Building products that drive your business forward.
Product Development • Software Architecture • Software Development • Recruiting • Engineering Management
51 - 200
March 29
Building products that drive your business forward.
Product Development • Software Architecture • Software Development • Recruiting • Engineering Management
51 - 200
• Design and develop robust data pipelines to collect, process, and analyze large-scale telco datasets • Collaborate closely with data scientists and domain experts to understand business requirements and translate them into technical solutions • Architect scalable and efficient systems for machine learning model training, inference, and deployment • Implement data quality checks, monitoring, and logging to ensure the reliability and integrity of the AI tool • Optimize performance and efficiency of data processing and storage solutions • Stay updated with the latest advancements in data engineering, AI, and telco industry trends
• Previous experience working on cutting-edge applications in the generative AI space • Proven experience in building data pipelines and infrastructure for large-scale data processing • Proficiency in programming languages such as Python, Scala, or Java. • Strong understanding of distributed computing frameworks (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, GCP, Azure) • Experience with containerization (e.g., Docker, Kubernetes) and orchestration tools • Solid knowledge of database systems, including SQL and NoSQL databases. • Excellent problem-solving skills and attention to detail • Effective communication and collaboration abilities within cross-functional teams • Bachelor's or Master's degree in Computer Science, Engineering, or a related field • Prior experience in the telco industry or related fields is a plus
• 100% fully remote work (anywhere in North America) • Flexible hours • Competitive compensation package • Bonus or commission [depending on your role] • Excellent benefits package • Generous RRSP [or] 401k matching program • Unlimited vacation • Quarterly/Yearly team ‘offsite’ events
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