Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

Your future role within QRT

We are seeking a pragmatic and commercially oriented Production Support Engineer with a strong Site Reliability Engineering (SRE) orientation to join our Risk Technology team. This role is primarily focused on ensuring stability, availability, and performance of critical trading, risk, and PnL systems in a fast-paced production environment.

The ideal candidate will have a solid background in supporting production systems, combined with an SRE mindset focused on automation, reliability, and continuous improvement. You will be responsible for monitoring live systems, managing incidents, troubleshooting complex issues, and driving initiatives that enhance system resilience and reduce operational overhead.

In addition to hands-on production support, you will contribute to improving system reliability through automation, proactive monitoring, and collaboration with development and infrastructure teams. You will play a key role in bridging support and engineering by identifying recurring issues, performing root cause analysis, and implementing long-term fixes aligned with SRE principles.

You will work closely with internal and external teams to ensure effective management, scalability, and reliability of the QRT Risk Technology stack while maintaining a strong focus on business continuity and operational excellence.

What will you do

• Provide end-to-end production support alongside the global team for post trade flows, ensuring high availability and performance
• Monitor production systems, investigate alerts, and respond to incidents in a timely manner
• Automate repetitive operational tasks to reduce manual intervention
• Perform root cause analysis (RCA) and implement preventive measures
• Troubleshoot issues across applications, infrastructure, and data layers
• Collaborate with development teams to improve system stability and release quality
• Ensure data quality and integrity across risk and PnL workflows
• Participate in on-call rotations and handle production incidents
• Participate in operational processes improvements, incidents management, and resolutions

Requirements

• Strong understanding of production support and incident management processes
• Experience with operating and configuration of monitoring, alerting, and logging tools
• Good understanding of system architecture and cloud technologies (AWS preferred)
• Proficiency in Python for troubleshooting and automation
• Strong analytical, problem-solving skills and ability to function independently.
• Ability to work in a fast-paced, business-critical environment
• Effective communication skills across technical and business stakeholders
• Commercially oriented mindset with focus on business impact
• Prior experience in finance is preferred but not required

Your present skillset

• 4+ years of experience in production support, or software engineering
• Strong Python skills and (good to have ) understanding of object-oriented programming
• Experience using pandas DataFrame for data analysis
• Experience with cloud platforms (AWS preferred)
• Experience with monitoring tools such as Prometheus, Grafana, or similar
• Strong problem-solving skills with a proactive approach
• Clear communication skills and ability to articulate complex ideas
• Good time management and prioritization skills
• Familiarity with risk and PnL concepts (good-to-have)
• Exposure to time-series data and tools like InfluxDB (good-to-have)
• Familiarity with REST APIs, Containers, Kubernetes, and SQL Server (good-to-have)
• UI development experience with Plotly Dash and/or Streamlit (good-to-have)

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

At IMC, technology is not a department; it’s at the heart of everything we do. Developed in house, our innovative software makes millions of trading decisions daily, and we win by making better and faster decisions than our competition.

IMC’s Sydney based Engineering teams work on a wide variety of applications, tools and functionalities, including trading algorithm implementations, option pricing, calculating volatility, simulation frameworks, market risk applications, trade reconciliation applications and data analysis & visualization tools for traders. We frequently need to develop not just the business applications themselves, but also the tools that keep our development process at the cutting edge. We are currently looking to expand our software engineering teams across our Strategy, Research tooling and Backbone teams.

The Strategy Developers work alongside our Sydney-based options research and trading teams in designing and implementing systematic trading strategies. You will be responsible for engineering efforts in a Python-based ecosystem that empowers our researchers and traders to develop strategies from initial prototypes to production. In this role, you will also be involved in the tactical development of front-office trading, analysis, and visualization tools.

The Backbone Developers create scalable business critical applications and tools to automate tasks supporting IMC’s Sydney Mid-Office and Risk Management departments. They gather requirements and feedback from a range of internal stakeholders in order to implement creative automation solutions via innovative coding practices.

The Research Tooling Developers collaborates closely with APAC Quant Research and other engineering teams to build and enhance tools that drive cutting-edge quantitative research. Our systems empower researchers to run large-scale computations on distributed clusters, enabling the exploration of new trading strategies, model training, and back testing.

