ...

Showing results 41-60

Algorithmic Trading information

See California salary details

$73.5K

$84.6K

$92.8K

How much do algorithmic trading jobs pay per year?

As of Sep 13, 2026, the average yearly pay for algorithmic trading in California is $84,627.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,900.00 and $89,800.00 per year, depending on experience, location, and employer.

What is algorithmic trading?

Algorithmic trading involves trading in equities, currencies, or other financial instruments using computer programs. A trading program uses an algorithm to calculate current market conditions. This trading method is automated, so the program buys or sells the financial instrument when the algorithm says that the market meets all the requirements for a profitable trade. To create an algorithm, you perform mathematical and statistical analysis, also known as quantitative analysis, on an exchange or equity. After creating an algorithm with defined trading rules, you test it using historical market data. While this is primarily a technical field, you also need an understanding of the market.

What is algorithmic trading?

Algorithmic trading refers to the use of computer programs and algorithms to automatically execute trading orders in financial markets. These algorithms follow predefined rules based on factors like price, timing, and volume to optimize trading strategies and reduce human intervention. Algorithmic trading is widely used by institutional investors, hedge funds, and individual traders to increase efficiency, minimize costs, and capitalize on market opportunities. It can range from simple rule-based systems to complex strategies involving machine learning and artificial intelligence.

What are the key skills and qualifications needed to thrive as an algorithmic trader, and why are they important?

To thrive as an Algorithmic Trader, you need a strong background in quantitative analysis, programming (often Python, C++, or Java), and a solid understanding of financial markets, typically supported by a degree in mathematics, engineering, finance, or computer science. Familiarity with statistical modeling tools, trading platforms, and backtesting systems is essential, and certifications such as CFA or FRM can be advantageous. Superior problem-solving skills, attention to detail, and the ability to work under pressure set standout professionals apart in this field. These skills are crucial to developing, implementing, and refining trading strategies that can operate profitably and reliably in fast-moving financial environments.

What are the main challenges faced by professionals in algorithmic trading, and how can they be addressed?

Professionals in algorithmic trading often encounter challenges such as developing strategies that remain effective in rapidly changing markets, minimizing latency for faster execution, and managing the risks associated with automated trading systems. To address these challenges, it's essential to stay updated with the latest market trends and technological advancements, conduct rigorous backtesting of algorithms, and implement robust risk management protocols. Collaboration with quantitative analysts, software engineers, and risk managers is also key to ensuring strategies are both innovative and resilient.

What is the difference between Algorithmic Trading vs Quantitative Analyst?

AspectAlgorithmic TradingQuantitative Analyst
Required CredentialsDegree in finance, computer science, or related field; programming skillsDegree in mathematics, statistics, or finance; strong analytical skills
Work EnvironmentTrading firms, hedge funds, financial institutions; fast-pacedInvestment banks, asset management firms; research-focused
Employer & Industry UsageUsed to automate trading strategiesDevelops models to inform trading decisions

While both roles involve quantitative skills and finance knowledge, Algorithmic Traders focus on implementing automated trading systems, whereas Quantitative Analysts develop models and strategies that may be used by traders or firms. The roles often overlap but differ mainly in their primary focus: execution versus modeling.

What are the most commonly searched types of Algorithmic Trading jobs in California?

The most popular types of Algorithmic Trading jobs in California are:

What are popular job titles related to Algorithmic Trading jobs in California?

For Algorithmic Trading jobs in California, the most frequently searched job titles are:

What job categories do people searching Algorithmic Trading jobs in California look for?

The top searched job categories for Algorithmic Trading jobs in California are:

What cities in California are hiring for Algorithmic Trading jobs?

Cities in California with the most Algorithmic Trading job openings:

Infographic showing various Algorithmic Trading job openings in California as of September 2026, with employment types broken down into 1% Internship, 88% Full Time, 8% Part Time, 1% Temporary, and 2% Contract. Highlights an 82% Physical, 6% Hybrid, and 12% Remote job distribution, with an average salary of $84,627 per year, or $40.7 per hour.

Quant Developer

San Francisco, CA • On-site

Gauntlet
Software Development • 11 - 50 employees

Other

Medical, Dental, Vision, PTO

Posted 11 days ago


Key responsibilities

  • Design, build, deploy, and own vault strategies from concept through live operation.

  • Optimize strategies through signals research, execution improvements, and rebalancing techniques.

  • Monitor and evaluate protocols, assets, and strategies to ensure safety, performance, and uptime.


Job description

You will design, build, and operate the strategies behind one of the largest asset managers in onchain finance. Gauntlet serves $1.5B+ in client TVL, and the vaults that hold it run on strategies that quant developers on our team build, ship, and stand behind. This is not a research seat where models get handed off to someone else's pipeline — you design the strategy, write the code, deploy it, and own it in production. If you want your models allocating real capital onchain within weeks of joining, read on.

