Applications Engineer
📌San Francisco, United States 🇺🇸
⏱︎ full-time
🧙♂️ mid-level
💰 235000
Alembic is pioneering a revolution in marketing, proving the true ROI of marketing activities. The Alembic Marketing Intelligence Platform applies sophisticated algorithms and AI models to finally solve this long-standing problem. When you join the Alembic team, you’ll help build the tools that provide unprecedented visibility into how marketing drives revenue, helping a growing list of Fortune 500 companies make more confident, data-driven decisions.
About The Role
We’re looking for a Machine Learning Applications Engineer with GPU, Python, and C++ expertise to help productionize cutting-edge causal AI models. You’ll work closely with ML scientists to turn experimental research code into optimized, scalable, and well-structured software that powers Alembic’s real-time analytics and inference systems.
This is a hands-on, performance-focused role where you’ll operate at the intersection of applied ML, systems engineering, and high-performance computing.
Key Responsibilities
- Translate early-stage ML research and prototypes into reliable, testable, and performant software components
- Use CUDA, Triton, and Numba to optimize GPU-accelerated workloads for inference and preprocessing
- Contribute to core libraries and performance-critical routines using modern C++ in hybrid Python/C++ environments Develop modular, reusable infrastructure that supports deployment of ML workloads at scale Collaborate with data scientists and engineers to optimize data structures, memory usage, and execution paths
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Build interfaces and APIs to integrate ML components into Alembic’s broader platform Implement logging, profiling, and observability tools to track performance and model behavior
- 4–7 years of software engineering experience, including substantial time in Python and C++
- Hands-on experience with GPU programming, including CUDA, Triton, Numba, or related frameworks Strong familiarity with the Python data stack (Pandas, NumPy, PyArrow) and low-level performance tuning Experience writing high-performance, memory-efficient code in C++
- Demonstrated ability to work cross-functionally with researchers, platform engineers, and product teams
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Comfort transforming research-grade ML code into maintainable, production-grade software
- Experience with hybrid Python/C++ or Python/CUDA extension development (e.g., Pybind11, Cython, custom ops)
- Familiarity with ML serving or inference tools (e.g., TorchServe, ONNX Runtime, Triton Inference Server)
- Exposure to structured data modeling, causal inference, or large-scale statistical computation
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Background in distributed systems or parallel processing is a plus
- A pivotal role building GPU-accelerated software at the heart of a real-world AI product
- Collaboration with an elite team of ML scientists, engineers, and product leaders
- The opportunity to shape performance-critical infrastructure powering enterprise decision-making
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A culture rooted in technical rigor, curiosity, and product impact
Senior Embedded Software Engineer
@ Embedd 
What we're looking for
At embedd.it, we power hardware-software integration in embedded devices. We turn fragmented semiconductor chip data into configurable digital twins, then deterministically generate code, tests, and documentation – making integration faster, cheaper, and resilient to supply chain shocks.
We’re looking for a true legend – someone with abstract thinking and deep expertise in low-level software development. You’ll build vendor-agnostic tooling for MCU and peripheral integration to solve hardware-software integration once and for all. We work at the intersection of embedded systems, code generation, compilers, and machine learning. It’s your chance to help redefine how low-level development is done.
Responsibilities
- Drive the architecture of the driver structures and system layout
- Define scalable patterns for cross-architectural integration across bare-metal, Zephyr, Linux, and other environments
- Deconstruct complex SoC device trees and translate hardware descriptions into structured internal models for automated reasoning
- Partner with the ML team to shape data and annotation models for AI-driven data-extraction tooling
Qualifications
- 5+ years of experience in embedded systems development, including bare-metal and RTOS-based systems
- Proficiency in C/C++
- Familiarity with firmware configuration, SoC bring-up, and system-level debugging
- Hands-on experience with code generation tools, or low-level compiler/decompiler/emulator technologies
- Strong background in embedded toolchains: compilers, linkers, debuggers, and build systems
- Python or scripting for automation and tooling is a plus
- Experience with functional-safety standards is a plus
Why embedd.it?
- Dynamic, venture-backed team of engineers challenging the status quo 🚀
- Work at the intersection of embedded systems, code generators, compilers, and ML 🤖
- Unusual challenges requiring out-of-the-box abstract thinking 🧠
- Competitive compensation: cash + equity 💰
- Remote work possible 🌍
About Us
embedd.it is a UK-based startup reinventing embedded development. Our platform transforms unstructured semiconductor data into structured digital twins, enabling automatic generation of drivers, tests, and documentation. We're building a single, traceable source of truth to make integration fast, vendor-agnostic, and future-proof.
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Employment
⏱︎ full-time
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Experience
🧙♂️ mid-level
-
Salary
💰 235000
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Skills
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Industry
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