The ideal candidate will contribute to alpha research, signal development, and strategy implementation in a dynamic and fast-paced environment. This role offers significant career growth.

Principal Responsibilities:

Work closely with the Senior Portfolio Manager to develop systematic macro strategies, focusing on alpha research, including idea generation, data preprocessing, statistical analysis, backtesting, and implementation.

Contribute to and enhance the internal research platform, including data pipelines, statistical learning tools, alpha analytics, and backtesting frameworks.

Independently explore and develop new alpha ideas while collaborating in a transparent and team-oriented environment.

Preferred Technical Skillset:

Strong research and programming skills, with proficiency in Python.

Solid experience with data analytics libraries (e.g., Pandas, SciPy, NumPy, Polars); extensive library-building experience is a plus.

Masters or PhD degree in a quantitative subject such as Applied Mathematics, Statistics, Physics, Engineering, Financial Engineering, Computer Science, or related field from a top-ranked university. Strong candidates with Bachelor's degree will also be considered.

Exceptional problem-solving abilities, intellectual curiosity (especially in alpha research), and a proactive research mindset.

Creativity and out-of-the-box thinking, combined with rigorous quantitative analysis.

Preferred Experience:

2+ years of experience in quantitative research with a focus on systematic macro strategies.

Preferred experience in hedge fund alpha research in commodities, FX, equity, and bond futures.

Experience in macro intraday strategies is a strong plus.

Experience in trading cost analysis is a plus.

Experience in machine learning is a plus.

Target Start Date:

Up to 12 months (strong preference for candidates who can start sooner)

Millennium pays a total compensation package which includes a base salary, discretionary performance bonus, and a comprehensive benefits package. The estimated base salary range for this position is $150,000 to $200,000, which is specific to New York and may change in the future.

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You will collaborate closely with our technical teams to support the development and refinement of new AI capabilities, with a particular emphasis on quantitative trading domains.

Your expertise will help select and solve challenging problems in systematic and quantitative strategies , including statistical arbitrage, factor investing, market microstructure modeling, high-frequency / execution algorithms, risk premia harvesting, machine learning-based alpha generation, and portfolio optimisation under realistic constraints.

This role requires strong analytical thinking, rapid adaptation to evolving guidelines, and the ability to provide rigorous, technically sound critiques and solutions in a fast-moving environment.

As a Quantitative Trader, you will directly contribute to xAI's mission by helping train and refine our frontier AI models.

You will teach the models how quantitative traders reason, model markets, evaluate signals, manage risk, and interact with complex financial data and systems.

This involves providing high-quality data in various formats (text, voice, video), writing detailed annotations, critiquing model outputs, recording audio explanations, and occasionally participating in structured video sessions.

We are looking for individuals who are enthusiastic about these data-generation activities, as they form a core part of advancing xAI’s goals in scientific discovery and real-world reasoning.

Quantitative Traders provide labeling, annotation, evaluation, and expert reasoning services across text, voice, and video data modalities to support model training and evaluation.

The role may include recording audio responses, participating in video-based tasks, or producing step-by-step quantitative reasoning traces , all of which are essential job functions required to fulfill xAI’s mission.

All outputs are considered work-for-hire and owned by xAI.

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The bottleneck has shifted downstream - to merge conflicts, flaky tests, inconsistent code quality, and dozens of other frictions that drain productivity and morale. Engineering teams that can stay focused on designing, implementing, and delivering software will build magical, high-quality projects - and they'll be happier doing it.

We're building a CI Reliability Platform that empowers teams to land code faster and develop happier.

We are looking for a motivated and experienced Senior Software Engineer to join our Platform/Data Engineering team. In this role, you will be responsible for developing and optimizing data ingestion pipelines that can handle vast amounts of real-time and batch data from various sources.

Your focus will be on designing systems that are scalable, reliable, and performant, as well as ensuring the proper integration of data across our entire ecosystem.

