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Machine Learning Engineer: 23rd September 2025

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Published 23rd September 2025

🔧 Company Engineering Blogs

Defending 20 Trillion Transactions: How Hyperforce’s Trusted Perimeter Stops DDoS Attacks with AI (engineering​.salesforce​.com). Explains Trusted Perimeter for Hyperforce: TLS termination, CDN caching, DDoS protection, AI-driven threat detection, and 10-minute global rollback

Viaduct, Five Years On: Modernizing the Data-Oriented Service Mesh (medium​.com/airbnb-engineering). Viaduct Modern overhauls engine and API, open-sources OSS at Airbnb, introducing tenant modules, resolvers, and dual APIs

🛠️ Applied ML Case Studies & Niche Models

Ranking the Perceived Safety of Streets (saadiqm​.com). Crowd-sourced street-view comparisons, Place Pulse 2.0, RankNet, DINOv3 embeddings, and a NA cities filter to rank perceived street safety

The Deceptively Complex World of Turkish Diacritics: A Neural Network Journey (ergoso​.me). Turkish diacritics restoration with a small neural model: BiLSTM, attention, masking, balanced loss, 6-letter scope, and GPU scaling

Building a Grocery Classification Model (dgendill​.com). Building a grocery classification model using 1–3-gram vocabularies, labeled data, and a RandomForest/OneVsRest multi-label classifier

🏈 Revamping Win Probability for 2025 (blog​.collegefootballdata​.com). New Python/XGBoost win-probability models with regulation, clutch, and overtime blending plus a Win Probability Calculator

Random Mutation Hill Climbing (RMHC) (4rknova​.com). Evolving images with Random Mutation Hill Climbing (RMHC) in the browser using Canvas 2D, MSE fitness, and shape-based DNA

What I Learned Building Synthetic Genomic Data: When Statistical Models Hit Their Limits (ksred​.com). ML-enhanced synthetic cfDNA data yields 92% fetal accuracy; statistical models plateau at ~77% due to fragment interdependencies

⚙️ ML Systems & Inference Engineering

Migrating to Nvidia Triton: High-Throughput, Low-Cost Inference at Scale (medium​.com/gumgum-tech). Migrating to Nvidia Triton for high-throughput, cost-efficient NLP inference with Python backends, dynamic batching, and GPU utilization tuning

Qwen-8B Embeddings: Near-SOTA Performance at 600x the Speed (alexdong​.com). Qwen-8B embeddings enable near-SOTA text classification, 600x faster than LLM classifiers, achieving MAP ~0.944 on Kaggle with simple MLP

Running SOTA AI-based Weather Forecasting models on AMD Instinct (rocm​.blogs​.amd​.com). Step-by-step guide to running SOTA AI weather forecasting models on AMD Instinct MI300X using JAX, PyTorch, Docker images, ai-models, and ECMWF data

Paths to Support Additional Numeric Types on the Java Platform #JVMLS (inside​.java). JVMLS discusses enabling full support for new numeric types in Java, including 16-bit floats and 8-bit formats for ML, with trade-offs across paths

Anthropic: A postmortem of three recent issues (simonwillison​.net). Anthropic explains three concurrent infrastructure bugs across AWS Trainium, NVIDIA GPUs, and Google TPUs that degraded Claude’s responses, plus privacy constraints hindering investigation

Announcing AWS Neuron SDK 2.26.0 (aws​.amazon​.com). GA of Neuron SDK 2.26.0 brings PyTorch 2.8, JAX 0.6.2, FLUX.1-dev image generation, and MoE expert parallelism on Trainium2

How do vector databases work? (hclimente​.github​.io). Vector embeddings, cosine similarity, UMAP visualizations, and HNSW-based vector databases (Qdrant) for RAG with LLMs

🚀 Training Paradigms, Efficiency, and Model Behavior

What gpt-oss Leaks (fi-le​.net). Analysis of GPT-oss; GPT-5 training data leakage, glitch tokens, tokenizers, embeddings, and membership inference across OpenAI models

The Shift to Reinforcement Learning Greatly Reduces Learning-Efficiency (tobyord​.com). RL training learns far less per hour than pre-training, impacting scalability, generality, and frontier task efficiency in AI systems

The Extreme Inefficiency of RL for Frontier Models (tobyord​.com). New scaling paradigm: RL’s information efficiency vs pre-training; long-horizon tasks, token-entropy, METR/HCAST, o1/o3/o3 models, latency and inference costs

Surprising GPT-OSS 20B 2-bit Quantization Performance (alexdong​.com). Benchmarking GPT-OSS 20B 2-bit, 5-bit quantization (GGUF), and long-context effects on RTX 3000 with MAP@3 insights

This paper changed my life: Dan Goodman on a paper that reignited the field of spiking neural networks (thetransmitter​.org). Friedemann Zenke’s 2019 paper on surrogate gradients enables modern ML with spiking neural networks and SpyTorch tutorials

