What are the responsibilities and job description for the Senior Fullstack Software Engineer - Observability and AI Multimedia Processing position at Recordly.AI?
Senior Fullstack Software Engineer - Observability and AI Multimedia Processing
Company Overview : Recordly.AI
Speak. Transcribe. Illuminate.
Meet Recordly.AI. Experience the award-winning innovation! Recordly.AI, the world's first Unified
Audio & Video Intelligence Platform.
Join Recordly.ai – Pioneering the Future of Speech and Audio AI
At Recordly.ai, we are at the forefront of building industry-leading Speech and Audio foundation models that power our cutting-edge transcription, captioning, and translation services. As an AI Engineer specializing in Speech and Audio, you will have the unique opportunity to advance state-of-the-art research, develop foundational models, and integrate them into products that transform the way people and businesses interact with AI.
Our Mission :
Recordly.ai's mission is to create the most advanced Speech and Audio foundation models that enable unparalleled transcription accuracy and natural-sounding speech synthesis. Our current focus is on enhancing speech recognition and synthesis to deliver human-like voices and nuanced transcriptions, making AI interactions more intuitive and impactful.
Where We Stand :
We have already built and fine-tuned an accurate speech model capable of recognizing speech with 98% accuracy & another model for generating high-quality voice outputs from 10 seconds of input. We support advanced deep voice cloning using 30-60 minutes of voice data, setting new standards in AI-driven speech synthesis and transcription.
Job Title :
Senior Fullstack Software Engineer
Job Duties :
As a Senior Fullstack Software Engineer at Recordly, you will integrate advanced monitoring and observability technologies into innovative cloud native, web and mobile applications, while leading the development and optimization of cutting-edge models for audio and video data processing.
Key responsibilities include :
- Developing and integrating observability and monitoring frameworks for web and mobile applications, ensuring high performance, scalability, and real-time monitoring for critical systems.
- Designing and implementing advanced telemetry systems using tools like OpenTelemetry, AWS CloudWatch, and Datadog to monitor application health, performance, and availability.
- Building and deploying observability solutions that support distributed tracing, logging, and metrics collection for cloud-native environments.
- Leading efforts to optimize system monitoring tools, ensuring real-time alerting and efficient incident response processes.
- Implementing advanced monitoring strategies for microservices and serverless architectures to ensure smooth operation across platforms like AWS and GCP.
- Developing tools and processes for analyzing and visualizing telemetry data to provide actionable insights for performance improvements and troubleshooting.
- Collaborating with cross-functional teams to integrate observability solutions and enhance application resilience and reliability.
- Supporting the continuous improvement of infrastructure by monitoring system health and advising on necessary optimizations.
- Mentoring junior team members on best practices for observability, monitoring, and cloud architecture, ensuring high-quality code and system reliability.
- Working with cloud-native technologies such as Docker, Kubernetes, and serverless systems to implement scalable and secure observability solutions.
- Contributing to research on improving monitoring systems for distributed architectures, with an emphasis on reducing downtime and improving operational efficiency.
- Developing and integrating AI models for tasks such as speech recognition, emotion detection, video summarization, and content generation, focusing on achieving high performance, scalability, and real-time latency requirements.
- Conducting original research to address unsolved real-world problems in speech recognition and advancing the state-of-the-art for use cases involving multiple languages, including Turkish and English.
- Designing and implementing machine learning algorithms and training state-of-the-art Turkish and English speech recognition models on large datasets, followed by rigorous evaluation of their performance.
- Assisting in the development of voice AI models for specific tasks such as speech recognition and emotion detection, with a focus on integrating these models into broader system architectures.
- Supporting the fine-tuning and deployment of pre-trained AI models into production environments.
- Collaborating with teams to improve data collection and training processes for AI models in real-world applications.
Education Required :
Training Required :
Experience Required :
Special Requirements :
Foreign Language Requirements :