Your Core Responsibilities: 

• Develop, test, deploy, and maintain high-performance Python applications.
• Work closely with traders, researchers, quants, and fellow engineers to build scalable and reliable software solutions.
• Take ownership of end-to-end development, from requirements gathering to production deployment.
• Implement automation and optimization projects to enhance trading and research workflows.
• Apply advanced automated testing practices and leverage daily deployments to achieve agile and incremental benefits.
• Balance trade-offs between latency, throughput, simplicity, scalability, and maintainability in a complex technology landscape.

Your Skills and Experience: 

• 5+ years of professional software engineering experience, with a strong focus on Python.
• Experience working with numerical computing and data processing frameworks such as Pandas, NumPy, SciPy, Celery, Dask, or Spark.
• Strong problem-solving skills and the ability to proactively tackle technical challenges.
• Experience with automated testing and CI/CD pipelines.
• Familiarity with Docker, Kubernetes, and Linux environments.
• Exposure to distributed computing and modern cloud-based data processing technologies.
• Strong communication skills and the ability to work with cross-functional teams including traders, researchers, and other engineers.
• Prior knowledge of financial markets or trading is not required, but curiosity and a willingness to learn are essential.

#LI-DNI

At The Trade Desk, we build technology that’s reshaping the future of digital advertising — with a mission to make the open internet better for everyone through principled, intelligent advertising.  

Handling over 1 trillion queries per day, our platform operates 24/7, across continents and data centers, processing petabytes of data to deliver meaningful insights and measurable outcomes.

Our engineers are true end-to-end owners — designing, building, and delivering high-impact, data-driven systems that power decisions for advertisers globally. We thrive in an environment built on trust, empathy, collaboration, and shared ownership, where everyone has the autonomy to make meaningful impact.

We believe great systems are built by teams that trust each other, value craftsmanship, and take ownership of what they create. 

ABOUT THE ROLE: 
 

The Measurement Upper Funnel engineering team is based in APAC, with members in Hong Kong, Shanghai, and Sydney. Our Product Manager is based in West Coast, and we have a 30 mins virtual standup every morning to sync up. We are a distributed team by design and rely heavily on technology such as asynchronous messaging and video conferencing to stay informed and connected.

We have a highly productive technology team that enjoy a collaborative work environment that has involvement in end-to-end delivery of scalable technology solutions. We have a mindset of build it, ship it, own it.  Our teams are empowered to use the best tools and technologies for the job. We have a multi-cloud environment and we are going towards the microservices architecture. 

We develop our client facing products utilising .Net/.Net Core, Javascript (React), gRPC, REST API’s, Docker containers and Kubernetes.  We developed our big data processing backend utilizing Apache Spark and Flink.

• As end-to-end owners, our engineers actively participate in every stage of product development — from design and implementation to deployment and monitoring — delivering real impact for our clients. We work across a broad and evolving technology landscape, including Docker, Kubernetes, Terraform, GitLab, Bamboo, SonarQube, AWS, Azure, Aliyun, Databricks, and databases such as SQL Server, Vertica, and ClickHouse.
• We continuously explore new technologies and AI-powered tools that make us smarter and more efficient, embracing pragmatic innovation as our projects evolve.
• Quality is core to everything we build. We emphasize code reviews, automated testing, robust deployment pipelines, metrics, and continuous monitoring to ensure reliability and maintainability at scale.
• Our engineers also make an impact beyond code — through mentorship, teaching, leading by example, and participating in hiring and community building — helping shape a team culture grounded in trust, learning, and excellence. 

Who We Are Looking For: 

Skills and experience 

• Proven skills and interest in programming (C#, Java, or equivalent)
• Proven skills in SQL to query data from databases.
• Understanding of designing web-based and microservices architecture
• Understanding of Agile development methodology and development practices
• Experience in cloud-based platform experience (AWS, Azure or Aliyun)
• Understanding of database technologies such as row-based vs column-based RDBMS, Document, Key-Value.
• Understanding of data analytics tools and frameworks such as Apache Spark or Databricks, and familiarity with Python-based data analysis (e.g. NumPy or Pandas) is preferred.
    

