Data Lead / ML Architect Offline

About BYANAT

We are building a next-generation AI-powered platform designed for comprehensive observability of digital infrastructure, including mobile networks and data centers. By leveraging advanced analytics, automation, and real-time monitoring, we empower businesses to optimize performance, enhance reliability, and prevent failures before they happen.
 
Our platform delivers deep insights, anomaly detection, and predictive intelligence, enabling telecom operators, cloud providers, and enterprises to maintain seamless connectivity, operational efficiency, and infrastructure resilience in an increasingly complex digital landscape.
 
Join us in shaping the future of AI-driven infrastructure management! 🚀


Job Summary
As the Data Lead / ML Architect, you will be responsible for defining and executing the data and machine learning strategy for our cutting-edge observability platform. You will lead the design, development, and deployment of scalable data pipelines and advanced ML models while mentoring a cross-functional team of data engineers, data scientists, and ML engineers. Your leadership will ensure that our AI-driven features are built on a robust, secure, and high-performance data foundation, enabling real-time analytics and predictive insights for telecom network management.
 
Key Responsibilities

• Strategic Data & ML Leadership
  • Define and articulate the data architecture and machine learning strategy in alignment with business goals and regulatory requirements.
  • Develop a roadmap for integrating advanced ML models, including generative AI and LLMs, into the observability platform.
  • Establish best practices for data governance, quality, security, and compliance across the organization.
• Architecture & Pipeline Design
  • Design and oversee the implementation of scalable, high-performance data pipelines that support real-time data ingestion, processing, and analytics.
  • Architect end-to-end ML pipelines, from feature engineering and model training to deployment and monitoring in production environments.
  • Evaluate and integrate cutting-edge data and ML technologies that drive innovation and operational efficiency.
• Team Leadership & Collaboration
  • Lead, mentor, and manage a team of data engineers, data scientists, and ML engineers, fostering a culture of continuous learning and technical excellence.
  • Collaborate closely with cross-functional teams (including product management, software engineering, and telecom integration) to align data initiatives with overall product strategy.
  • Facilitate technical discussions, code reviews, and knowledge sharing sessions to drive best practices and cross-team collaboration.
• Operational Excellence & Continuous Improvement
  • Implement automated processes for model monitoring, retraining, and performance optimization.
  • Drive initiatives for continuous improvement in data processing, model accuracy, and system scalability.
  • Stay current with industry trends, emerging technologies, and regulatory changes affecting data and ML practices.
• Stakeholder Communication & Documentation
  • Communicate technical strategies, roadmaps, and progress updates to both technical and non-technical stakeholders.
  • Maintain comprehensive documentation of data architectures, ML model designs, and integration processes to ensure transparency and reproducibility.

 
Required Qualifications

• Experience:
  • 8–12+ years of professional experience in data engineering, data science, or ML engineering, with a significant track record in leadership roles.
  • Proven experience in architecting and deploying scalable data pipelines and ML models in production, preferably in telecom, enterprise software, or high-volume data environments.
• Technical Skills:
  • Expertise in programming languages such as Python (and relevant libraries: pandas, scikit-learn, TensorFlow, PyTorch) and familiarity with data processing frameworks (e.g., Apache Spark, Kafka).
  • Strong background in designing and implementing data architectures and ML pipelines, with hands-on experience in cloud platforms (AWS, Azure, or GCP).
  • Deep understanding of big data technologies, SQL/NoSQL databases, containerization (Docker, Kubernetes), and CI/CD pipelines.
  • Experience with deploying, monitoring, and managing AI/ML models in real-time applications.
• Leadership & Soft Skills:
  • Demonstrated ability to lead, mentor, and inspire cross-functional teams in an agile environment.
  • Excellent analytical, problem-solving, and decision-making skills.
  • Strong communication skills with the ability to convey complex technical concepts to both technical and non-technical audiences.
  • Proven experience in stakeholder management and strategic planning.
• Education:
  • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field. An advanced degree (MS or Ph.D.) is a plus.

 
Preferred Qualifications

• Experience working on AI-driven products or observability platforms.
• Familiarity with telecom network data, OSS, and real-time data analytics.
• Relevant certifications in data engineering, cloud architecture, or machine learning.

 
Benefits
✅ Competitive Compensation & Equity – We recognize your value with a highly competitive salary and a meaningful equity package.
🏥 Comprehensive Health Coverage – Enjoy top-tier medical insurance to keep you and your loved ones covered.
🌍 Flexibility & Work-Life Balance – Choose where and how you work with hybrid and remote-friendly options.
🚀 Career Growth & Learning – Access to advanced training, mentorship programs, and global industry conferences to accelerate your professional development.
🤝 Impact-Driven Culture – Join an innovative, fast-paced team where your expertise directly influences the future of AI-driven telecom network management.