Staff/Senior AI/ML Engineer - (Dublin, CA)
- Design, develop, and deploy AI/ML models ranging from traditional ML regression algorithms to transformer-based architectures.
- Train, fine-tune, and optimize deep learning and LLM-based solutions.
- Engage with customers to understand their needs and transform them into actionable tasks for developing new functionalities within the Articul8 platform.
- Collaborate with researchers, software engineers, and product teams to integrate new AI capabilities into our applications.
- Implement and evaluate state-of-the-art automated testing and metrics to improve model accuracy and efficiency.
- Optimize models for both cloud and on-premises environments to ensure low latency and high availability.
- Develop APIs and micro-services to serve AI models in production.
- Stay current with the latest AI models, research, and best practices.
- Ensure ethical AI practices, data privacy, and security compliance.
- Practice humility – Listen first, respect all voices, and recognize that great solutions are built together.
- Bias for outcomes – Focus on impact, not just effort; deliver meaningful results that matter to our customers.
- Care deeply – Invest in relationships, act with empathy, and put customer and teammate success at the center.
- Dare to do the impossible & embrace scarcity – Push boundaries with creativity and resourcefulness, even when constraints are real.
- Build a better world – Use our technology and platform to create solutions that benefit not just enterprises, but society at large.
- Master's or PhD in Computer Science, AI, Machine Learning, or equivalent engineering field.
- 8+ years of experience in AI/ML modeling development and deployment for the Senior role, 10+ years for the Staff role.
- Expert-level programming skills in Python and ML frameworks like PyTorch.
- Experience with LLMs, NLP, computer vision, or reinforcement learning.
- Experience with ML modeling for multi-dimensional, large time-series datasets.
- Strong proficiency in containerization technologies including Docker and Kubernetes.
- Proficiency in data preprocessing and model evaluation techniques, as well as MLOps tools like MLflow and Kubeflow.
- 3+ years of experience with distributed computing frameworks (Spark, Ray, Dask).
- Experience deploying AI models on major cloud providers (AWS, GCP, or Azure).
- Excellent communication and teamwork skills.
- Experience as a technical lead, guiding junior engineers and data scientists throughout product lifecycles, from proof of concept to model deployment.
- Experience in multi-cloud AI deployments.
- Experience working on AI SaaS platforms.
- Problem Solving: Ability to break down complex problems into manageable components, devise creative solutions, and refine ideas based on feedback and evidence.
- Collaboration and Communication: Skill in working cross-functionally—communicating clearly, offering constructive feedback, delegating responsibilities, and respecting diverse perspectives.
- Project Management and Prioritization: Demonstrated ability to juggle multiple projects, meet deadlines, and efficiently balance short-term objectives with long-term goals.
- Critical Thinking: Capacity to evaluate assumptions, question methodologies, challenge personal biases, and maintain healthy skepticism when interpreting results.
- Curiosity and Continuous Learning: Drive to stay informed about advances in related fields and actively seek opportunities to expand knowledge.
- Emotional Intelligence and Intellectual Humility: Demonstration of empathy, resilience, adaptability, and self-awareness. Willingness to recognize limitations, embrace uncertainty, acknowledge mistakes, and value others' contributions.
- A culture of curiosity and innovation, where your ideas shape enterprise AI adoption.
- Opportunities for continuous learning and growth, including mentoring, knowledge sharing, and thought leadership.
- The chance to work with leading global enterprises on cutting-edge Generative AI projects.
- A collaborative team that values diversity, inclusion, and creativity, supporting both personal and professional development.
- Equity and ownership opportunities in a category-defining company.
- The opportunity to directly influence reference architectures, product roadmap, and the future of enterprise AI adoption.
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