AM.Dirac Logo

AM.Dirac

AI/ML Engineer

Reposted 24 Days Ago
Remote
Hiring Remotely in United States
Mid level
Remote
Hiring Remotely in United States
Mid level
Design and productionize ML models and agentic systems for intraday financial alpha generation. Build data pipelines, experiment frameworks, and portfolio optimization methods. Collaborate with quants and engineers to move models from research to live trading environments.
The summary above was generated by AI

AI/ML Engineer – Full Time
Location: Remote or Hybrid (Location Flexible)
Start Date: Rolling
Company: AM.Dirac, Quantitative Proprietary Trading Firm

About AM.Dirac

AM.Dirac is an AI-forward quantitative trading firm applying machine learning and programmatic reasoning to public market strategies. We use frontier ML capabilities to automate and scale our alpha-generating infrastructure across asset classes. Our team combines deep expertise in ML engineering, quant research, and systems design, working collaboratively to develop intelligent agents that operate in real-time, data-rich environments.

Position Overview

We are looking for a full-time AI/ML Engineer to join the core team at AM.Dirac. This is an opportunity to build intelligent systems that power next-generation trading strategies, from idea generation to execution. You’ll work at the intersection of state-of-the-art ML (including LLMs and agentic systems), portfolio optimization, and real-time data pipelines. Your work will directly support live strategies in production and lay the foundation for autonomous investment agents.

Key Responsibilities
  • Alpha Generation: Design and refine predictive ML models trained on intraday financial data and alternative datasets to surface trade signals.

  • Data Infrastructure & Experimentation: Work with large-scale time series, macroeconomic, and unstructured datasets. Build pipelines, clean data, and rapidly iterate on hypotheses.

  • Agentic Systems Development: Help architect and implement systems using LLMs to automate alpha research, backtesting, and live trading tasks.

  • Portfolio Optimization: Contribute to the design of intelligent portfolio construction methods that integrate learned signals and risk constraints.

  • Tooling & Research Ops: Develop internal experimentation frameworks in Python/Jupyter and build reproducible research workflows across the team.

  • Collaboration: Work closely with quant researchers, founders, and systems engineers to scale model impact from prototype to production.

Qualifications

Required:

  • Education: BS in Computer Science, Machine Learning, or related field (MS/PhD preferred). Exceptional candidates without a degree but with strong evidence of technical ability will be considered.

  • Python & Jupyter Expertise: Demonstrated fluency with Python, NumPy, pandas, scikit-learn, and Jupyter for ML development and research.

  • ML Proficiency: Experience with supervised learning, time series modeling, and neural networks. Bonus points for hands-on use of LLMs or reinforcement learning frameworks.

  • Experimentation Mindset: Ability to rapidly test, measure, and iterate on model-based systems in noisy or nonstationary environments.

  • Curiosity for Markets: While no prior finance experience is required, you should be motivated to learn how markets behave and how ML can exploit inefficiencies.

Preferred:

  • LLM & Agentic Workflows: Familiarity with prompting strategies, RAG, fine-tuning, or frameworks like LangChain, Transformers, or OpenAI APIs. Experience working with messy and unstructured data as inputs to modeling tasks.

  • Open Source Contributions or Research: Active GitHub, blog posts, or published work showing initiative and originality in applied ML.

  • Quantitative Finance: Experience building backend infrastructure for algorithmic trading and conducting research to originate market signals and trading strategies highly preferred.

Why Join Us
  • High Impact, Early Team Role: Shape the design and function of our AI-native investment platform from the ground up.

  • Research-to-Production: See your work go from notebook to production in live trading strategies.

  • Fast Iteration, Deep Focus: No bureaucracy, no endless meetings. Just focused execution with elite peers.

  • Compensation: Competitive base salary + performance-linked bonus + benefits.

  • Culture: Intellectually honest, independently driven, and curious about the edge of AI and finance.

Application Process

Interested candidates should submit:

  • Resume/CV highlighting your technical background and ML experience

  • Optional: Links to open-source projects, GitHub repos, or writing samples

  • Brief note (if you'd like) on why you're excited about joining an AI-native trading firm

AM.Dirac is an equal opportunity employer. We value diverse perspectives and are committed to building a team that reflects a wide range of backgrounds and experiences.

Similar Jobs

7 Days Ago
In-Office or Remote
146K-250K Annually
Senior level
146K-250K Annually
Senior level
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Lead design, development, and enterprise deployment of scalable production ML/AI solutions for pharmacy services. Own MLOps pipelines, model training, validation, containerized deployment, monitoring, and architecture. Collaborate with data scientists, engineers, and business leaders, evaluate emerging AI/LLM technologies, and provide technical leadership and mentorship.
Top Skills: AWSAzureCi/CdContainerizationDockerGCPGenerative AiKubernetesLlmsMlopsNoSQLPythonPyTorchRagScikit-LearnSparkSQLTensorFlowTerraform
8 Days Ago
Remote or Hybrid
120K-215K Annually
Senior level
120K-215K Annually
Senior level
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Design, build, and deploy AI/ML and generative AI solutions and full-stack applications. Develop frontend experiences, backend services, microservices, APIs, and cloud-native data integrations. Implement RAG, LLMs, vector DBs, dashboards, reporting, and self-service analytics to support quality, patient safety, and workflow automation. Provide technical leadership, mentor engineers, and apply CI/CD, testing, observability, security, and performance best practices.
Top Skills: AgentsApache SupersetAutomated TestingAWSAzureAzure Ai ServicesCi/CdDatabricksEvent-Driven ArchitectureGCPGenerative AiJavaJavaScriptLangchainLlmsMicroservicesMicrosoft FabricObservabilityOpenaiPower BIPrompt EngineeringPythonRagReactRest ApisSemantic KernelSnowflakeSpring BootSQLTypescriptVector Databases
8 Days Ago
Remote or Hybrid
171K-261K Annually
Senior level
171K-261K Annually
Senior level
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Lead development and operation of CI platform components (RBE, FUSE) to enable scalable build, test, and developer workflows. Collaborate across teams, own projects end-to-end, drive engineering best practices, mentor engineers, perform design/code reviews, and support integration of internal tools with the FUSE-based file system to improve developer productivity for AV and ML workloads.
Top Skills: FuseGoLinuxNetworkingPythonRemote Build Execution (Rbe)Ssh

What you need to know about the Los Angeles Tech Scene

Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.

Key Facts About Los Angeles Tech

  • Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
  • Key Industries: Artificial intelligence, adtech, media, software, game development
  • Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
  • Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account