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Audio Speech Machine Learning Jobs in Connecticut

Catalyst Labs

ML Engineer

Greenwich, CT · On-site

Catalyst Labs is a leading talent agency specializing in Applied AI, Machine Learning, and Data ... natural speech interaction and real-time audio understanding. • Develop and optimize ML models ...

Catalyst Labs

ML Engineer

Stamford, CT · On-site

Catalyst Labs is a leading talent agency specializing in Applied AI, Machine Learning, and Data ... natural speech interaction and real-time audio understanding. • Develop and optimize ML models ...

Interon IT Solutions

IBM Watson Developer

Hartford, CT · On-site

Leveraging AI, NLP Technologies and cognitive machine learning to develop chatbot applications ... Tuning and enhancing Speech to Text models. Required Qualifications * 8+ years software delivery ...

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Audio Speech Machine Learning information

What is an audio speech machine learning engineer?

An Audio Speech Machine Learning Engineer is a specialized professional who designs, develops, and implements machine learning models that process and analyze audio and speech data. Their work involves tasks like speech recognition, speaker identification, and audio event detection by leveraging algorithms and large datasets. These engineers collaborate with data scientists, software developers, and linguists to create applications such as voice assistants, transcription tools, and automated customer service systems. Expertise in signal processing, deep learning frameworks, and programming languages like Python is crucial for this role.

What are some common challenges faced when developing machine learning models for audio speech applications?

A key challenge in audio speech machine learning roles is dealing with diverse and noisy audio data, which can significantly affect model accuracy. Additionally, models must be robust to different accents, languages, and speaking styles, requiring large and varied datasets for training and validation. Collaboration with data engineers, linguists, and software developers is often necessary to ensure high-quality data pipelines and model integration into production systems. Staying updated with the latest research and optimizing models for real-time performance are also ongoing aspects of the role.

What are the key skills and qualifications needed to thrive as an audio speech machine learning engineer, and why are they important?

To thrive as an Audio Speech Machine Learning Engineer, you need a solid background in machine learning, signal processing, and programming (typically Python), along with a relevant degree in computer science or a related field. Familiarity with tools like TensorFlow or PyTorch, audio processing libraries (such as Librosa), and experience with speech datasets and ASR systems are commonly required. Critical soft skills include problem-solving, innovation, and effective communication for collaborating with cross-functional teams. These skills are essential to develop accurate, scalable speech recognition systems that advance voice-driven technology.

What is the difference between Audio Speech Machine Learning vs Speech Data Analyst?

AspectAudio Speech Machine LearningSpeech Data Analyst
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegree in Data Analysis, Statistics, or related fields; experience with data tools
Work EnvironmentResearch labs, tech companies, AI startupsData analysis teams, research institutions, tech firms
Industry UsageDeveloping speech recognition, voice assistants, NLP applicationsAnalyzing speech datasets, improving speech models, reporting insights

Audio Speech Machine Learning focuses on developing algorithms for speech recognition and processing, often involving model training and AI development. Speech Data Analysts interpret speech data, generate insights, and support model improvements. Both roles require strong analytical skills, but their core tasks differ: one builds models, the other analyzes data.

What are popular job titles related to Audio Speech Machine Learning jobs in Connecticut?

For Audio Speech Machine Learning jobs in Connecticut, the most frequently searched job titles are:

What job categories do people searching Audio Speech Machine Learning jobs in Connecticut look for?

The top searched job categories for Audio Speech Machine Learning jobs in Connecticut are:

Audio Speech Machine Learning jobs near you
Infographic showing various Audio Speech Machine Learning job openings in Connecticut as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

ML Engineer

Catalyst Labs

Greenwich, CT • On-site

Full-time

Re-posted 6 days ago

Job description

Job Summary:
Catalyst Labs is a leading talent agency specializing in Applied AI, Machine Learning, and Data Science. They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to drive innovation in AI applications.
Responsibilities:
• Design, build, and deploy production-grade ML systems with end-to-end ownership of the model lifecycle from conception to deployment and maintenance.
• Architect and deliver AI-powered solutions enabling natural speech interaction and real-time audio understanding.
• Develop and optimize ML models focused on audio data to extract business-critical insights from previously unstructured voice data.
• Build agents capable of operating natively on real-world audio inputs.
• Collaborate with cross-functional teams to shape the foundations of the AI stack, improve tooling, and drive innovation in LLM and audio ML applications.
• Work directly with customers to identify needs, gather feedback, and deliver impactful real-world solutions.
• Handle the entire AI lifecycle, including data acquisition, preprocessing, model training, deployment, inference, and monitoring in production environments.
• Participate in continuous improvement of the ML infrastructure and processes for scalability and performance.
Qualifications:
Required:
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• 1-6 years of professional experience in ML engineering.
• Strong programming skills in Python (TypeScript experience is a plus).
• Hands-on experience with ML frameworks such as PyTorch or TensorFlow.
• Familiarity with cloud environments and infrastructure (preferably AWS).
• Strong understanding of data pipeline design, real-time inference, and model monitoring.
• Excellent communication skills with the ability to engage directly with customers and stakeholders.
• Proven experience building and deploying ML models into production environments.
• Demonstrated ability to own the full model lifecycle from data ingestion and model development to deployment and monitoring.
• Experience with audio-focused ML projects or similar domains involving unstructured data.
• Proficiency in building scalable data pipelines for model training and evaluation.
• Solid grasp of ML systems architecture, feature engineering, evaluation strategies, and deployment best practices.
Preferred:
• Familiarity with FastAPI, OpenAI APIs, Baseten, LiteLLM, LiveKit, PostgreSQL, Redis, and S3 is a plus.
Company:
Welcome to Catalyst Labs – Powering Catalytic Growth At Catalyst Labs, catalytic growth isn't just a concept, it's our driving force. Founded in , the company is headquartered in London, GB, , with a team of 11-50 employees. The company is currently Early Stage.

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