Key Attributes 

• What and how you can contribute is what's important to us. Our consideration is not limited by the kind of education you have or the specific technologies you have experience with. Variety of technical challenge is one of the best things about working at The Trade Desk as an engineer, but we do not expect you to know every technology we use when you start. What we care about is that you can learn quickly and solve complex problems using the best tools for the job. 
• You are a creative thinker, not bound by "the way things have always been done". You can distill facts and insights to guide your work, and turn data into actionable decisions. What you know is less important than how well you learn and innovate. We don't need engineers who know all the answers; we need engineers who can invent the answers no one has thought of yet, to the questions yet to be asked.  
   

What we Offer: 
 

You will also get the opportunity, depending on your interests and aptitude, to work on large-scale distributed systems coordinating thousands of servers in cloud and physical data centers around the world, petabyte-scale data challenges, machine learning, advanced visualizations, and interactive user interfaces. 

There are a ton of reasons why TTD is a great company to work for, but here are the top 6 that we think you'll find most interesting: 

• We are a globally collaborative environment. You will have the opportunity to work with brilliant & diverse teams from all over the world  
• We celebrate continuous learning at TTD – here you will have opportunities to be sponsored for further education, certifications and we also have an in-house learning platform to support your further development 
• Our culture - We have a wonderful team of brilliant high achievers built on a culture of empathy, grit, collaboration, & ownership. We are an award-winning company – we have won ‘Great Place to Work’ awards across Australia, US, UK, Europe and Asia! 

• We offer an attractive compensation package, a flexible work environment, and beautiful offices with all the perks you’d expect — from snacks and catered lunches to wine and beer. You’ll also enjoy competitive equity and an employee stock purchase plan. We promote an environment of reward and recognition – At TTD, you will be recognised for your efforts and for each anniversary at TTD, we will celebrate you, and reward you for your contribution! 
• We promote an inclusive and diverse environment – we have many events and activities that truly make TTD a ‘Great Place to Work’ and promote inclusivity and diversity across our organisation. 

CSQ227R47

The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. Open to remote locations.

The impact you will have:

• Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI Research to solve customer problems
• Own production rollouts of consumer and internally facing GenAI applications
• Serve as a trusted technical advisor to customers across a variety of domains
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap

What we look for:

• Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
• Expertise in deploying production-grade GenAI applications, including evaluation and optimizations 
• Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
• Passion for collaboration, life-long learning, and driving business value through AI
• [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets

WHAT YOU'LL DO

Our Data Scientist, AI Deployment team is a group of creative technical experts who design and build end-to-end machine learning solutions that power 1-to-1 personalization for some of the world's leading brands. In this role, you will:

• Design RL use cases from the ground up — scoping solutions that optimize for real business value, accounting for the complexity of modern marketing journeys, and proactively identifying risks to set each engagement up for success
• Build and own the full ML pipeline —  taking customers' raw data through transformation, model training, and activation, so that model decisions are delivered to personalize experiences for millions of end users
• Drive customer success by being providing ongoing technical guidance that ensures data science performance, successful adoption and measurable outcomes
• Extend product capabilities by developing features and tools that support the broader AI deployment team and scale what's possible across engagements
• Partner with the Braze Product team to refine and advance Braze's reinforcement learning algorithms, pushing the self-learning capabilities of the platform forward
• Shape BrazeAI product strategy and roadmap by bringing customer-facing insights and deep technical expertise to the table

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

WHAT YOU'LL DO

Our Data Scientist, AI Deployment team is a group of creative technical experts who design and build end-to-end machine learning solutions that power 1-to-1 personalization for some of the world's leading brands. In this role, you will:

