Artificial Intelligence Engineer

Hyqoo

Website: hyqoo.com
Job details:

Title - AI Engineer

Type - Contract

Location - Remote

Roles and Responsibilities:

- Vision & Strategy: Develop and continuously refine the long-term vision for driving innovation, user-centricity, and strategic alignment with broader business goals.

- AI & System Architecture: Lead the design and development of the AI-driven architecture, ensuring scalability, robustness, and cutting-edge technology integration across machine learning, NLP, data pipelines, and automation components.

- Team Leadership & Mentorship: Guide and inspire a team of AI engineers, machine learning specialists, and product developers, fostering a collaborative, innovative environment that encourages continuous learning and growth.

- Cross-Functional Collaboration: Partner closely with stakeholders from product, design, engineering, and business units to ensure the roadmap aligns with business needs and delivers tangible value.

- Platform Innovation: Keep the platform at the forefront of technology by incorporating emerging trends in agentic AI, multi-modal interfaces, generative AI, and autonomous orchestration.

- Quality & Performance Optimization: Establish benchmarks for platform performance, reliability, and security. Regularly review and refine core systems to ensure peak performance and user satisfaction.

- User Experience Focus: Drive a user-first approach, ensuring that functionality and interface support intuitive and seamless interactions for employees, partners, and customers.

- Vendor & Technology Management: Evaluate and manage strategic relationships with third-party vendors, especially in areas like NLP, Microsoft integrations (e.g., Copilot), and cloud infrastructure (Azure), to leverage the best available technology.

Qualifications:

- Education: Advanced degree (PhD preferred) in Computer Science, AI, Machine Learning, or a related field.

- Experience: 3-5 years of experience in AI/ML

- AI Expertise: Deep knowledge of machine learning techniques, NLP, LLMs, and data-driven AI architectures, with hands-on experience designing and deploying complex AI systems.

- Communication: Excellent communication skills with the ability to translate complex AI concepts into strategic roadmaps and actionable plans, tailored to both technical and non-technical stakeholders.

- Strategic Mindset: Strong analytical and strategic thinking skills, with the foresight to anticipate future AI trends and an understanding of how to apply them to a multi-functional platform.

Tools and Technologies:

- AI Development Tools: Proficiency with AI development tools and frameworks such as Azure ML, PyTorch, TensorFlow, LangChain, and transformer-based models.

- Cloud Infrastructure: Experience in using cloud-based AI and data infrastructure, particularly with Azure and Kubernetes.

- Model Optimization: Familiarity with tools for managing and optimizing AI models in production (e.g., Milvus for vector search, Graph API for MS integrations).

- System Design: Expertise in designing scalable, secure, and fault-tolerant AI systems, including familiarity with microservices, API management, and real-time data processing.

Preferred Skills:

- Industry Knowledge: Experience within a large, matrixed organization, preferably in technology or a related industry.

- Multi-Modal Systems: Knowledge of systems integrating chat, voice, visual data, and embedded dashboards is a plus.

- Enterprise AI Deployment: Familiarity with compliance, governance, and scalability considerations in deploying AI in enterprise environments.

- Project Management: Skilled in project planning, prioritization, and resource allocation within an agile development environment.

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