Machine Learning Engineer

At Akkodis, we use our insight, knowledge, and global resources to make exceptional connections every day. With 60 branch offices located strategically throughout North America, we are positioned perfectly to deliver the industry's top talent to each of our clients. Clients choose Akkodis as their workforce partner to solve staffing challenges that range from locating hard-to-find niche talent to completing quick-fill demands. Akkodis is seeking a Machine Learning Engineer for a contract role with a client located in Santa Ana, CA (Remote) Pay Rate: $55-60/hr. (The rate may be negotiable based on experience, education, geographic location, and other factors). Location: Santa Ana, CA (Remote) Machine Learning Engineer (LLMs) We’re hiring a Senior Machine Learning Engineer with deep experience building and deploying Large Language Model (LLM) solutions at production scale. This role is for someone who can design, code, and ship real systems — not prototypes — and who is highly fluent in Python written from scratch (no reliance on AI‑generated code). You’ll 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 • 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 • Design and implement Retrieval‑Augmented Generation (RAG) systems: • Vector databases • Embeddings • Semantic search and document chunking • Build evaluation frameworks, feedback loops, and continuous improvement pipelines • Implement 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 — 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 • Model optimization (quantization, compression, distillation) • 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 in Santa Ana, CA then please click APPLY NOW. For other opportunities available at Akkodis go to www.akkodis.com. If you have questions about the position, please contact Priyanka Khurana at Priyanka.khurana@akkodisgroup.com Equal Opportunity Employer/Veterans/Disabled Military connected talent encouraged to apply Benefit offerings available for our associates include medical, dental, vision, life insurance, short-term disability, additional voluntary benefits, EAP program, commuter benefits and a 401K plan. Our benefit offerings provide employees the flexibility to choose the type of coverage that meets their individual needs. In addition, our associates may be eligible for paid leave including Paid Sick Leave or any other paid leave required by Federal, State, or local law, as well as Holiday pay where applicable. To read our Candidate Privacy Information Statement, which explains how we will use your information, please visit https://www.modis.com/en-us/candidate-privacy/ 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 • San Francisco Fair Chance Ordinance