Giving Foundation Models a Notion of Now (building​.nubank​.com). Explores encoding transaction timestamps as time deltas to improve transformer model performance and generalization with time-delta tokens and bucketed granularity

🧪 Classic ML, Explainability, and Statistical Modeling

Detecting and Fixing Data Quality Problems in Data Pipelines and ML Systems (wasi0013​.com). Detects, validates, and remediates data quality issues in web-scraped pipelines using Python, Pandas, and Imputation techniques

2025-09-17: Classic Machine Learning Models and XAI Methods (ws-dl​.blogspot​.com). Overview of classic ML models (Naive Bayes, Random Forest, SVM) and model-agnostic XAI methods (SHAP, LIME, permutation importance) with logistic regression discussion

Key improvements in shapviz and kernelshap (lorentzen​.ch). Shapviz and kernelshap updates with GLM and XGBoost SHAP explanations and interactions

Generating Synthetic Data with R-vine Copulas using esgtoolkit in R (thierrymoudiki​.github​.io). Tutorial on generating synthetic data with R-vine copulas using esgtoolkit in R and RVineModel fitting

Graph Regularization (blog​.devgenius​.io). Graph regularization in semi-supervised learning using Laplacian, manifold regularization, NSL, and Planetoid with TensorFlow

🌊 Scientific ML for Physics & Simulation

Introducing P3D: The three-dimensional PDE-Transformer (ge​.in​.tum​.de). P3D: a scalable 3D PDE-Transformer for high-resolution physics surrogates and diffusion-ready probabilistic 3D turbulence modeling

Discovering new solutions to century-old problems in fluid dynamics (deepmind​.google). New AI-assisted method using Physics-Informed Neural Networks to discover unstable singularities in IPM and Boussinesq fluid equations

New AI Technique Unravels Quantum Atomic Vibrations in Materials (caltech​.edu). Caltech AI method speeds up phonon interaction calculations for thermal transport by compressing high-order tensors via CANDECOMP/PARAFAC decomposition

Autodesk Research Brings Warp Speed to Computational Fluid Dynamics on NVIDIA GH200 (developer​.nvidia​.com). Autodesk Research leverages NVIDIA Warp and GH200 to speed Python-based CFD with XLB, achieving ~8x speedup and scaling to 50B cells

New approach improves accuracy of quantum chemistry simulations using machine learning (phys​.org). Machine learning inverts many-body results to learn a universal exchange-correlation functional for DFT accuracy

📐 Math Foundations for ML: Linear Algebra, Sampling, and Structure

Think Linear Algebra (allendowney​.com). Think Linear Algebra explores code-first approaches to linear algebra, with chapters on PageRank, 2D graphics transforms, LU decomposition, null space, and truss analysis

Global epistasis emerges from a generic model of a complex trait (or: random walks on a hypercube with reweighting) (quomodocumque​.wordpress​.com). A simple model of evolution using 2^n genotypes on a hypercube with fitness polynomial and reweighting dynamics

Polynomial Bounds for Chowla’s Cosine Problem (gilkalai​.wordpress​.com). Polynomial bounds for Chowla’s cosine problem via spectral graph theory and Hadamard products

Rayleigh quotient (aarnphm​.xyz). Rayleigh quotient for Hermitian matrices, eigenvalue bounds, eigenvectors, and Lagrangian formulation with extensions to covariance, generalized and two-sided forms

Latent trees (languagelog​.ldc​.upenn​.edu). Syntactic structure in LMs, historical statistical approaches, Harris/Firth, word segmentation, latent trees, and critiques by Futrell, Liu, and Beguš

I Misunderstood Rejection Sampling All This Time (buttondown​.com/jaffray). Rejection sampling expanded beyond disks: image distributions, volume sampling, grid subdivision, and efficiency improvements

📚 Academic Research

APFEx: Adaptive Pareto Front Explorer for Intersectional Fairness (arxiv:cs). Adaptive Pareto Front Explorer (APFEx) optimizes intersectional fairness across sensitive attribute combinations with differentiable metrics and Pareto-aware gradient strategies

Personalized Federated Learning with Heat-Kernel Enhanced Tensorized Multi-View Clustering (arxiv:cs). Personalized federated learning using heat-kernel enhanced tensorized multi-view fuzzy c-means with Tucker/CP decompositions and DP-enabled global aggregation

Green Recommender Systems: Understanding and Minimizing the Carbon Footprint of AI-Powered Personalization (arxiv:cs). Recommender systems eco-footprint: comparing traditional models and deep learning, measuring energy use and CO2 via hardware meters

Benefits of Online Tilted Empirical Risk Minimization: A Case Study of Outlier Detection and Robust Regression (arxiv:stat). Online Tilted Empirical Risk Minimization (TERM) for streaming data; balances accuracy, fairness, and robustness via a per-sample tilt parameter t

Cost-Performance Analysis: A Comparative Study of CPU-Based Serverless and GPU-Based Training Architectures (arxiv:cs). Comparative cost-performance analysis of SPIRT, ScatterReduce, AllReduce, and MLLess for serverless and GPU-based ML training with RedisAI

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