As a Systematic Production Support Engineer, you will be responsible for building, developing, and maintaining a reliable, scalable, and integrated platform for trading strategy monitoring, reporting, and operations. You will work closely with portfolio managers and other internal customers to reduce operational risk through the implementation of monitoring, reporting, and trade workflow solutions, as well as automated systems and processes focused on trading and operations.

Key responsibilities include:

• Building, developing, and maintaining a reliable, scalable, and integrated platform for trading strategy monitoring, reporting, and operations
• Working with portfolio managers and other internal customers to reduce operational risk through the implementation of monitoring, reporting, and trade workflow solutions
• Implementing automated systems and processes focused on trading and operations
• Streamlining development and deployment processes

Technical qualifications include:

• 5+ years of development experience in Python
• Experience working in a Linux/Unix environment
• Experience working with PostgreSQL or other relational databases

Preferred skills and experience include:

• Understanding of NLP, supervised/non-supervised learning, and Generative AI models
• Experience operating and monitoring low-latency trading environments
• Familiarity with quantitative finance and electronic trading concepts
• Familiarity with financial data
• Broad understanding of equities, futures, FX, or other financial instruments
• Experience designing and developing distributed systems with a focus on backend development in C/C++, Java, Scala, Go, or C#
• Experience with Apache/Confluent Kafka
• Experience automating SDLC pipelines (e.g., Jenkins, TeamCity, or AWS CodePipeline)
• Experience with containerization and orchestration technologies
• Experience building and deploying systems that utilize services provided by AWS, GCP, or Azure
• Contributions to open-source projects

This is a unique opportunity to drive significant value creation for one of the world's leading investment managers.

XML job scraping automation by YubHub

This role directly supports portfolio management teams across Millennium, with operational excellence at the core. Our efforts are focused on delivering the highest quality returns to our investors – providing a world-class and reliable trading and technology platform is essential to this mission.

This is a unique opportunity to drive significant value creation for one of the world's leading investment managers.

Principal Responsibilities:

• Build, develop and maintain a reliable, scalable, and integrated platform for trading strategy monitoring, reporting, and operations.
• Work with portfolio managers and other internal customers to reduce operational risk through:
• Implementation of monitoring, reporting, and trade workflow solutions.
• Implementation of automated systems and processes focused on trading and operations.
• Streamlining development and deployment processes.
• Implementation of MCP servers focused on assisting rest of the Support Engineering team as well as proactively monitoring production environment.

Technical Qualification:

• 5+ years of development experience in Python.
• Experience working in a Linux / Unix environment.
• Experience working with PostgreSQL or other relational databases.
• Ability to understand and discuss requirements from portfolio managers.

Preferred Skills and Experience:

• Understanding of NLP, supervised/non-supervised learning and Generative AI models.
• Experience operating and monitoring low-latency trading environments.
• Familiarity with quantitative finance and electronic trading concepts.
• Familiarity with financial data.
• Broad understanding of equities, futures, FX, or other financial instruments.
• Experience designing and developing distributed systems with a focus on backend development in C/C++, Java, Scala, Go, or C#.
• Experience with Apache / Confluent Kafka.
• Experience automating SDLC pipelines (e.g., Jenkins, TeamCity, or AWS CodePipeline).
• Experience with containerization and orchestration technologies.
• Experience building and deploying systems that utilize services provided by AWS, GCP or Azure.
• Contributions to open-source projects.

The estimated base salary range for this position is $100,000 to $175,000, which is specific to New York and may change in the future. Millennium pays a total compensation package which includes a base salary, discretionary performance bonus, and a comprehensive benefits package. When finalizing an offer, we take into consideration an individual's experience level and the qualifications they bring to the role to formulate a competitive total compensation package.

XML job scraping automation by YubHub

We're excited to offer PhD machine learning engineering internships for the summer of 2026. As an intern, you'll contribute to critical projects that directly enhance Stripe's suite of products, focusing on areas such as foundation models used for dozens of tasks e.g. fraud detection, enhanced support, and predicting user behavior.

Responsibilities

• Develop and deploy large-scale machine learning systems that drive significant business value across various domains.
• Engage in the end-to-end process of designing, training, improving, and launching machine learning models.
• Write production-scale ML models that will be deployed to help Stripe enable economic infrastructure access for a diverse range of businesses globally.
• Collaborate across teams to incorporate feedback and proactively seek solutions to challenges.
• Rapidly learn new technologies and approaches, demonstrating a strong ability to ask insightful questions and communicate the status of your work effectively.

