Job Description
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
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