ML Engineer
San Francisco, CA · On-site
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 ...
ML Engineer
San Francisco, CA · On-site
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 ...
ML Engineer
Greenwich, CT · On-site
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 ...
ML Engineer
Greenwich, CT · On-site
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 ...
ML Engineer
Fort Worth, TX · On-site
They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, while collaborating with cross-functional teams to drive innovation in AI applications. Responsibilities ...
ML Engineer
Fort Worth, TX · On-site
They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, while collaborating with cross-functional teams to drive innovation in AI applications. Responsibilities ...
ML Engineer
Santa Clara, CA · On-site
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 ...
ML Engineer
Santa Clara, CA · On-site
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 ...
ML Engineer
Dallas, TX · On-site
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 ...
ML Engineer
Dallas, TX · On-site
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 ...
ML Engineer
Jacksonville, FL · On-site
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 ...
ML Engineer
Jacksonville, FL · On-site
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 ...
ML Engineer
United, PA · On-site
They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, optimize models focused on audio data, and collaborate with cross-functional teams to drive innovation in AI ...
ML Engineer
United, PA · On-site
They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, optimize models focused on audio data, and collaborate with cross-functional teams to drive innovation in AI ...
ML Engineer
Mountain View, CA · On-site
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 ...
ML Engineer
Mountain View, CA · On-site
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 ...
ML Engineer
Menlo Park, CA · On-site
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 ...
ML Engineer
Menlo Park, CA · On-site
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 ...
ML Engineer
Boston, MA · On-site
They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, while collaborating with cross-functional teams to drive innovation in AI applications. Responsibilities ...
ML Engineer
Boston, MA · On-site
They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, while collaborating with cross-functional teams to drive innovation in AI applications. Responsibilities ...
ML Engineer
Austin, TX · On-site
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 ...
ML Engineer
Austin, TX · On-site
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 ...
ML Engineer
Seattle, WA · On-site
The ML Engineer will be responsible for developing, training, deploying, and operationalizing machine learning systems across Weyerhaeuser's AI portfolio, including pricing optimization, industrial ...
ML Engineer
Seattle, WA · On-site
The ML Engineer will be responsible for developing, training, deploying, and operationalizing machine learning systems across Weyerhaeuser's AI portfolio, including pricing optimization, industrial ...
ML Engineer
San Francisco, CA · On-site
$180K - $300K/yr
The role At Mach9, ML Engineers build the perception models at the core of our AI-enabled CAD system. We build models to extract 3D object and line features from dense LiDAR point clouds and imagery.
ML Engineer
San Francisco, CA · On-site
$180K - $300K/yr
The role At Mach9, ML Engineers build the perception models at the core of our AI-enabled CAD system. We build models to extract 3D object and line features from dense LiDAR point clouds and imagery.
AI/ML Engineer
Minneapolis, MN · On-site
AI/ML Engineer Work Location: MinneapolisMN55401 Detailed The AI/ML Engineer will be responsible for delivering capital-funded cloud migration initiatives involving AI/ML and data platforms. The ...
AI/ML Engineer
Minneapolis, MN · On-site
AI/ML Engineer Work Location: MinneapolisMN55401 Detailed The AI/ML Engineer will be responsible for delivering capital-funded cloud migration initiatives involving AI/ML and data platforms. The ...
The ML Engineer will be responsible for developing, training, deploying, and operationalizing machine learning systems across Weyerhaeuser's AI portfolio, including pricing optimization, industrial ...
The ML Engineer will be responsible for developing, training, deploying, and operationalizing machine learning systems across Weyerhaeuser's AI portfolio, including pricing optimization, industrial ...
AI/ML Engineer
Round Rock, TX · On-site
AI/ML Engineer Location: Round Rock, TX Duration: Contract(onsite) Job Summary We are looking for an experienced AI/ML Engineer to design, develop, and deploy machine learning and artificial ...
AI/ML Engineer
Round Rock, TX · On-site
AI/ML Engineer Location: Round Rock, TX Duration: Contract(onsite) Job Summary We are looking for an experienced AI/ML Engineer to design, develop, and deploy machine learning and artificial ...
The ML Engineer will be responsible for developing, training, deploying, and operationalizing machine learning systems across Weyerhaeuser's AI portfolio, including pricing optimization, industrial ...
The ML Engineer will be responsible for developing, training, deploying, and operationalizing machine learning systems across Weyerhaeuser's AI portfolio, including pricing optimization, industrial ...
ML ENGINEER Job Location Primary: Tampa - FL/ Alternate GA Job summary - - Typically, minimum of 4 years - Professional Experience in Coding, Designing, Developing and Analyzing Data in DS setting ...
