Recordly.AI
Senior Fullstack Software Engineer - Observability and AI Multimedia Processing
Recordly.AI, Santa Rosa, California, us, 95402
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:
Bachelor’s degree or higher in
Computer Science, Machine Learning, Electrical Engineering, or a closely related field. Must have GPA of 3.00 or above (based on 4.00)
Training Required:
Exposure to machine learning concepts and frameworks , with a focus on deploying AI models for practical applications.
Experience Required:
Progressive experience in Software Engineering,
with a strong emphasis on observability and monitoring systems. Ability to design and localize software for Turkish-speaking users, ensuring cultural and linguistic relevance. Extensive experience working with Application Monitoring Tools (APM) like New Relic, Datadog, Prometheus, and Grafana. Strong background in implementing and managing monitoring systems for cloud-native applications and distributed architectures (microservices, serverless). Solid experience in deploying and maintaining monitoring infrastructure in cloud platforms like AWS, GCP, and Azure. Experience with
Turkish Natural Language Processing tools and libraries such as Zemberek, NLTK, spaCy, and Hugging Face. Demonstrated ability to optimize application performance and troubleshoot issues using observability data. Previous experience in optimizing system performance, focusing on real-time latency and operational reliability. Proven ability to integrate observability tools into web and mobile applications to enhance system monitoring and application health. Hands-on experience with technologies such as Docker, Kubernetes, CI/CD pipelines, and cloud-native infrastructure. Strong experience in designing test cases and automation for English and Turkish-specific scenarios, including error handling and logging. Experience with English and Turkish-focused SEO strategies and UI/UX best practices. Strong knowledge of implementing distributed tracing, logging, and metrics collection for complex systems.
Special Requirements:
Proficiency in programming languages like Python, Java, JavaScript, C#, SQL, and frameworks such as React, Spring Boot, Node.js, and Nest.js. Proficiency in AWS CDK and AWS Cloudformation Extensive experience with cloud platforms (AWS, GCP) and containerization technologies such as Docker and Kubernetes. Expertise in scaling observability tools, such as OpenTelemetry and Prometheus, for production environments. Advanced skills in analyzing telemetry data and creating dashboards for system performance insights. Experience with Elasticsearch for log aggregation, search, and analysis. Familiarity with data privacy regulations and ethical considerations related to monitoring and observability. Proven track record in optimizing system reliability and scalability across multiple cloud platforms. Ability to mentor junior team members in observability best practices, cloud architecture, and full-stack development.
Foreign Language Requirements:
Fluent/Native in Turkish Fluent/Native in English
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:
Bachelor’s degree or higher in
Computer Science, Machine Learning, Electrical Engineering, or a closely related field. Must have GPA of 3.00 or above (based on 4.00)
Training Required:
Exposure to machine learning concepts and frameworks , with a focus on deploying AI models for practical applications.
Experience Required:
Progressive experience in Software Engineering,
with a strong emphasis on observability and monitoring systems. Ability to design and localize software for Turkish-speaking users, ensuring cultural and linguistic relevance. Extensive experience working with Application Monitoring Tools (APM) like New Relic, Datadog, Prometheus, and Grafana. Strong background in implementing and managing monitoring systems for cloud-native applications and distributed architectures (microservices, serverless). Solid experience in deploying and maintaining monitoring infrastructure in cloud platforms like AWS, GCP, and Azure. Experience with
Turkish Natural Language Processing tools and libraries such as Zemberek, NLTK, spaCy, and Hugging Face. Demonstrated ability to optimize application performance and troubleshoot issues using observability data. Previous experience in optimizing system performance, focusing on real-time latency and operational reliability. Proven ability to integrate observability tools into web and mobile applications to enhance system monitoring and application health. Hands-on experience with technologies such as Docker, Kubernetes, CI/CD pipelines, and cloud-native infrastructure. Strong experience in designing test cases and automation for English and Turkish-specific scenarios, including error handling and logging. Experience with English and Turkish-focused SEO strategies and UI/UX best practices. Strong knowledge of implementing distributed tracing, logging, and metrics collection for complex systems.
Special Requirements:
Proficiency in programming languages like Python, Java, JavaScript, C#, SQL, and frameworks such as React, Spring Boot, Node.js, and Nest.js. Proficiency in AWS CDK and AWS Cloudformation Extensive experience with cloud platforms (AWS, GCP) and containerization technologies such as Docker and Kubernetes. Expertise in scaling observability tools, such as OpenTelemetry and Prometheus, for production environments. Advanced skills in analyzing telemetry data and creating dashboards for system performance insights. Experience with Elasticsearch for log aggregation, search, and analysis. Familiarity with data privacy regulations and ethical considerations related to monitoring and observability. Proven track record in optimizing system reliability and scalability across multiple cloud platforms. Ability to mentor junior team members in observability best practices, cloud architecture, and full-stack development.
Foreign Language Requirements:
Fluent/Native in Turkish Fluent/Native in English