About Gauntlet

Gauntlet builds the financial systems of the future. While much of onchain finance is focused on point solutions, we operate across the entire stack to offer best-in-class vault products. Today we serve over $1.5B in client TVL across some of the largest fintechs/neobanks, protocols, exchanges, and capital allocators in crypto — and, increasingly, traditional asset management. Our team brings together traditional finance and crypto-native expertise to deliver durable, sophisticated products for institutional clients moving onchain.

The role

Depending on your background and interests, you'll join one of our vault strategy teams. Our strategies span lending and credit curation, cross-chain yield aggregation, structured products, RWAs, and more. Teams own the full strategy lifecycle: research and protocol due diligence, strategy design and backtesting, allocation and rebalancing engines, onchain execution and optimization, and 24/7 monitoring of live positions. You own strategies end-to-end and are accountable for their performance, safety, and uptime.

What you'll do;
  • Design and ship vault strategies: take a strategy from thesis and design doc through implementation, simulation, deployment, and live operation — RWAs, leveraged lending, yield aggregation, cross-protocol allocation, perpetuals, prediction markets, and new product types we haven't built yet.
  • Optimize strategies: signals research, execution optimization, gas-aware rebalancing across tokens and chains, liquidity and duration management.

  • Run protocol and asset due diligence: evaluate new protocols, collateral assets, and chains for inclusion in strategies — solvency mechanics, oracle design, redemption paths, liquidity depth, and more.

  • Own risk parameters: supply caps, LLTV settings, concentration limits, VaR-based exposure models, and automated de-risking logic that pulls positions when conditions deteriorate.

  • Integrate new protocols and chains: build and validate adapters for lending markets, DEX aggregators, and bridges; verify strategy behavior against forked-chain simulation before capital touches it.

  • Monitor what you build: extend our risk-monitoring and alerting systems, define the conditions that page someone, and participate in the on-call rotation for the strategies you own.

  • Support launches and clients: partner with growth, capital markets, and client teams on new vault and strategy launches.

What you bring;
  • A track record of building quantitative systems that run in production — algorithmic trading, portfolio optimization, market making, or risk systems at a trading firm, asset manager, fintech, or crypto-native company. This is often 2–8 years of experience, but we weight what you've built over years on a résumé.

  • You write the code behind your strategies. Strong Python and solid software-engineering fundamentals: testing, code review, and the judgment to build durable abstractions rather than one-off scripts. This is a hands-on, quantitative role — not a discretionary trading seat.

  • Applied quantitative skills: optimization, statistics, and simulation, and the instinct to validate models against real data before trusting them.

  • Comfort with data infrastructure: SQL and experience building or consuming data pipelines.

  • Production ownership: you've debugged live systems under pressure and understand that a strategy managing other people's money has to be correct, monitored, and recoverable.

  • Clear technical communication.

Bonus points
  • Hands-on DeFi experience: lending protocols, ERC-4626 vaults, AMMs, or oracle systems — as a builder or a sophisticated user.

  • Solidity / EVM literacy: reading protocol contracts, forked-chain simulation (anvil), or writing adapters; non-EVM experience (e.g., Solana) also valued.

  • On-chain operational experience: multisig workflows, transaction submission and signing infrastructure, bridging.

  • TypeScript, and familiarity with a modern data stack (e.g., BigQuery, Dagster, Hex, GCP/Kubernetes).

  • Experience with risk modeling for volatile or thinly-traded assets: VaR, liquidation modeling, stress testing.

Who thrives here;
  • Wants end-to-end ownership — research, code, deployment, and the pager — not a hand-off between research and engineering.

  • Comfortable that crypto markets don't close. Strategy owners take on-call seriously, and the occasional market-event night is part of the job; we staff and rotate to keep it sustainable.

  • Operates well in ambiguity: can take \"we should have a strategy for X\" and return a scoped design, not a list of questions — and is comfortable in a fast-moving space where priorities and team structure evolve.

  • Holds a genuine risk view and voices it — including \"we shouldn't do this\" when the analysis says so.

  • Pragmatic about shipping: balances rigor against client timelines without cutting corners on safety.

  • Naturally curious about digital assets and DeFi. Deep crypto experience is not required — curiosity and strong quant fundamentals are.

Benefits & perks;
  • Remote first — work from anywhere in the US & Canada

  • Regular in-person company retreats and cross-country \"office visit\" perk

  • 100% paid medical, dental, and vision premiums for employees

  • $1,000 WFH stipend

  • Monthly reimbursement for home internet, phone, and cellular data

  • Unlimited vacation

  • 100% paid parental leave of 12 weeks

  • Fertility benefits

  • Opportunity for incentive compensation

Please note at this time our hiring is reserved for potential employees who are able to work within the contiguous United States and Canada. Should you need alternative accommodations, please note that in your application.

The national pay range for this role is $175,000 – $200,000 base plus additional On Target Earnings potential by level and equity in the company. Our salary ranges are based on paying competitively for a company of our size and industry, and are one part of many compensation, benefits, and other reward opportunities we provide. Individual pay rate decisions are based on a number of factors, including qualifications for the role, experience level, skill set, and balancing internal equity relative to peers at the company.

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