MLOps
Operacions d’aprenentatge automàtic
cfo-advisor
borghei
Financial leadership advisor for CFOs on financial planning, fundraising, investor reporting, unit economics, cash management, and financial operations.
marketing-analyst
borghei
Expert marketing analytics covering campaign analysis, attribution modeling, marketing mix modeling, ROI measurement, and performance reporting.
demand-gen-manager
borghei
Expert demand generation covering lead generation, campaign management, funnel optimization, marketing automation, and pipeline contribution.
agile-coach
borghei
Expert agile coaching covering team transformation, agile frameworks, coaching techniques, organizational change, and continuous improvement.
sales-operations
borghei
Expert sales operations covering CRM management, sales analytics, territory planning, compensation design, and process optimization.
cfo-advisor
borghei
Financial leadership advisor for CFOs on financial planning, fundraising, investor reporting, unit economics, cash management, and financial operations.
cmo-advisor
borghei
Marketing leadership advisor for CMOs on brand strategy, demand generation, marketing operations, growth marketing, and revenue marketing alignment.
coo-advisor
borghei
Operations leadership advisor for COOs on business operations, process optimization, scaling infrastructure, cross-functional alignment, and operational excellence.
senior-ml-engineer
borghei
Expert ML engineering covering model development, MLOps, feature engineering, model deployment, and production ML systems.
coo-advisor
borghei
Operations leadership advisor for COOs on business operations, process optimization, scaling infrastructure, cross-functional alignment, and operational excellence.
people-analytics
borghei
Expert people analytics covering workforce analytics, HR metrics, predictive modeling, employee insights, and data-driven HR decisions.
cmo-advisor
borghei
Marketing leadership advisor for CMOs on brand strategy, demand generation, marketing operations, growth marketing, and revenue marketing alignment.
product-strategist
borghei
Expert product strategy covering market analysis, competitive positioning, go-to-market planning, and product-led growth.
data-scientist
borghei
Expert data science covering machine learning, statistical modeling, experimentation, predictive analytics, and advanced analytics.
account-executive
borghei
Expert sales execution covering pipeline management, discovery, demos, negotiation, and deal closing.
ml-ops-engineer
borghei
Expert MLOps engineering covering model deployment, ML pipelines, model monitoring, feature stores, and infrastructure automation.
databricks-expert
personamanagmentlayer
Expert-level Databricks platform, Apache Spark, Delta Lake, MLflow, notebooks, and cluster management
eachlabs-fashion-ai
eachlabs
Generate fashion model imagery, virtual try-on, runway videos, and campaign visuals using EachLabs AI. Use when the user needs fashion content, model photography, or virtual try-on.
fine-tuning-serving-openpi
majiayu000
Fine-tune and serve Physical Intelligence OpenPI models (pi0, pi0-fast, pi0.5) using JAX or PyTorch backends for robot policy inference across ALOHA, DROID, and LIBERO environments. Use when adapting pi0 models to custom datasets, converting JAX checkpoints to PyTorch, running policy inference servers, or debugging norm stats and GPU memory issues.
hqq-quantization
majiayu000
Half-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast quantization workflows, or when deploying with vLLM or HuggingFace Transformers.
miles-rl-training
majiayu000
Provides guidance for enterprise-grade RL training using miles, a production-ready fork of slime. Use when training large MoE models with FP8/INT4, needing train-inference alignment, or requiring speculative RL for maximum throughput.
mamba-architecture
majiayu000
State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.
gptq
majiayu000
Post-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when you need 4× memory reduction with <2% perplexity degradation, or for faster inference (3-4× speedup) vs FP16. Integrates with transformers and PEFT for QLoRA fine-tuning.
verl-rl-training
majiayu000
Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.