Machine Learning Research Engineer (AI/ML)

Location: New York, United States

Salary: $200,000–$300,000 annual base salary, plus eligible discretionary bonus

Company

hirify.global is a quantitative trading firm developing electronic trading infrastructure, machine learning systems, market access, data, compute, research infrastructure, and risk management services.

What you will do

• Act as the primary feedback loop for the central machine learning platform by running complex models through training and inference pipelines.
• Benchmark and validate distributed machine learning infrastructure across software and hardware layers, identifying bottlenecks before broader rollout.
• Build abstractions and integrate machine learning tools with simulation and data frameworks to accelerate research prototyping.
• Enable rapid iteration on real-world data and distributed training with Ray.
• Use AI agents and automated research workflows to generate experiments, stress-test distributed clusters, and identify infrastructure improvements.
• Document system capabilities and hardware performance, sharing findings with engineering and research teams.

Requirements

• Deep proficiency in Python and software design principles.
• Experience building scalable APIs and abstractions for developers and researchers.
• Hands-on experience with modern machine learning frameworks such as PyTorch or TensorFlow.
• Practical experience training, evaluating, and deploying models at scale.
• Experience scaling machine learning workloads across GPUs and multi-node clusters using Ray, Dask, or PyTorch Distributed.
• Ability to debug and optimize hardware and software bottlenecks, including memory limits, GPU utilization, and data pipeline latency.

Nice to have

• Experience in quantitative finance or complex algorithmic research environments.
• Familiarity with large-scale time-series data, simulation engines, or performance benchmarking.
• Experience bridging systems engineering and applied machine learning research.
• Familiarity with LLM tooling and agentic frameworks for coding, research, or testing automation.

Culture & Benefits

• Hybrid working opportunities in a collaborative workplace.
• Generous paid time off policies.
• Savings plans and financial wellness tools available in each region.
• Daily breakfast, lunch, and snacks, plus wellness experiences and reimbursement for selected wellness expenses.
• Company-sponsored sports teams, fitness events, volunteer opportunities, charitable giving, and social events.
• Workshops and continuous learning opportunities.