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Hiring via TechTree This is a role that TechTree is recruiting for on behalf of one of its clients. TechTree is an AI-driven recruitment platform working with high-growth companies. When you apply, TechTree's AI Agent matches you not just to this role , but to other relevant opportunities across its network, so one application can unlock multiple roles. Senior ML Engineer | Foundation Models & CUDA TechTree's client is hiring a Senior ML Engineer to help build and scale a novel foundation model for automated software delivery in embedded systems. This is a deeply technical role for an engineer who has built large-scale foundation models, developed custom CUDA kernels, and scaled distributed ML systems in production. Location: Brazil — remote Employment: Full-time Estimated compensation: £100,000–£150,000/year + equity Level: Mid-Senior / Senior Relocation: UK visa sponsorship may be available What You'll Own Lead development and production deployment of a large-scale foundation model Design and implement custom CUDA kernels for performance-critical workloads Optimise training and inference across GPUs and distributed infrastructure Architect scalable ML systems with demanding reliability and performance requirements Profile and improve data pipelines, training loops, inference, and serving infrastructure Evaluate modern architectures including Mixture-of-Experts and state-space models Build internal tooling, benchmarks, evaluation systems, and observability infrastructure Work closely with founders on technical strategy and optimisation priorities Improve model quality, latency, scalability, and compute efficiency What We're Looking For Deep professional experience with CUDA C/C++ Strong Python skills Experience building and shipping large-scale foundation models Proven custom CUDA kernel development Experience with distributed training and inference Strong knowledge of modern deep learning architectures Production expertise with PyTorch or another major ML framework Experience operating ML workloads on AWS, Azure, or GCP Strong understanding of ML observability, evaluation, and production SLOs Experience delivering complex systems in fast-moving environments Strong advantages Built a foundation model from 01 Early-stage AI startup or top-tier research lab experience Experience with MoE, state-space models, and advanced inference optimisation Built tooling that significantly improved engineering or research productivity Experience optimising large-scale GPU workloads for cost and performance Why consider this opportunity? Work on a genuinely novel foundation-model problem Significant technical ownership from day one Direct influence over architecture and ML strategy Work closely with an experienced founding team Competitive compensation plus equity Remote opportunity for candidates based in Brazil Potential UK relocation support If this sounds like a fit, we'd love to hear from you. Apply today!
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.