Senior Machine Learning Engineer

Overview of the Role Our entertainment media client is seeking a Senior ML Architect to join their team. In this role, you will define and own the technical vision for a scalable, AWS based machine learning platform. This senior individual contributor role sets architectural direction across data ingestion, training pipelines, model serving, and ML observability. You will partner closely with ML Ops, Data Science, infrastructure, and data engineering teams to establish platform standards, diagnose gaps in the current ecosystem, and design a roadmap that supports robust experimentation and reliable production deployment. The Basics • Duration: 9 months • Hours: 40 hours per week • Location: Hybrid (flexible schedule) in Burbank, CA Top Three Required Qualifications 1. 8 to 12 plus years of experience in ML Engineering, ML Architecture, or ML Platform and Infrastructure roles. 1. Proven experience designing end to end ML platform architecture from the ground up in AWS. 1. Deep AWS expertise across ML relevant services, including SageMaker, ECS, Lambda, Step Functions, S3, IAM, RDS, and related data services. Other Qualifications • Strong Python proficiency and familiarity with production ML tooling such as MLflow, orchestration frameworks, and feature stores. • Experience with infrastructure as code frameworks such as Terraform or CloudFormation and containerization standards. • Ability to design systems that support the full ML lifecycle, including experimentation, training, deployment, and monitoring. • Proven ability to drive technical alignment and set architectural standards across multiple engineering and data teams without direct managerial authority. • Excellent communication skills with the ability to explain complex architectural trade offs to technical and non technical audiences. Key Responsibilities • Own the end to end ML platform architecture, including data ingestion, feature management, training pipelines, model serving, and observability. • Develop and maintain a phased ML architecture roadmap covering foundational data layers, orchestration, tooling, and production deployment. • Document architectural decisions, including design rationale, trade offs, and alignment across teams. • Ensure the platform scales with growing data volume, model count, and use case complexity. • Design the ML development platform, including environment management, dependency strategies, repository structure, and packaging conventions. • Define the CI and CD architecture supporting the ML lifecycle from experimentation through production. • Select and specify tools for Data Science workflows with clear ownership and usage guidance. • Establish architectural boundaries across experimentation, staging, and production environments. • Design the orchestration strategy and pipeline architecture for ML workflows, including tooling selection and pipeline structure. • Define end to end data flow from source systems through preprocessing, training, and inference, with structured intermediate storage patterns and data contracts. • Establish lineage, observability, and monitoring requirements for ML workflows. • Architect AWS native deployment patterns for batch and real time serving, including model promotion paths and infrastructure guidance. • Define feature store architecture and model registry standards to ensure traceable model lifecycle management. • Evaluate AWS and third party services against evolving ML platform needs. • Act as the senior technical authority on ML platform decisions across engineering, Data Science, infrastructure, and data teams. • Collaborate with the ML Ops Lead to ensure implementation aligns with architectural intent. • Work closely with Data Science to understand experimentation needs and reduce deployment friction. • Partner with data engineering to ensure strong integration with broader data ecosystem systems. • Communicate architectural decisions and updates clearly to stakeholders. In this position, you may have access to client or customer systems, confidential and/or proprietary information or data. This position is onsite and requires you to work closely with other individuals in a collaborative team environment. Benefits Creative Circle's Freelance Employee benefits package includes eligibility for Minimum Essential Coverage (MEC) medical plan, dental/vision/term life package, discount prescription program, critical illness, accident, tele-behavioral health, and 401(k) plan. Sick leave is provided to Candidates whose assignment work location is in a state or city subject to sick leave laws. A Minimum Value (MV) PPO medical plan, Employee Stock Purchase Plan, and paid holiday eligibility are based on length and dates of service. For Creative Circle to represent you for this opportunity, you must be currently authorized to work in the United States without the need of employer sponsorship for a non-immigrant visa such as a H-1B, TN, or O visa. We do not support or provide training for STEM/OPT programs. Additionally, you must be physically located in and perform the work for our client in the United States.