Machine Learning Engineer

Akkodis

Santa Ana (CA)

Remote

USD 120,000 - 160,000

Full time

14 days+

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Benefits offered by this job

Medical insurance
Dental insurance
Vision insurance
401K plan
Paid Sick Leave

Job summary

A leading technology firm is seeking a Machine Learning Engineer in Santa Ana, CA (Remote) to design and deploy Large Language Model solutions at scale. The successful candidate will have 5+ years of ML engineering experience and expert-level skills in Python. Responsibilities include building ML systems, optimizing models, and utilizing cutting-edge frameworks. The role offers comprehensive benefits, including medical and 401K plans. If interested, apply now.

Qualifications

  • 5+ years of hands-on ML engineering experience in production environments.
  • Expert-level Python ability to design and implement systems without AI-generated code.
  • Proven experience deploying LLMs and NLP systems at scale.

Responsibilities

  • Design, build, and deploy LLM-powered systems handling large-scale workloads.
  • Write production-quality Python code for data pipelines and model training.
  • Optimize models for latency, throughput, memory, and cost.

Skills

Machine learning engineering
Production-quality Python
LLM fine-tuning
RAG architectures
MLOps
Cloud ML

Tools

LangChain
LlamaIndex

Job description

Overview

Akkodis is seeking a Machine Learning Engineer for a contract role located in Santa Ana, CA (Remote). This role focuses on building and deploying Large Language Model (LLM) solutions at production scale, designing, coding, and shipping real systems with production‑quality Python code. You will work across the full ML lifecycle delivering high‑throughput, low‑latency AI systems used at scale.

What You’ll Be Doing
  • Design, build, and deploy LLM‑powered systems handling large‑scale, real‑world workloads
  • Write production‑quality Python code from scratch for data pipelines, model training, inference, and evaluation
  • Fine‑tune and adapt LLMs using:
    • LoRA
    • DPO / preference‑based optimization
  • Optimize models for latency, throughput, memory, and cost
  • Quantization, compression, distillation
  • Design and implement Retrieval‑Augmented Generation (RAG) systems:
    • Embeddings
    • Semantic search and document chunking
  • Build evaluation frameworks, feedback loops, and continuous improvement pipelines
  • 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 — ability to design and implement systems without AI‑generated code
  • Proven experience deploying LLMs and NLP systems at scale
  • Strong background in:
    • LLM fine‑tuning and adaptation techniques
    • RAG architectures and vector search
  • Experience with modern ML/LLM frameworks (e.g., LangChain, LlamaIndex)
  • Solid MLOps experience (CI/CD, automated evaluation, monitoring)
  • Cloud ML experience (e.g., GCP, Databricks, or similar)

If you are interested in this Machine Learning Engineer position in Santa Ana, CA, please click APPLY NOW.

Equal Opportunity Employer/Veterans/Disabled

Military connected talent encouraged to apply

Benefits and Privacy

Benefit offerings include medical, dental, vision, life insurance, short‑term disability, additional voluntary benefits, EAP program, commuter benefits, and a 401K plan. Paid leave policies may include Paid Sick Leave and other paid leave required by law, along with Holiday pay where applicable. For details about how we use your information, read our Candidate Privacy Information Statement at the following link: https://www.modis.com/en-us/candidate-privacy/

Legal Notices

The Company will consider qualified applicants with arrest and conviction records in accordance with federal, state, and local laws and/or security clearance requirements, including, as applicable:

  • The California Fair Chance Act
  • Los Angeles City Fair Chance Ordinance
  • Los Angeles County Fair Chance Ordinance for Employers
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