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Recordly

Senior Fullstack Software Engineer - Observability and AI Multimedia Processing

Recordly, San Mateo, CA, United States, 94409

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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 withTurkish 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