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Lead the design and implementation of simulation-based validation for autonomous systems, mentoring engineers and ensuring robust testing methodologies.
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Machine LearningProgramming Languages Relevant To Simulation And TestingSimulation Platforms
Artificial Intelligence • Cloud • Sales • Security • Software • Cybersecurity • Data Privacy
As a Senior AI Engineer at SailPoint, you will design, develop, and deploy AI solutions, focusing on Generative AI and ML engineering, while collaborating with teams to innovate and enhance identity governance.
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AirflowAWSBedrockGoKafkaPythonSagemakerSnowflake
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Develop AI-powered applications and workflows on the ServiceNow platform, leveraging AIA Studio, AI capabilities, and collaborating across functions to improve GTM processes.
Top Skills:
Agentic AiAia StudioAWSAzureGCPJavaJavaScriptKnowledge GraphsPythonRag FrameworksServicenow
Join our team as an AI Engineer and take a central role in designing and deploying innovative AI solutions that drive our organization forward. You will work with cross-functional teams to build robust, scalable systems using advanced machine learning techniques and Python. We value individuals who communicate clearly and excel in a collaborative, fast-paced environment.
Key Responsibilities:
- Develop, implement, and optimize AI models and algorithms to address real-world business challenges.
- Collaborate with data scientists, engineers, and product managers to integrate AI capabilities into products and services.
- Write clean, efficient, and well-documented Python code for machine learning pipelines and data processing tasks.
- Continuously evaluate model performance and iterate to improve accuracy and efficiency.
- Stay updated on emerging AI technologies, tools, and best practices, and share knowledge with the team.
- Contribute to technical documentation, code reviews, and team discussions.
- Communicate complex technical concepts clearly and effectively to both technical and non-technical stakeholders.
Qualifications:
- Proficient in Python with hands-on experience in building and deploying machine learning models.
- Solid understanding of core machine learning concepts, algorithms, and data structures.
- Strong written and verbal communication skills to facilitate collaboration and knowledge sharing.
- Ability to work independently in a remote environment and manage multiple priorities effectively.
- Experience with data preprocessing, feature engineering, and evaluation metrics.
- Familiarity with machine learning libraries such as TensorFlow, PyTorch, or scikit-learn.
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Preferred Qualifications:
- Experience with deploying AI models into production environments using cloud platforms.
- Background in natural language processing, computer vision, or deep learning.
- Contributions to open-source AI communities or research publications.
About RYZ Labs:
RYZ Labs is a startup studio built in 2021 by two lifelong entrepreneurs. The founders of RYZ have worked at some of the world's largest tech companies and some of the most iconic consumer brands. They have lived and worked in Argentina for many years and have decades of experience in Latam. What brought them together is the passion for the early phases of company creation and the idea of attracting the brightest talents in order to build industry-defining companies in a post-pandemic world.
Our teams are remote and distributed throughout the US and Latam. They use the latest cutting-edge technologies in cloud computing to create applications that are scalable and resilient. We aim to provide diverse product solutions for different industries, planning to build a large number of startups in the upcoming years.
At RYZ, you will find yourself working with autonomy and efficiency, owning every step of your development. We provide an environment of opportunities, learning, growth, expansion, and challenging projects. You will deepen your experience while sharing and learning from a team of great professionals and specialists.
Our values and what to expect:
- Customer First Mentality - every decision we make should be made through the lens of the customer.
- Bias for Action - urgency is critical, expect that the timeline to get something done is accelerated.
- Ownership - step up if you see an opportunity to help, even if not your core responsibility.
- Humility and Respect - be willing to learn, be vulnerable, and treat everyone who interacts with RYZ with respect.
- Frugality - being frugal and cost-conscious helps us do more with less
- Deliver Impact - get things done in the most efficient way.
- Raise our Standards - always be looking to improve our processes, our team, and our expectations. The status quo is not good enough and never should be.
What you need to know about the Chicago Tech Scene
With vibrant neighborhoods, great food and more affordable housing than either coast, Chicago might be the most liveable major tech hub. It is the birthplace of modern commodities and futures trading, a national hub for logistics and commerce, and home to the American Medical Association and the American Bar Association. This diverse blend of industry influences has helped Chicago emerge as a major player in verticals like fintech, biotechnology, legal tech, e-commerce and logistics technology. It’s also a major hiring center for tech companies on both coasts.
Key Facts About Chicago Tech
- Number of Tech Workers: 245,800; 5.2% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: McDonald’s, John Deere, Boeing, Morningstar
- Key Industries: Artificial intelligence, biotechnology, fintech, software, logistics technology
- Funding Landscape: $2.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Pritzker Group Venture Capital, Arch Venture Partners, MATH Venture Partners, Jump Capital, Hyde Park Venture Partners
- Research Centers and Universities: Northwestern University, University of Chicago, University of Illinois Urbana-Champaign, Illinois Institute of Technology, Argonne National Laboratory, Fermi National Accelerator Laboratory
