Machine Learning Engineer

Role Overview

Akkodis is seeking a Senior Machine Learning Engineer (LLMs) for a contract role supporting a client in Santa Ana, CA (Remote). The role focuses on designing, coding, and deploying production-grade Large Language Model (LLM) systems—not prototypes—with strong emphasis on handwritten Python (no reliance on AI-generated code).

Responsibilities

• Design, build, and deploy LLM-powered systems for large-scale, real-world workloads
• Write production-quality Python from scratch for:
  • Data pipelines
  • Model training
  • Inference
  • Evaluation
• Build and maintain end-to-end ML pipelines (ingestion → training → validation → deployment)
• Fine-tune and adapt LLMs using:
  • Full fine-tuning
  • LoRA
  • Prompt engineering
  • DPO / preference-based optimization
• Optimize models for latency, throughput, memory, and cost
  • Quantization, compression, distillation
• Implement Retrieval-Augmented Generation (RAG) systems:
  • Vector databases
  • Embeddings
  • Semantic search and document chunking
• Create evaluation frameworks and continuous improvement feedback loops
• Apply MLOps best practices:
  • CI/CD for ML
  • Monitoring, logging, alerting
  • Highly available production systems

Must-Have Qualifications

• 5+ years of hands-on ML engineering experience in production environments
• Expert-level Python, able to design and implement systems without AI-generated code
• Proven experience deploying LLMs and NLP systems at scale
• Strong background in:
  • LLM fine-tuning/adaptation
  • Model optimization (quantization, compression, distillation)
  • RAG architectures and vector search
• Experience with modern ML/LLM frameworks such as LangChain or LlamaIndex
• Strong MLOps experience (CI/CD, automated evaluation, monitoring)
• Cloud ML experience (e.g., GCP or Databricks)

Nice-to-Haves

• Additional depth in latency/cost optimization and evaluation/monitoring automation
• Experience building feedback loops for continuous model improvement