Expedite Technology Solutions LLC
Job Overview
Level 9 Machine Learning Engineer role focused on designing and implementing scalable MLOps data pipelines. Onsite work in Scottsdale, AZ for 3 days with a required credit check. US citizenship is not required but green card and H-1B holders are acceptable. Responsibilities
Design and implement scalable MLOps pipelines for data ingestion, processing, and storage. Deploy models using Vertex Pipelines, Kubeflow, or similar MLOps platforms. Implement end-to-end machine learning workflows and patterns. Write high-quality Python code with data science and ML packages. Containerize models with Docker and orchestrate with Kubernetes and CI/CD practices. Build AI/ML products using LLMs, neural networks, Flask or FastAPI, and RAG/Supervised Tuning techniques. Develop and maintain large-scale machine learning frameworks such as TensorFlow, PyTorch, and Spark ML. Apply expertise in Gen AI advancements including Gemini, OpenAI, Claude, and open-source LLMs. Provide strong distributed systems design and knowledge. Leverage at least one public cloud provider, preferably GCP. Qualifications
Expert-level programming skills in Python. Extensive experience with data science and machine learning frameworks. Proficiency in Docker, Kubernetes, and CI/CD pipelines. Hands‑on experience building and deploying ML models at scale. Strong analytical, written, and verbal communication skills. Experience with LLMs, LangChain, vector databases, and GCP Vertex AI tools. Tech Stack
Python, SQL, Docker, Kubernetes, FastAPI, Flask, MLOps, ML, LLMs, LangChain, Vector DB, GCP, Vertex AI, AutoML. Location
18700 North Hayden Road, Scottsdale, AZ or Client Dallas. Onsite role, 3 days onsite. Employment Information
Full-time, Mid-Senior level, Engineering and Information Technology function. Green card and H‑1B holders acceptable.
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Level 9 Machine Learning Engineer role focused on designing and implementing scalable MLOps data pipelines. Onsite work in Scottsdale, AZ for 3 days with a required credit check. US citizenship is not required but green card and H-1B holders are acceptable. Responsibilities
Design and implement scalable MLOps pipelines for data ingestion, processing, and storage. Deploy models using Vertex Pipelines, Kubeflow, or similar MLOps platforms. Implement end-to-end machine learning workflows and patterns. Write high-quality Python code with data science and ML packages. Containerize models with Docker and orchestrate with Kubernetes and CI/CD practices. Build AI/ML products using LLMs, neural networks, Flask or FastAPI, and RAG/Supervised Tuning techniques. Develop and maintain large-scale machine learning frameworks such as TensorFlow, PyTorch, and Spark ML. Apply expertise in Gen AI advancements including Gemini, OpenAI, Claude, and open-source LLMs. Provide strong distributed systems design and knowledge. Leverage at least one public cloud provider, preferably GCP. Qualifications
Expert-level programming skills in Python. Extensive experience with data science and machine learning frameworks. Proficiency in Docker, Kubernetes, and CI/CD pipelines. Hands‑on experience building and deploying ML models at scale. Strong analytical, written, and verbal communication skills. Experience with LLMs, LangChain, vector databases, and GCP Vertex AI tools. Tech Stack
Python, SQL, Docker, Kubernetes, FastAPI, Flask, MLOps, ML, LLMs, LangChain, Vector DB, GCP, Vertex AI, AutoML. Location
18700 North Hayden Road, Scottsdale, AZ or Client Dallas. Onsite role, 3 days onsite. Employment Information
Full-time, Mid-Senior level, Engineering and Information Technology function. Green card and H‑1B holders acceptable.
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