AI/ML Engineer
AM.Dirac
WorldwideremotePosted 10 days ago
Skill Required
AI-ML-EngineerMachine-Learning-EngineerQuant-DeveloperQuantitative-ResearcherData-ScientistAI-ML-Software-EngineerMachine Learning EngineerAI EngineerAIMachine LearningDeep LearningEngineeringSystem Designrelated fieldScikit-learnTime SeriesLangChainbuildingJupyterPythonPandasdesignGitOpenAPINumPyAPIsGenerative AIRAGandGoFulltime
Key highlights
- Compensation: Competitive base salary + performance-linked bonus + benefits
- Location: Remote or Hybrid (Location Flexible)
- Requirement: BS in Computer Science, Machine Learning, or related field (MS/PhD preferred)
- Key Benefit: High Impact, Early Team Role
Role overview
AM.Dirac is an AI-forward quantitative trading firm applying machine learning and programmatic reasoning to public market strategies. We are looking for a full-time AI/ML Engineer to join the core team to build intelligent systems that power next-generation trading strategies, from idea generation to execution, working at the intersection of state-of-the-art ML (including LLMs and agentic systems), portfolio optimization, and real-time data pipelines.
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.
Requirements
- 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.
- 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.
Nice to have
- Hands-on use of LLMs or reinforcement learning frameworks.
- 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.
Benefits
- 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.
Additional details
- Location: Remote or Hybrid (Location Flexible)
- Start Date: Rolling
- Company: AM.Dirac, Quantitative Proprietary Trading Firm
- 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.
- Originally posted on Himalayas