Data Lead / ML Architect

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.

• 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.

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• 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.

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• 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.

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• 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.

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