> Markdown version of [/jobs/ext/1754058-manager-data-science-ai](https://www.wearedevelopers.com/jobs/ext/1754058-manager-data-science-ai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Manager, Data Science & AI - **Company:** XPO Logistics, Inc. - **Location:** Boston, MA, United States - **Experience:** Experienced - **Salary:** $131,100.0 - $163,875.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Computer Vision, Automated Storage and Retrieval Systems, Microsoft Azure, Code Review, Continuous Integration, Monitoring of Systems, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Software Engineering, Google Cloud, Enterprise Software Applications, Cloud Platform System, Pytorch, Large Language Models, Prompt Engineering, Generative AI, Containerization, AI Platforms, Kubernetes, Information Technology, Performance Monitor, Data Management, Machine Learning Operations, Docker - **Published:** July 17, 2026 - **Apply:** https://www.dice.com/job-detail/b62f9bbd-31a2-4192-b3f9-6cc3784a4d57 ## About the Role * Bachelor's degree or equivalent related work or military experience * 5+ years of experience in Machine Learning Engineering, Applied AI, or MLOps, including hands-on development of ML and Generative AI solutions * 3+ years of experience leading and developing high-performing technical teams * Strong technical foundation in end-to-end AI systems, such as: * Designing and implementing scalable MLOps pipelines (training, CI/CD, deployment, monitoring, governance) * Building production-grade ML inference services and APIs (batch and real-time) * Developing and deploying Generative AI solutions, including LLM-powered applications and RAG pipelines * Supporting Computer Vision or multimodal models in production environments Proficiency in Python and modern ML frameworks (e.g., PyTorch), with demonstrated experience taking AI solutions from prototype to enterprise-scale deployment Experience integrating AI systems with enterprise applications and data platforms Strong communication skills with the ability to influence engineering, product, and business stakeholders Preferred qualifications: * Master's degree or PhD in Computer Science, Engineering, Data Science, or related field * Experience building and scaling enterprise AI platforms providing best practices and/or acting as a Center of Excellence * Hands-on experience with: * LLM application development, prompt engineering, evaluation frameworks, and guardrails * Vector databases and retrieval systems * Model monitoring, drift detection, and AI governance practices Experience deploying AI solutions in cloud environments (AWS, Azure, Google Cloud Platform) Familiarity with containerization and orchestration (Docker, Kubernetes) Experience working across globally distributed teams Strong business acumen with experience driving measurable ROI from AI initiatives ## Description * Lead a team of ML engineers focused on building, deploying, and scaling production AI and Generative AI solutions that solve complex transportation and operational challenges * Partner with Data Science teams to transition models from experimentation into robust, scalable, and monitored production systems * Design and implement Generative AI applications, including: * RAG-enabled knowledge assistants * Internal copilots for operations, sales, and customer service * Multimodal AI solutions leveraging structured data, documents, and images Define and execute the company's MLOps strategy, including: * Standardizing CI/CD for ML * Establishing model lifecycle management and governance * Implementing observability, performance monitoring, and drift detection * Build reusable AI services, APIs, and shared frameworks that accelerate delivery across US and India AI teams * Drive Computer Vision enablement by ensuring scalable training, inference, and monitoring pipelines * Serve as a trusted advisor to senior stakeholders, helping translate Generative AI and ML capabilities into operational efficiency, cost reduction, and revenue growth * Conduct architecture reviews, code reviews, and performance tuning to ensure high engineering standards * Mentor engineers and data scientists on production-ready AI development and best practices * Stay at the forefront of advancements in ML Engineering, GenAI, and MLOps to guide technology decisions and enterprise adoption Annual Salary Range: $131,100 to $163,875 Actual compensation may vary due to factors such as experience and skill set. This is an incentive-based position, which may include bonuses, incentive or commission plans. ## Related Videos - [MLOps - What’s the deal behind it?](https://www.wearedevelopers.com/videos/392-mlops-what-s-the-deal-behind-it) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Microservices: how to get started with Spring Boot and Kubernetes](https://www.wearedevelopers.com/videos/242-microservices-how-to-get-started-with-spring-boot-and-kubernetes) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) ## Related Articles - [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) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [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) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)