Akkodis is seeking a Senior Machine Learning Engineer for a 6-month contract with a client in Chicago, IL 60606-Remote. Title: Senior Machine Learning Engineer Location: Chicago, IL 60606-Remote Contract: 6-month contract with extension Pay Rate: $110-$115/hr (The rate may be negotiable based on experience, education, geographic location, and other factors.) The Opportunity Senior Machine Learning Engineer contractor to build algorithmic assets across Personalization, Generative AI, Forecasting, and Decision Science domains. This role combines deep technical modeling expertise with infrastructure engineering to design, build, and operate end-to-end ML/AI systems at scale. You'll implement foundational MLOps frameworks across the full product lifecycle, including data ingestion, ML processing, and results delivery/activation. Working cross-functionally with data science, data engineering, and architecture teams, you'll serve as both solutions architect and hands-on implementation engineer. Roles and Responsibilities: Model Development & Optimization • Design and optimize machine learning models, including deep learning architectures, LLMs, and specialized models (BERT-based classifiers) • Implement distributed training workflows using PyTorch and other frameworks • Fine-tune large language models and optimize inference performance using compilation tools (Neuron compiler, ONNX, vLLM) • Optimize models for hardware targets (GPU, TPU, AWS Inferentia/Trainium) Infrastructure Design & AI-Services Architecture • Design AI services and architectures for real-time streaming and offline batch optimization use cases • Lead ML infrastructure implementation, including data ingestion pipelines, feature processing, model training, and serving environments • Build scalable inference systems for real-time and batch predictions • Deploy models across compute environments (EC2, EKS, SageMaker, specialized inference chips) MLOps Platform & Pipeline Automation • Implement and maintain MLOps platform, including Feature Store, ML Observability, ML Governance, Training, and Deployment pipelines • Create automated workflows for model training, evaluation, and deployment using infrastructure-as-code • Build MLOps tooling that abstracts complex engineering tasks for data science teams • Implement CI/CD pipelines for model artifacts and infrastructure components Performance & Cross-functional Partnership • Monitor and optimize ML systems for performance, accuracy, latency, and cost • Conduct performance profiling and implement observability solutions across the ML stack • Partner with data engineering to ensure optimal data delivery format/cadence • Collaborate with data architecture, governance, and security teams to meet required standards • Provide technical guidance on modeling techniques and infrastructure best practices Required Experience: • Master's degree in Computer Science, Software Engineering, Machine Learning, or related fields • 5+ years implementing AI solutions in cloud environments with a focus on AI services and MLOps • 3+ years of hands-on experience with ML model development and production infrastructure • Proven track record delivering production ML systems in enterprise environments Additional Requirements: • Agile Methodology experience • End-to-end ML systems experience from research to production • Strong communication and collaboration skills • Ability to work independently with minimal supervision • Enterprise security and compliance experience Preferred: • Recommendation systems, NLP applications, or real-time inference systems experience • MLOps platform development and feature store implementations Equal Opportunity Employer/Veterans/Disabled Benefit offerings available for our associates include medical, dental, vision, life insurance, short-term disability, additional voluntary benefits, an 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. Disclaimer: These benefit offerings do not apply to client-recruited jobs and jobs that are direct hires to a client. To read our Candidate Privacy Information Statement, which explains how we will use your information, please visit https://www.akkodis.com/en/privacy-policy. 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