Responsibilities

• Design, build, and maintain scalable data ingestion pipelines to handle large volumes of structured and unstructured data.
• Optimize and improve the efficiency of existing data processing workflows, ensuring they can scale as the data grows.
• Collaborate with cross-functional teams to gather data requirements and ensure seamless integration with various data sources.
• Implement real-time and batch processing systems for ingesting data from APIs and webhooks.
• Ensure data quality, consistency, and integrity across all data pipelines.
• Troubleshoot and resolve performance bottlenecks and data-related issues in the ingestion pipeline.
• Develop monitoring and alerting systems to proactively manage the health of data pipelines.
• Continuously evaluate and adopt new technologies and tools to improve the scalability and performance of our systems.
• Document the design, implementation, and operations of data pipelines for knowledge sharing within the team.

Requirements

• 4-5+ years of professional software engineering experience
• You're located within commute distance of San Francisco and are willing to work in office at least 8 days per month.
• You have experience in areas such as databases, distributed systems, service-oriented architectures, and data infrastructure
• You derive joy from refactoring and building clean abstractions in order to make complex systems fun to develop on and easy to understand
• Excellent debugging and troubleshooting skills and the tenacity to drive a solution to a conclusion
• Experience and intuition to zero in on root causes for bugs that can leave others stumped
• The ability to operate independently, but know when you are in too deep and need to ask for help
• Ability to collaborate with colleagues to plan and execute the best solution

Tech Stack

• Frontend: Typescript, React, Next.js, AWS
• Backend: Typescript, Node, AWS
• Data pipelines: Dagster, python, polars
• CI/CD: GitHub Actions

Benefits

• Unlimited PTO
• Competitive salary and equity
• Work-life balance
• Lunch ordered in on us at the office on Wednesdays and Thursdays
• Few meetings, so you can ship fast and focus on building
• One Medical membership on us!
• Top-notch medical, dental, vision, short-term disability, long-term disability, and life insurance
• All insurance is 100% company-paid ($0 premiums) for employees and highly subsidized for dependents
• FSA, HSA with company contributions, and pre-tax commuter benefits
• 401(k) plan
• Paid parental leave (up to 12 weeks)

The salary and equity range for this role are: $170K - $210K and .15% - .35%.

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Technical Skills:

• Evolve our architecture from decentralized reporting scripts to a centralized, framework-based delivery system
• Build automated validation and reconciliation that lets us scale without adding manual oversight

Complexity and Impact of Work:

• Design data models that become a trusted, shared source of truth for downstream product teams and external APIs
• Navigate complexity across multiple product data streams, applying consistent logic to all financial statements

Organizational Knowledge:

• Work with Product and Foundations teams to standardize how we capture and represent financial data
• Create self-service frameworks so other teams can add new report types through configuration instead of code

Communication and Influence:

• Listen to product stakeholders to stay ahead of scaling needs for client-facing data
• Help mature our engineering culture by advocating for and modeling 'Data as a Product' principles and high-quality engineering standards

You may be a fit for this role if you:

• 7+ years building data systems: You have experience creating internal tools, frameworks, or engines that handle 10x scale
• Financial domain experience: You've worked in fintech, banking, or other environments where numbers matter. You understand what a 'Statement of Record' means and the precision it demands.
• Systems thinking: You consider the next 100 products, not just the current one. You value extensible systems over one-off pipelines.
• Solid technical foundation: You're proficient with Python (Pandas/Polars/Arrow) and SQL, with experience in BigQuery or similar cloud warehouses and modern orchestration tools like Airflow or Dagster.

Although not a requirement, bonus points if:

• You've been a data consumer: Prior experience as a financial or business analyst gives you the perspective to design truly usable data models.
• You care about performance: You enjoy making data move faster and cheaper, whether through ADBC, multiprocessing, vectorized operations, or other optimizations.

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What you'll do

• Troubleshoot and resolve complex production issues quickly across the full technology stack (backend, frontend, and data).
• Design, develop, and maintain scalable backend systems and data pipelines using Python and modern frameworks.

What you need

• Bachelor’s or Master’s degree in Computer Science, or 5+ years of hands-on professional software development experience.
• Experience building, shipping, and supporting scalable, cloud-hosted services.

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