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Key Responsibilities:
AI Strategy and Design:
Architecture Leadership:
Design scalable, robust, and high-performance AI systems, ensuring seamless integration with existing platforms. Define AI architecture frameworks, tools, and methodologies used in building solutions.
AI Model Development:
Lead the design and optimization of machine learning models. Work on developing algorithms for predictive analytics, natural language processing, computer vision, and other AI subfields depending on business needs.
Collaboration & Team Leadership:
Collaborate with cross-functional teams, including data scientists, engineers, business analysts, and product managers, to define requirements and deliver high-quality solutions. Mentor junior AI professionals and ensure that best practices are followed in AI development.
Research & Innovation:
Keep up with the latest trends and developments in AI technologies, such as deep learning, reinforcement learning, and neural networks, and implement state-of-the-art models and algorithms.
AI Infrastructure & Deployment:
Oversee the deployment and maintenance of AI systems, ensuring they are scalable, reliable, and cost-efficient. Lead the use of cloud technologies, distributed systems, and high-performance computing (HPC) for AI model training and deployment.
Ethics & Compliance:
Ensure that AI solutions comply with industry standards, regulations, and ethical guidelines. Advocate for the responsible and transparent use of AI, particularly in areas of data privacy and bias mitigation.
Documentation & Reporting:
Document the architecture, models, and algorithms used, and provide regular updates on project progress to senior leadership. Prepare technical reports and presentations for stakeholders to communicate the potential and performance of AI models.
Qualifications:
Education:
Bachelor's or Master’s degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related field. Ph.D. in AI/ML or related disciplines is a plus.
Experience:
Minimum of 5-7 years of experience in AI, machine learning, or data science, with at least 3 years in an architectural or leadership role.
Hands-on experience with a wide range of AI technologies, including machine learning, deep learning, NLP, computer vision, and recommendation systems.
Experience with cloud platforms (AWS, Google Cloud, Microsoft Azure) and distributed computing environments.
Skills & Expertise:
Strong proficiency in programming languages such as Python, R, Java, or C++.
Expertise in AI/ML frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn.
Deep understanding of data structures, algorithms, and software engineering principles.
Strong knowledge of databases, big data tools (Hadoop, Spark), and AI/ML deployment techniques.
Familiarity with DevOps practices, CI/CD pipelines, and containerization (e.g., Docker, Kubernetes).
Understanding of AI ethics, fairness, and interpretability of models.
Soft Skills:
Excellent problem-solving and critical thinking skills.
Strong communication skills to explain complex AI concepts to both technical and non-technical stakeholders.
Ability to lead teams and work collaboratively across functions.
Strong business acumen and ability to align AI solutions with company goals and objectives.
Preferred Qualifications:
Experience with real-time AI applications and big data analytics.
Experience working with edge AI systems or IoT-based AI solutions.
Familiarity with MLOps (Machine Learning Operations) to streamline model deployment, monitoring, and maintenance.
Travel Percent:
The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .
The U.S. national annual pay range for this role is
$144800 to $319000
Our Benefits:
Any general requests for consideration of your skills, please
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