• Design RL use cases from the ground up — scoping solutions that optimize for real business value, accounting for the complexity of modern marketing journeys, and proactively identifying risks to set each engagement up for success
• Build and own the full ML pipeline —  taking customers' raw data through transformation, model training, and activation, so that model decisions are delivered to personalize experiences for millions of end users
• Drive customer success by being providing ongoing technical guidance that ensures data science performance, successful adoption and measurable outcomes
• Extend product capabilities by developing features and tools that support the broader AI deployment team and scale what's possible across engagements
• Partner with the Braze Product team to refine and advance Braze's reinforcement learning algorithms, pushing the self-learning capabilities of the platform forward
• Shape BrazeAI product strategy and roadmap by bringing customer-facing insights and deep technical expertise to the table

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Core Development is a global team of technologists who architect, build and maintain our world-class trading platform. From optimizing our core trading engine to building custom hardware, we leverage software & hardware engineering, data science and research, to deliver the infrastructure and tools that drive our trading and business needs.

About the Role:

Our Software Engineer internship is an intensive 10-week experience at Jump Trading's Sydney (or Singapore) office. You will be working with the team that helps the business make sense of data. You will get to sharpen your Python skills, through the mentorship provided by our Software Engineers, by researching, analyzing and building high-impact solutions and products that connect data better with the daily trading environment. At Jump, you will experience a healthy work-life balance, a casual environment, and a flat management structure. Our internship program is the primary way we identify top young talent, and it’s a proven path for earning full-time opportunities at Jump.

What you’ll do:

• You will be working with our experienced engineers and receive ongoing feedback and coaching from a dedicated mentor throughout the summer.
• You will use your Python programming skills to build high-impact products, helping Jump tackle exciting new initiatives and streamline every part of the trade cycle.
• You will also be part of the team that collects and analyzes datasets, to identify patterns and gain insights, to discover new and creative opportunities and solutions.
• You will take on projects working on production code and gain experience with our full-cycle process for development, testing, and release.
• Other duties as assigned or needed

Skills You’ll need:

• Strong academic foundation with a Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a closely-related field
• Experience in using Python programming to investigate, make sense of, and improve on open-ended scenarios.
• Exposure to tools such as Pandas, NumPy, PyCharm
• Experience working with Linux/UNIX OS including advanced commands and shell scripts
• Understanding of networking concepts such as routing, multicast, ethernet
• Curiosity for all things trading and computer related, taking a rigorous, detail-oriented approach in all that you do.
• Desire to make an impact in a collaborative, cross-team environment with a positive can-do attitude
• Ability to operate independently and communicate clearly in the fast-paced environment of a daily live-trading operation
• Reliable and predictable availability

Also helpful, but not required:

• Past internship or job experience in a software engineering role

* No finance or economics study or work experience required

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incentivising collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organisations and universities to solve problems.

The global security team is a team of technologists that develop and contribute across the full security stack. You will be (or will become) a "T-shaped" individual with enormous potential to further your career in the security domain. The ideal candidate will be passionate about security operations and automation, with experience in more than one (Network security, cloud security, application security). The candidate will have a good ability to automate (using a language such as Python or Go) and understand risk-based approach to security.

What You'll Do:

- Automate processes and procedures to create a highly resilient security infrastructure.

- Implement and make recommendations based on threat assessments at the network, server, and endpoint levels.

- Involved in Threat, Vulnerability Management and Attack Surface reduction exercises.

- Assist in performing investigations of anomalous activity and creating actionable reports to senior management.

- Analyze data sets and produce reports using basic tools (e.g. SQL, Python, Pandas).

- Work highly independently, with multiple stakeholders outside of the formal management structure.

- Other duties as assigned or needed.

Skills You’ll Need:

- Comfort using a programming language for automation tasks (Python, Go, etc).

- Comfort using the Linux shell to understand and troubleshoot an overall system.

- Familiarity troubleshooting network issues in the stack.

- Understand DNS, SSL/ TLS, and how traffic on IP networks establishes end-to-end security and trust.

- Understand principles around secure Identity Management and Authentication.

- Passionate about high-quality of work and continuous improvement.

- Reliable and predictable availability.

Useful (but certainly not mandatory) skills:

- Relevant and well-regarded certifications in cloud computing such as CKA (Certified Kubernetes Administrator), AWS Professional or          Specialty levels, Google Professional level.

- Advanced security accreditation such as CISSP, OSCP, CASP, Security+.