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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Operations Engineer - **Company:** VEHO, LLC - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $175,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Computing, Information Engineering, Data Integration, Data Integrity, Data Warehousing, Python (Programming Language), Machine Learning, Open Source Technology, Azure Machine Learning, SQL Databases, Snowflake, Apache Flink, Machine Learning Operations, Data Pipelines, Amazon Redshift, Databricks - **Published:** July 15, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=54163520c7c8e41d ## About the Role * Bachelor's Degree plus at least 3 years of experience in machine learning engineering, or Master's Degree plus at least 2 years in machine learning engineering * This experience should include: * Developing and optimizing MLOps pipelines for speed, reliability, and observability. * Utilizing statistical modeling or machine learning techniques to solve business problems. * Strong proficiency in Python and SQL. * Hands-on experience with open-source languages and tooling for large-scale ML (e.g., Ray, Flink, Feast). * Working with Data Warehouses (e.g., Redshift, Databricks, Snowflake). * Utilizing cloud-based (AWS Preferred) data engineering and data science tools. * Experience building ML systems in Startups is a plus * Experience with DS/ML in Logistics/Supply Chain is a plus. ## Description As a Senior Machine Learning Operations Engineer you'll be embedded in a team of talented data scientists and software engineers to create sophisticated models that answer hard questions centered around improving our logistics network and user experiences. This role bridges between ML platform work and building on top of our platforms to create new models. You'll create the infrastructure and tooling necessary to deploy, monitor, and scale our machine learning models in production. In close collaboration with data scientists you'll own our production models, ensuring optimal performance and responding to production incidents. A great candidate: Is an expert in their craft, creating high quality ML infrastructure and delivering impactful machine learning models to our stakeholders. Works in close collaboration with the other Data Science team members and keeps the business value at the center of their work. Has a bias for action, balancing delivering impact in the short-term while building out the long term vision. Applies their ML / MLOPS knowledge to suggest new patterns, tools, approaches to improve the team's models What you'll do: * Build reliable, efficient, and scalable infrastructure for our AI/ML capabilities * Create robust data pipelines to feed analyses and models * Enable forecasting, network orchestration, and live pricing systems * Ensure data quality and data integrity through best practices in data integration * Build out robust feature stores, model orchestration tooling, experimentation tooling, model performance monitoring. * Create standards and templates for model development and deployment across all Data Science teams. ## Related Videos - [DevOps for Machine Learning](https://www.wearedevelopers.com/videos/179-devops-for-machine-learning) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) - [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops) ## Related Articles - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Why Upskilling And Reskilling is Important For Developers](https://www.wearedevelopers.com/magazine/428-why-upskilling-and-reskilling-is-important-for-developers)