About this role
ATTENTION MILITARY AFFILIATED JOB SEEKERS - Our organization works with partner companies to source qualified talent for their open roles. The following position is available to Veterans, Transitioning Military, National Guard and Reserve Members, Military Spouses, Wounded Warriors, and their Caregivers . If you have the required skill set, education requirements, and experience, please click the submit button and follow the next steps. Unless specifically stated otherwise, this role is "On-Site" at the location detailed in the job post. What you will do Let’s do this. Let’s change the world. In this vital role you will play a pivotal role in building and scaling our machine learning models from development to production. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines. A background in data engineering, including experience with data pipelines and distributed data processing, is a strong plus. Roles & Responsibilities: Lead the end-to-end design, development, and delivery of machine learning and Generative AI (GenAI) solutions, from problem framing to production deployment and business impact realization. Act as the technical owner for large-scale ML/GenAI initiatives, driving architecture decisions, scalability, reliability, and long-term maintainability. Design and implement advanced agentic AI systems, including multi-agent architectures, reasoning workflows, tool integration, and autonomous decision-making systems. Define and institutionalize evaluation, validation, and governance frameworks for ML/GenAI systems, including model performance, prompt evaluation, safety guardrails, hallucination mitigation, and compliance. Partner directly with business stakeholders and product leaders to understand objectives, translate them into AI/ML solutions, and ensure measurable value delivery. Establish and enforce best practices in MLOps, LLMOps, and DevOps, including CI/CD, monitoring, observability, reproducibility, and cost optimization. Architect and oversee scalable cloud-based ML/GenAI platforms leveraging AWS, GCP, or Azure. Drive experimentation strategy, including A/B testing, prompt optimization, and iterative improvement of models and agent workflows. Provide technical leadership and mentorship to L4 and L5 engineers, including design reviews, code reviews, and career guidance. Lead cross-functional collaboration across data science, engineering, product, and business teams to deliver integrated AI solutions. Stay at the forefront of advancements in machine learning, Generative AI, and agentic systems, and drive adoption of new technologies and approaches. Design, develop, and implement robust data architectures and platforms to support ML Operation. Ensuring data integrity, accuracy, and consistency through rigorous quality checks and monitoring.