Are you an AI expert who thrives on designing and implementing intelligent systems that solve real-world problems? Do you love working at the intersection of cutting-edge technology and business strategy, creating scalable AI architectures that drive innovation? If you're passionate about architecting AI-driven solutions and helping companies unlock the power of artificial intelligence, then our client has the perfect role for you. We're looking for an AI Architect (aka The AI Visionary) to lead the design and deployment of AI systems that transform products and drive business success. As an AI Architect at our client, you'll work closely with product managers, data scientists, and engineers to design scalable AI architectures that support machine learning, natural language processing (NLP), and other AI applications. Your expertise will guide the entire AI development lifecycle, from concept to deployment, ensuring that AI technologies are integrated effectively into products and solutions. Key Responsibilities:
AI System Design and Architecture: - Lead the design and implementation of end-to-end AI architectures that support machine learning models, deep learning algorithms, and other AI technologies. You'll ensure the architecture is scalable, secure, and optimized for performance.
Technology Evaluation and Selection: - Evaluate and select the right AI tools, frameworks, and platforms to meet the specific needs of each project. You'll recommend AI technologies such as TensorFlow, PyTorch, Keras, or cloud-based AI services, ensuring the tech stack aligns with business objectives.
Collaborate with Cross-Functional Teams: - Work closely with data scientists, machine learning engineers, and software developers to integrate AI models into products and services. You'll ensure seamless collaboration between teams to translate AI research into production-ready solutions.
Scalability and Performance Optimization: - Design AI systems that can scale efficiently to handle large datasets and increasing workloads. You'll optimize models and AI infrastructure to ensure high performance, low latency, and reliable deployment in production environments.
Data Pipeline and Integration: - Collaborate with data engineers to build robust data pipelines that support the training and deployment of machine learning models. You'll ensure that data collection, storage, and preprocessing systems are aligned with the needs of AI models.
AI Governance and Security: - Implement best practices for AI governance, including model explainability, fairness, and security. You'll ensure compliance with industry regulations and data privacy standards such as GDPR, HIPAA, or SOC2, while maintaining the integrity of AI systems.
Stay Current with AI Trends: - Keep up-to-date with the latest advancements in AI research, tools, and best practices. You'll experiment with cutting-edge technologies like transformers, reinforcement learning, and self-supervised learning to ensure your AI architecture is future-proof.
RequirementsRequired Skills:
- AI and Machine Learning Expertise: Deep knowledge of AI technologies, including machine learning, deep learning, natural language processing (NLP), and computer vision. You're experienced with designing architectures that support AI models and algorithms.
- Programming and AI Tools: Proficiency in programming languages such as Python, R, or Java, with hands-on experience using AI frameworks like TensorFlow, PyTorch, Keras, or Scikit-learn. You can build and optimize AI models and systems from the ground up.
- Scalable Architecture Design: Expertise in designing scalable AI systems that can handle large datasets, complex algorithms, and high-performance requirements. You understand cloud-based AI services (AWS, GCP, Azure) and how to deploy AI solutions at scale.
- Data Engineering and Integration: Experience working with data pipelines and collaborating with data engineers to ensure that AI models are trained on high-quality data. You understand how to structure data systems for efficient model training and deployment.
- AI Governance and Ethics: Familiarity with AI governance, ethical AI practices, and compliance standards. You can ensure that AI models are fair, explainable, and secure, meeting regulatory requirements and business standards.
Educational Requirements:
- Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field. Equivalent experience in AI architecture is also highly valued.
- Certifications or additional coursework in AI, machine learning, or cloud platforms (AWS, GCP, Azure) are a plus.
Experience Requirements:
- 5+ years of experience in AI development or architecture, with a proven track record of designing and implementing scalable AI systems.
- Hands-on experience working with large-scale AI models and deploying them in production environments.
- Experience collaborating with cross-functional teams, including data scientists, machine learning engineers, and product managers, to bring AI solutions from concept to production.
Benefits
- Health and Wellness: Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums.
- Paid Time Off: Competitive vacation, sick leave, and 20 paid holidays per year.
- Work-Life Balance: Flexible work schedules and telecommuting options.
- Professional Development: Opportunities for training, certification reimbursement, and career advancement programs.
- Wellness Programs: Access to wellness programs, including gym memberships, health screenings, and mental health resources.
- Life and Disability Insurance: Life insurance and short-term/long-term disability coverage.
- Employee Assistance Program (EAP): Confidential counseling and support services for personal and professional challenges.
- Tuition Reimbursement: Financial assistance for continuing education and professional development.
- Community Engagement: Opportunities to participate in community service and volunteer activities.
- Recognition Programs: Employee recognition programs to celebrate achievements and milestones.