ML ENGINEER Job Location Primary: Tampa - FL/ Alternate GA Job summary - - Typically, minimum of 4 years - Professional Experience in Coding, Designing, Developing and Analyzing Data in DS setting ...
ML Engineer
Malvern, PA · On-site
$100K - $135K/yr
Roles & Responsibilities Senior AWS ML Engineer with 8+ years of experience in • Design, build, and deploy scalable Machine Learning solutions on AWS using SageMaker, ensuring high performance ...
ML Engineer
Malvern, PA · On-site
$100K - $135K/yr
Roles & Responsibilities Senior AWS ML Engineer with 8+ years of experience in • Design, build, and deploy scalable Machine Learning solutions on AWS using SageMaker, ensuring high performance ...
ML Engineer
Minneapolis, MN · On-site
Own production health: drift detection, performance regression, rollback strategies, and incident response." * 5+ years software engineering with 2+ years shipping ML models to production. * Strong ...
ML Engineer
Minneapolis, MN · On-site
Own production health: drift detection, performance regression, rollback strategies, and incident response." * 5+ years software engineering with 2+ years shipping ML models to production. * Strong ...
Ml Engineer information
See salary details
$33K - $42.9K
7% of jobs
$42.9K - $52.8K
2% of jobs
$52.8K - $62.7K
11% of jobs
$65.9K is the 25th percentile. Wages below this are outliers.
$62.7K - $72.6K
16% of jobs
$72.6K - $82.5K
14% of jobs
The median wage is $82.9K / yr.
$82.5K - $92.5K
14% of jobs
$92.5K - $102.4K
11% of jobs
$104.1K is the 75th percentile. Wages above this are outliers.
$102.4K - $112.3K
7% of jobs
$112.3K - $122.2K
12% of jobs
$122.2K - $132.1K
4% of jobs
$132.1K - $142K
3% of jobs
$33K
$89.2K
$142K
How much do ml engineer jobs pay per year?
As of Aug 21, 2026, the average yearly pay for ml engineer in the United States is $89,183.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,500.00 and $109,000.00 per year, depending on experience, location, and employer.
What is an ML engineer?
ML Engineers, or Machine Learning Engineers, are professionals who design, build, and deploy machine learning models into production systems. They bridge the gap between data science and software engineering, ensuring that machine learning solutions are scalable, reliable, and efficient. ML Engineers work with large datasets, develop algorithms, and optimize models for performance. They also collaborate with data scientists, software developers, and business stakeholders to solve real-world problems using artificial intelligence.
What are the key skills and qualifications needed to thrive as an ML engineer?
To thrive as an ML Engineer, you need a solid background in mathematics, statistics, computer science, and experience with machine learning algorithms, often supported by a degree in a related field. Familiarity with programming languages like Python or R, ML frameworks such as TensorFlow or PyTorch, and data processing tools is typically required, with relevant certifications being a plus. Strong problem-solving, critical thinking, and communication skills help you translate complex data insights into actionable solutions and work effectively in teams. These abilities ensure accurate model development, effective deployment, and successful collaboration on data-driven projects.
What are some common challenges ML engineers face when deploying models to production?
Machine Learning Engineers often encounter challenges such as ensuring models remain accurate over time as data changes (known as data drift), optimizing models for speed and scalability, and integrating models seamlessly with existing software systems. Additionally, maintaining model performance in real-world environments can require continuous monitoring, retraining, and close collaboration with data engineers and DevOps teams. Addressing these challenges typically involves robust testing, using automated pipelines, and staying up-to-date with the latest MLOps best practices.
What is the difference between Ml Engineer vs Data Scientist?
| Aspect | ML Engineer | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's or Master's in CS, Data Science, or related fields; knowledge of ML frameworks | Bachelor's or Master's in Statistics, Data Science, or related fields; strong analytical skills |
| Work Environment | Develops, deploys, and maintains ML models in production systems | Analyzes data, builds models, and provides insights for decision-making |
| Employer & Industry Usage | Tech companies, startups, and enterprises deploying ML solutions | Research institutions, tech firms, and industries relying on data analysis |
While both roles involve working with data and machine learning, ML Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights to inform business decisions. The roles often overlap but differ in their core responsibilities and focus areas.
Are machine learning engineers still in demand?
Machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. They typically require skills in programming, data analysis, and frameworks like TensorFlow or PyTorch, and often work in environments that emphasize continuous learning and adaptation. The demand is expected to remain strong as organizations increasingly rely on machine learning solutions for competitive advantage.
What does a machine learning engineer do?
A machine learning engineer designs, develops, and deploys machine learning models to solve specific problems using large datasets. They work with programming languages like Python or Java, utilize frameworks such as TensorFlow or PyTorch, and often collaborate with data scientists and software engineers to integrate models into applications.
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Full-time
Re-posted 29 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.
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.
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.