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Java Quant Developer Jobs in Texas (NOW HIRING)

Roku

Senior Machine Learning Engineer, DevOps/SRE

Austin, TX

$128K - $165K/yr

... quantitative field * 8+ years of experience in DevOps, SRE, or ML infrastructure, including 4+ years supporting large-scale ML or AI systems * Strong programming skills in Python and/or Scala or Java ...

Copart, Inc.

Software Engineering Intern

Dallas, TX · On-site

Write highly concurrent, multi-threaded Java backend services capable of handling real-time AI ... quantitative field. AI & LLM Foundational Knowledge: Hands-on experience or academic projects ...

Meds

Senior Software Engineer

Austin, TX

$121K - $160K/yr

Azure DevOps Notable Projects & Accomplishments * Telemedicine Platform: Proprietary system with ... Examples are TypeScript, Javascript, Python, Go, C++, Java, etc Ideal Profile * Has written lots of ...

Copart, Inc.

Software Engineering Intern

Dallas, TX · On-site

Write highly concurrent, multi-threaded Java backend services capable of handling real-time AI ... quantitative field. AI & LLM Foundational Knowledge: Hands-on experience or academic projects ...

Omni Inclusive

Cloud Data Engineer

Houston, TX · On-site

$109K - $131K/yr

... DevOps practices. 5 years of cloud data solution design experience with PaaS/SaaS applications. 4 ... Intellectual curiosity along with excellent problem-solving and quantitative skills. Experience ...

Quanta Search

Senior Software Engineer (Python)

Houston, TX · On-site

$117K - $154K/yr

As a Senior Research Software Engineer based in Houston, TX you'll support quantitative and ... Proficiency in Java or C++, particularly in relation to backend infrastructure. * Demonstrated ...

Quanta Search

Senior Software Engineer (Python)

Houston, TX · On-site

$117K - $154K/yr

As a Senior Research Software Engineer based in Houston, TX you'll support quantitative and ... Proficiency in Java or C++, particularly in relation to backend infrastructure. * Demonstrated ...

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Java Quant Developer information

How does a Java Quant Developer typically collaborate with quantitative analysts and traders within a financial firm?

As a Java Quant Developer, you will work closely with quantitative analysts (quants) and traders to translate complex mathematical models into robust, efficient code. Collaboration often involves frequent discussions to clarify model specifications, optimize algorithms for speed, and ensure accurate integration with trading platforms. You'll participate in code reviews, daily stand-ups, and sometimes even sit on the trading floor to gain firsthand insights into how your solutions impact trading strategies. This close teamwork helps ensure that models are delivered quickly and perform reliably in real-market conditions.

What are the key skills and qualifications needed to thrive as a Java Quant Developer, and why are they important?

To thrive as a Java Quant Developer, you need strong programming skills in Java, a solid grasp of quantitative finance, and typically a degree in computer science, mathematics, or a related field. Familiarity with financial libraries, statistical analysis tools, and experience using version control systems like Git are commonly expected, along with knowledge of databases such as SQL. Exceptional analytical thinking, problem-solving ability, and effective communication skills help you collaborate with traders and other stakeholders. These capabilities ensure the development of robust, efficient trading solutions that meet complex financial requirements and perform reliably in high-stakes environments.

What is a Java Quant Developer?

A Java Quant Developer is a software engineer who specializes in developing quantitative models and trading systems using the Java programming language. They work closely with quantitative analysts (quants) to implement mathematical models that help financial firms make trading decisions, manage risk, and analyze large datasets. Their responsibilities typically include designing, coding, testing, and optimizing high-performance applications for financial markets. A strong background in mathematics, finance, and computer science is usually required, along with expertise in Java and related technologies.
What are popular job titles related to Java Quant Developer jobs in Texas? For Java Quant Developer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Java Quant Developer jobs in Texas look for? The top searched job categories for Java Quant Developer jobs in Texas are:
What cities in Texas are hiring for Java Quant Developer jobs? Cities in Texas with the most Java Quant Developer job openings:
Java Quant Developer jobs near you
Senior Machine Learning Engineer, DevOps/SRE

Senior Machine Learning Engineer, DevOps/SRE

Roku

Austin, TX

$128K - $165K/yr

Other

Posted 22 days ago

Key responsibilities

  • Lead the design and operation of scalable, production-grade cloud infrastructure for ML workloads across AWS and GCP.

  • Architect and improve CI/CD systems for ML models and platform services to enable fast, reliable, and safe production releases.

  • Own and evolve low-latency infrastructure for real-time model inference, including KV store and vector databases.

Job description

About the team 

The Advertising Performance group focuses on performance for all participants in the Advertising ecosystem - Advertisers, Publishers, and Roku. The systems and solutions span multiple disciplines and technologies to perform real-time multi-objective optimization across distributed systems at large scale and with low latency. We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems, and Auction Dynamics to solve a large set of complex problems. At the core of this is our Machine Learning, Experimentation, and Inference Platform, which powers the entire landscape, and we continuously evolve. 

About the role 

We are seeking a talented and experienced Senior Software Engineer, MLOps/DevOps, to join the Advertising Performance team and play a critical role in supporting and scaling our Machine Learning infrastructure. The ideal candidate has a strong background in DevOps/SRE practices, cloud infrastructure management, and MLOps tooling - with a passion for building platforms that accelerate ML experimentation and deployment at internet scale. 

You will partner closely with ML Scientists and Engineers to streamline the end-to-end ML lifecycle across training, evaluation, deployment, and monitoring - on top of a modern, cloud-native stack running on GCP and AWS using Kubernetes, Apache Airflow, Spark, Ray, MLflow, Chronon, etc.

 What you'll be doing 
  • Lead the design and operation of scalable, production-grade cloud infrastructure for ML workloads across AWS and GCP, including GPU/TPU-based training and inference environments
  • Architect and improve CI/CD systems for ML models and platform services to enable fast, reliable, and safe production releases
  • Own and evolve low-latency infrastructure for real-time model inference, including KV store and vector databases
  • Define and enforce observability standards for ML systems, including model performance monitoring, drift detection, capacity planning, and pipeline health metrics
  • Participate in on-call rotation, leading incident response and root-cause analysis for critical ML training and serving infrastructure
  • Partner with data scientists and ML engineers to improve platform usability, accelerate model iteration, and implement strong MLOps and SRE best practices
  • Champion operational excellence across ML infrastructure through automation, resilience engineering, disaster recovery planning, and continuous improvement
We're excited if you have 
  • BS or MS in Computer Science, Engineering, or a related quantitative field
  • 8+ years of experience in DevOps, SRE, or ML infrastructure, including 4+ years supporting large-scale ML or AI systems
  • Strong programming skills in Python and/or Scala or Java for platform automation and tooling
  • Deep experience with Kubernetes and container orchestration on GCP (GKE) and/or AWS (EKS)
  • Expertise with NoSQL or low-latency data stores such as Aerospike or similar technologies
  • Hands-on experience with data and orchestration technologies such as Apache Spark, Apache Flink, Apache Airflow, and Kafka
  • Experience building and maintaining CI/CD systems using tools such as Jenkins or GitLab Runner
  • Familiarity with feature engineering platforms such as Chronon and model lifecycle tools such as MLflow
  • Strong infrastructure-as-code experience with Terraform or similar tooling
  • Experience with observability platforms such as Prometheus, Grafana, and Datadog
  • Excellent communication and cross-functional collaboration skills
  • Experience in the Advertising domain is a plus 
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