ML Engineer
Greenwich, CT · On-site
... 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 ...
ML Engineer
Greenwich, CT · On-site
... 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 ...
ML Engineer
Stamford, CT · On-site
... 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 ...
ML Engineer
Stamford, CT · On-site
... 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 ...
Senior Software Engineer Applied AI
Hartford, CT · On-site
$140 - $210/hr
... plus the machine learning and LLM pipelines around them. This is one seat that spans four ... Audio handling and the quirks of real human conversation (interruptions, timing, noise)
Senior Software Engineer Applied AI
Hartford, CT · On-site
$140 - $210/hr
... plus the machine learning and LLM pipelines around them. This is one seat that spans four ... Audio handling and the quirks of real human conversation (interruptions, timing, noise)
Senior Software Engineer Applied AI
Hartford, CT · On-site
$123K - $162K/yr
... plus the machine learning and LLM pipelines around them. This is one seat that spans four ... Audio handling and the quirks of real human conversation (interruptions, timing, noise)
New
Senior Software Engineer Applied AI
Hartford, CT · On-site
$123K - $162K/yr
... plus the machine learning and LLM pipelines around them. This is one seat that spans four ... Audio handling and the quirks of real human conversation (interruptions, timing, noise)
New
$50/hr
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
$50/hr
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
$50/hr
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
$50/hr
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
$50/hr
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
$50/hr
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
$50/hr
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
$50/hr
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
$50/hr
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
$50/hr
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
$50/hr
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
$50/hr
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
$50/hr
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
$50/hr
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
$50/hr
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
$50/hr
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
... audio signal processing. * Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard
Audio Machine Learning information
What is an audio machine learning?
An Audio Machine Learning job involves developing algorithms and models that analyze, process, and generate audio data. Responsibilities typically include working with speech recognition, music analysis, sound classification, and audio enhancement. Professionals in this field use deep learning, signal processing, and neural networks to improve audio-based applications like voice assistants, noise reduction systems, and music recommendation engines. They often work with datasets of speech, music, or environmental sounds to build models that understand and manipulate audio signals effectively.
What does an audio machine learning do?
Professionals in Audio Machine Learning typically spend their days designing, developing, and optimizing machine learning models tailored to audio data, such as speech or music recognition systems. You may also preprocess large datasets, extract and engineer relevant features, and collaborate closely with data scientists, audio engineers, and software developers to integrate your work into larger applications. Regular tasks often include running experiments, evaluating model performance, tuning hyperparameters, and keeping up with the latest advancements in the field. Team meetings, code reviews, and presenting findings to stakeholders are also common parts of the workweek.
What are the key skills and qualifications needed to thrive in audio machine learning?
To thrive in Audio Machine Learning, you need a strong background in machine learning, digital signal processing, and proficiency with programming languages such as Python or MATLAB, typically supported by a relevant degree in computer science, electrical engineering, or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with audio libraries (e.g., Librosa), and knowledge of cloud computing tools are highly valued, as are certifications in AI or data science. Strong problem-solving skills, creativity, and effective communication are essential soft skills for success in this field. These skills are crucial for developing innovative solutions, collaborating across multidisciplinary teams, and addressing complex audio data challenges in real-world projects.
What are the most commonly searched types of Audio Machine Learning jobs in Connecticut?
The most popular types of Audio Machine Learning jobs in Connecticut are:
What are popular job titles related to Audio Machine Learning jobs in Connecticut?
For Audio Machine Learning jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Audio Machine Learning jobs in Connecticut look for?
The top searched job categories for Audio Machine Learning jobs in Connecticut are:
Full-time
Re-posted 4 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.
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.