Evolution Cloud Services
Technology
SeniorMachineLearningEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Machine Learning Engineer at Evolution Cloud Services. Skills: Machine Learning Engineering, Transformer models, Distributed training, Model deployment. Train AI models. Build training pipelines”
Industry & Context.
Find problems; Fix problems
What They're Looking For.
Must Have
5+ years ML engineering experience, Meaningful time fine-tuning transformer models, Python and PyTorch fluency, Hugging Face stack fluency, Git, Docker, Fluent in English
Nice to Have
Read a CUDA kernel, Built distributed training setup, Azure AI Foundry experience, Dbt experience, Airflow experience, Dagster experience, Spark experience, W&B experience, MLflow experience, Spreadsheet experiment tracking, Bilingual or near-native English, Run quantized models locally, Familiarity with whisper.cpp, Familiarity with flash-moe, Take on MoE routing, Take on speculative decoding, Take on KV-cache management, RLHF experience, DPO experience, Preference data curation experience
What You'll Do.
Build training pipelines
Maintain training pipelines
Build retraining pipelines
Maintain retraining pipelines
Manage fine-tuning workflows
Manage drift monitoring
Close the loop on production data
Make model design calls
Run hyperparameter work
Operate distributed training setups
Design eval harnesses
Ship models into production
How You'll Work.
Team & Collaboration
Client-facing role
Communication Scope
Interpersonal skills; Communication skills
Full Job Description
EVOCS OVERVIEW EVOCS’s journey began with a mission to empower businesses with advisory expertise, empowered with idealtechnologies to provide them with comprehensive solutions to grow and prosper. Founded by a team of passionate experts, EVOCS has grown into a trusted partner to a growing number of leaders across their respective industries. Our roots in employee-managed operations reflect our commitment to quality, consistency, and client success. If you enjoy working in a hyper-fast-growing company, are eager to be part of an agile team, and want to be part of our success story, then let’s talk! 🎯 Role Overview As a Senior Machine Learning Engineer, you will be the person we trust with the training side of our AI work. You’ll decide what to build, how to build it, and whether to build it at all. You will be responsible for the quality of the models we ship: the data they learn from, the pipelines that produce them, and the judgment calls that separate a useful model from an expensive one. You’ll be mentoring engineers who’ve never watched a loss curve diverge and felt something. 🧩 What you will do In this role, you will: Be the primary person responsible for the data piece of our AI initiatives. This could be called the unglamorous stuff that decides whether the model works, but this is your passion. You put the enthusiast in MLE. Build and maintain training and retraining pipelines in Azure AI Foundry. We’re talking working on the model catalog, fine-tuning workflows, deployment, drift monitoring, and closing the loop when production data reveals the eval set was lying to you. Make the real model design calls because you know best which way to go: full fine-tune vs. LoRA/QLoRA vs. DPO vs. “better prompting would save us three weeks.” Know when not to train. Run hyperparameter work that isn’t a grid search copied from a 2021 Medium post. Operate distributed training setups and know what breaks at scale. Pick your poison: FSDP, DeepSpeed, Megatron, accelerate, e
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