Who We're Looking For

• A deep understanding of computer science, obtained through the pursuit of a PhD in Computer Science, Machine Learning, or a closely related field, with the expectation of graduating in winter 2026 or spring/summer 2027.
• Practical experience with programming and machine learning, evidenced by projects, classwork, or research. Familiarity with languages such as Python, Scala, Spark and libraries such as Pandas, NumPy, and Scikit-learn.
• Expertise in areas of machine learning such as supervised and unsupervised learning techniques, ML operations, and possibly experience in Large Language Models or Reinforcement Learning.
• Demonstrated ability to work on collaborative projects, with experience in receiving and applying feedback from various stakeholders.
• A proactive approach to learning unfamiliar systems and a demonstrated ability to understand complex systems independently.

What We Offer

• Join us for an unforgettable summer internship and help shape the future of global commerce.
• At Stripe, you won't just be working on theoretical projects; you'll make a tangible impact on the world's economic infrastructure.

XML job scraping automation by YubHub

The role reports to the Director, Machine Learning Science. This role can be a Hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.

Key responsibilities include:

• Independently pursuing cutting-edge research in AI applied to biological problems
• Building new models or fine-tuning existing models to identify biological changes resulting from disease
• Building models that achieve high accuracy and that generalise robustly to new data
• Applying contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model, ideally suggesting potential biological mechanisms
• Working closely with ML Engineering partners to ensure that Freenome's computational infrastructure supports optimal model training and iteration
• Taking a mindful, transparent, and humane approach to your work

Requirements include:

• PhD or equivalent research experience with an AI emphasis and in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics
• 3+ years of postdoc or post-PhD industry experience achieving impactful results using relevant modelling techniques
• Expertise, demonstrated by research publications or industry achievements, in applied machine learning, deep learning and complex data modelling
• Practical and theoretical understanding of fundamental ML models like generalised linear models, kernel machines, decision trees and forests, neural networks
• Practical and theoretical understanding of DL models like large language models or other foundation models
• Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning
• Proficient in current state of the art in ML/DL approaches in different domains, with an ability to envision their applications in biological data
• Proficiency in a general-purpose programming language: Python, R, Java, C, C++, etc.
• Proficiency in one or more ML frameworks such as; Pytorch, Tensorflow and Jax; and ML platforms like Hugging Face
• Experience in ML analysis and developer tools like TensorBoard, MLflow or Weights & Biases
• Excellent ability to communicate across disciplines, work collaboratively, and make progress in smaller steps via experimental iterations
• A passion for innovation and demonstrated initiative in tackling new areas of research

Nice to have qualifications include:

• Deep domain-specific experience in computational biology, genomics, proteomics or a related field
• Experience in building DL models for genomic data, with knowledge of state-of-the-art DNA foundation models
• Experience in NGS data analysis and bioinformatic pipelines
• Experience with containerized cloud computing environments such as Docker in GCP, Azure, or AWS
• Experience in a production software engineering environment, including the use of automated regression testing, version control, and deployment systems

XML job scraping automation by YubHub

Location

San Francisco

Employment Type

Full time

Department

Intelligence & Investigations

Compensation

• $198K – $320K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

Benefits

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the Team

The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal and external partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits humanity.

About the Role

As a Quantitative Intelligence Analyst, you will focus on discovering novel and emerging risks in complex human–AI systems before they are well-defined, measurable, or widely understood.

Responsibilities

• Discover and define new quantitative risk signals where no established metrics exist, using subject matter expertise to surface early, weak, or unconventional indicators

• Translate complex trust and safety challenges into measurable signals that can be tracked and stress-tested over time

• Develop upstream early-warning and signal frameworks that inform downstream detection and mitigation efforts

• Analyze risk trends to assess the underlying drivers and causal factors behind those changes

• Conduct data mining and statistical modeling to understand how risks originate, evolve, and propagate across systems

• Design adversarial scenarios, and quantitative stress tests to assess exposure, coverage gaps, and vulnerabilities

• Produce clear data-driven briefs to support risk prioritization, contingency planning, and strategic risk products across teams

Requirements

• Have 3–6+ years of experience in quantitative intelligence analysis, trust & safety, security analysis, or risk-focused research

• Are comfortable working on complex trust and safety domains such as child safety, violent activities, self-harm, or similar high-stakes risk areas

• Familiarity with data mining, statistical modeling, and supervised learning methods

• Understand how to monitor signals or models for data drift, behavioral adaptation, or performance degradation over time, and can diagnose likely causes

• Experience in operationalizing adversarial or strategic risk behaviors, including through red-team exercises, agent-based modeling, or structured scenario analyses

• Comfortable working with Python and SQL

• Nice to have: Experience with quantitative stress testing or Monte Carlo simulations to assess uncertainty and tail risk

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI and work to ensure that our technology is developed and used responsibly.

XML job scraping automation by YubHub