What you'll need to succeed as a Manager, Data Science & AI at XPOMinimum qualifications:
- 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, GCP)
- Familiarity with containerization and orchestration (Docker, Kubernetes)
- Experience working across globally distributed teams
- Strong business acumen with experience driving measurable ROI from AI initiatives
About the Manager, Data Science & AI jobPay, benefits and more:
- Competitive compensation package
- Full health insurance benefits are available on day one
- Life and disability insurance
- Earn up to 15 days of PTO over your first year
- 9 paid company holidays
- 401(k) option with company match
- Education assistance
- Opportunity to participate in a company incentive plan
What you'll do on a typical day:
- 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.
