⚡ Senior ML Infrastructure Engineer
📍 Mountain View (3 days per week)
💲 $180k – $300k base + meaningful equity (level dependent)

I’m supporting our client, an AI-native wealth management platform, as they hire a senior individual contributor to build and scale the ML systems backbone powering trading and portfolio intelligence.

This is not a support function. Research Infrastructure sits at the core of the business. Machine learning systems directly power trading decisions, portfolio construction, and capital allocation.

You’ll design and scale the infrastructure that enables researchers to train models, run large-scale experiments, simulate strategies, and deploy production trading systems reliably and reproducibly.

If you’re interested in building ML platforms that actually move capital — not just publish benchmarks — this will be a strong fit.

Who This Role Is For

You’re a senior engineer who enjoys owning complex distributed systems end-to-end.

You think in terms of system design, performance trade-offs, failure modes, determinism, and correctness — not just scripts and notebooks.

You’ve built production-grade ML infrastructure before and understand the gap between research code and hardened systems operating in live environments.

What You’ll Do

Own the ML Systems Layer
Architect and evolve large-scale distributed training and evaluation pipelines.
Build reproducible experimentation frameworks including data versioning, experiment tracking, and model registries.
Design high-performance backtesting and simulation infrastructure for systematic strategies.
Enable seamless transitions from research prototypes to production trading systems.

Power AI-Driven Trading Infrastructure
Develop infrastructure for signal generation, portfolio optimization, and execution workflows.
Build low-latency and batch processing pipelines across market, fundamental, and alternative datasets.
Partner closely with research and trading teams to productionize alpha models.
Improve throughput, latency, and reliability across compute-intensive workloads.
Ensure correctness, determinism, and auditability across research and trading systems.

Scale and Harden the Platform
Optimize distributed compute across cloud-native environments.
Improve orchestration of large-scale ML workloads.
Drive observability, monitoring, and failure isolation.
Write production-quality, well-tested code with long-term maintainability in mind.
Raise the engineering bar across research systems.

What They’re Looking For

• 5+ years building production-grade distributed systems or ML infrastructure.
• Deep experience designing large-scale data processing or training pipelines.
• Strong Python skills and fluency in modern ML ecosystems.
• Experience operating high-compute workloads in cloud-native environments.
• Proven ability to translate ambiguous research requirements into scalable platforms.
• Comfort owning complex systems end-to-end.

Strong Plus

• Experience building ML platforms at AI-first or research-driven companies.
• Experience with systematic trading, quant research infrastructure, or portfolio optimization systems.
• Experience with distributed training frameworks and large-model workflows.
• Familiarity with high-performance computing or low-latency systems.
• A PhD in ML systems, distributed systems, optimization, computational finance, statistics, or applied mathematics is valued but not required.

Why Apply?

• You’ll work on infrastructure that directly underpins live trading systems and portfolio construction. This is an opportunity to own foundational ML systems at a company where research and engineering are core to the product.
• Compensation ranges from $110k–$300k base (level dependent), with equity forming a meaningful part of total compensation.

Interested in applying?
Please click Easy Apply or email me at ben.watts@storm2.com

⚡ Storm2 is a specialist FinTech recruitment firm with clients across Europe, APAC, and North America. To discuss open opportunities or career options, visit storm2.com and follow the Storm2 LinkedIn page for the latest roles and market intel.