MLabs
Staff AI Engineer
New York, United States · Staff+ · Full-time
No sponsorship$175k-$250kDetected 23 days ago
TypeScriptPythonGoDistributed SystemsMachine LearningData EngineeringLLMsMLOpsValuationRoboticsResearch
About the role
- The Staff AI Engineer will be responsible for moving beyond manual propagation of insights to a system where the fleet gets smarter with every trade.
- This is a high-stakes production role, not a research position.
Responsibilities
- Evaluation Frameworks: Build frameworks to quantify which signals and market conditions accurately predict profitable trades versus noise.
- Automated Strategy Generation: Develop systems to explore new configurations, backtest them against real fleet data, and surface candidates for deployment autonomously.
- Market Adaptation: Build mechanisms to detect shifts in market conditions (e.g., trending vs. choppy) and adapt fleet behavior in real-time.
- Autonomous Fleet Intelligence Fleet Monitoring: Create higher-order agents for automated monitoring to catch configuration errors and performance degradation across all concurrent agents.
- Performance Attribution: Decompose trades into component drivers-signal accuracy, execution efficiency, and exit timing-to feed insights back into strategy design.
- Coordination & Risk: Manage concentration risk and capital allocation across the fleet, balancing the exploration of new approaches with the exploitation of proven strategies.
- Data Capture: Build the telemetry and data capture layer to ensure every decision and outcome is structured and queryable.
- Domain-Specific Training: Determine the efficacy of domain-specific training over general-purpose prompting and build the necessary pipelines for implementation.
- Inference Optimization: Optimize inference for many concurrent agents, ensuring structured decision outputs and cost-efficiency at scale.
- Closed-Loop Systems: A track record of building systems where predictions lead to actions that generate outcomes, which then feed back into improved predictions.
Requirements
- Proven experience training, deploying, and maintaining models that run in production and directly impact business outcomes.
- Proficiency in Python is required, with additional comfort in Go or TypeScript for production services.
- Experience with fine-tuning and serving (PEFT/LoRA, vLLM, TGI) or custom inference pipelines.
- If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion.
- Software Engineering: Proficiency in Python is required, with additional comfort in Go or TypeScript for production services.
- LLM Specialization: Experience with fine-tuning and serving (PEFT/LoRA, vLLM, TGI) or custom inference pipelines.
Nice to have
- Background in signal generation, alpha research, portfolio optimization, or execution.
- Preferred Experience Financial ML: Background in signal generation, alpha research, portfolio optimization, or execution.
Compensation
- $175K - $250K We are hiring on behalf of our client who is developing a cutting-edge autonomous agent runtime focused on high-frequency financial environments.
- While current agents operate effectively as independent units, the next phase of evolution involves building a sophisticated intelligence layer where the entire fleet learns autonomously from real-time market outcomes.
- The Staff AI Engineer will be responsible for moving beyond manual propagation of insights to a system where the fleet gets smarter with every trade.
- This is a high-stakes production role, not a research position.
- The feedback loop is immediate and measurable: the work produced either enhances agent profitability or it does not.
- The successful candidate will own the intelligence layer that turns thousands of daily trading decisions into compounding, autonomous growth.
Benefits
- Approximately 1% initial stock grant, with significant valuation growth potential.
- Reinforcement/Online Learning: Deep understanding of the practical challenges of learning from real-world outcomes rather than static datasets.
Company info
- At MLabs, we are committed to offer equal opportunities to all candidates.
- We ensure no discrimination, accessible job adverts, and providing information in accessible formats.
- Our goal is to foster a diverse, inclusive workplace with equal opportunities for all.
- If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing human-resources@mlabs.city.
- MLabs Ltd collects and processes the personal information you provide such as your contact details, work history, resume, and other relevant data for recruitment purposes only.
- Your data may be shared only with clients and trusted partners where necessary for recruitment purposes.
- You may request the deletion of your data or withdraw your consent at any time by contacting legal@mlabs.city.
- Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates.
- Commitment to Equality and Accessibility: At MLabs, we are committed to offer equal opportunities to all candidates.
This listing is sourced directly from MLabs's careers page and normalized into a canonical job model.