• Lead the design and implementation of advanced AI/ML systems including large language models, computer vision transformers, and reinforcement learning solutions for industrial applications
• Develop and deploy production-grade deep learning pipelines using cloud platforms (AWS, GCP, Azure) with focus on scalability, reliability, and performance optimization
• Build innovative AI solutions leveraging transformer architectures, generative models, and Bayesian frameworks to solve complex business challenges in ocean exploration, robotics, and industrial automation
• Implement online reinforcement learning systems for resource optimization and intelligent decision-making in critical operational environments
• Lead cross-functional teams in developing foundation models and fine-tuning strategies using advanced techniques including curriculum learning, adversarial training, and multimodal approaches
• Establish and drive MLOps best practices including automated model training pipelines, continuous deployment, monitoring, and A/B testing frameworks using tools like Docker, Kubernetes, and AdaptDL
• Translate cutting-edge AI research papers into production-ready solutions while maintaining robust evaluation metrics and interpretability frameworks
• Provide technical leadership and mentorship to the AI/ML engineering team, guiding development in advanced concepts including manifold embeddings, graph neural networks, and causal inference methodologies
• Work with external partners (academic and commercial) to coordinate AI development efforts and integrate novel technologies
• Ensure AI systems comply with security, privacy regulations and implement responsible AI development practices
• Present complex AI implementations and research findings to technical and non-technical stakeholders through clear documentation and compelling presentations

A technical leader with proven expertise in architecting and deploying enterprise-scale AI systems. You combine deep theoretical understanding of neural networks with strong leadership and implementation skills. Experienced in setting technical direction, guiding development teams, and taking AI initiatives from research to production. You excel at defining architectural standards, making strategic technology decisions, and translating complex algorithms into business value. Comfortable leading teams through ambiguity while maintaining focus on practical, scalable solutions that drive business outcomes.

• Master's degree in computer science, AI/ML, or related field
• 5+ years of experience in AI/ML development with focus on deep learning and neural network architectures
• Expert-level proficiency in TensorFlow, PyTorch, PyTorch Lightning, and deep learning frameworks
• Demonstrated experience architecting and deploying large-scale AI systems in production environments
• Strong expertise in transformer architectures, LLMs, computer vision models, and reinforcement learning
• Advanced programming skills in Python and C++, with experience in CUDA/GPU programming
• Proven experience with MLOps practices, containerization (Docker/Kubernetes), and elastic workload management
• Deep understanding of the mathematics behind neural networks including optimization, embeddings, and statistical learning theory
• Experience with cloud platforms (AWS, GCP, Azure) for AI model deployment and scaling
• Track record of leading AI research initiatives and converting research papers to production code • Strong problem-solving skills with ability to work on complex, ambiguous problems
• Legal authorization to work in the United States
  

• PhD in Computer Science, Machine Learning, or related field
• Publications or significant contributions to AI/ML research conferences
• Experience with robotics, autonomous systems, or industrial automation applications
• Expertise in active inference, causal inference, and interpretability frameworks
• Knowledge of edge computing and embedded AI deployment
• Experience with government or defense contracts (NOAA, Sandia, Space Force)
• Competition wins (Kaggle, hackathons) or open-source AI contributions
• Teaching or mentoring experience in AI/ML topics
• Experience with multimodal AI systems and cross-modal learning
• Background in formal methods and verification of AI systems
• Certifications in cloud AI platforms or specialized AI frameworks
  

At Emerson, we prioritize a workplace where every employee is valued, respected, and empowered to grow. We foster an environment that encourages innovation, collaboration, and diverse perspectives—because we know that great ideas come from great teams. Our commitment to ongoing career development and growing an inclusive culture ensures you have the support to thrive. Whether through mentorship, training, or leadership opportunities, we invest in your success so you can make a lasting impact. We believe diverse teams, working together are key to driving growth and delivering business results.

We recognize the importance of employee wellbeing. We prioritize providing flexible, competitive benefits plans to meet you and your family’s physical, mental, financial, and social needs. We provide a variety of medical insurance plans, with dental and vision coverage, Employee Assistance Program, 401(k), tuition reimbursement, employee resource groups, recognition, and much more. Our culture offers flexible time off plans, including paid parental leave (maternal and paternal), vacation and holiday leave.

Our compensation philosophy is simple: we pay a competitive base salary, within the local market in which we operate, and reward performance during our annual merit review process. The salary range for this role is $100,500 - $145,000, annually, commensurate with the skills, talent, capabilities, and experience each candidate brings to a role.

This position will be open for a minimum of 7 days from the day of posting. Applicants are encouraged to apply early to receive optimal consideration. In compliance with the Colorado Job Application Fairness Act, in any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.

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