Quick Overview
Job Description
AI/ML Engineer
Long Term Contract
Remote
TaxTerm: C2C &W2
Summary Build, train, and deploy machine learning models with a focus on LLM fine-tuning and high-performance inference pipelines. You own models from experimentation through to reliable production serving.
Role Expectations
- Train, fine-tune, and evaluate models including LLMs via full fine-tuning, LoRA/PEFT, and instruction tuning.
- Build and optimize inference pipelines for latency, throughput, and cost (batching, quantization, caching).
- Design data pipelines and datasets for training and evaluation; ensure data quality and reproducibility.
- Implement rigorous offline and online evaluation, benchmarking, and regression testing for models.
- Partner with platform engineers to deploy models to production with monitoring and rollback.
- Stay current with model architectures and translate research into practical improvements.
Required Skills
5+ years in ML/AI engineering; proven track record shipping models to production.
Strong Python and deep learning with PyTorch; solid understanding of the Transformer architecture.
Hands-on LLM fine-tuning experience (LoRA/PEFT, quantization, or full fine-tuning).
Experience building inference/serving pipelines and measuring model performance.
Comfortable with experiment tracking, versioning, and MLOps fundamentals.
Value adds:
Distributed training experience (multi-GPU, DeepSpeed, FSDP).
Publications, competition results, or notable open-source ML work.
Experience with retrieval, embeddings, and evaluation frameworks.
Core Stack:
Python PyTorch Transformers LLM Fine-Tuning MLOps Prompt Engineering
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