The Machine Learning Engineer will design and develop scalable training pipelines for multimodal AI ... paced startup environment, and able to demonstrate strong ownership and urgency in execution.
The Machine Learning Engineer will design and develop scalable training pipelines for multimodal AI ... paced startup environment, and able to demonstrate strong ownership and urgency in execution.
Machine Learning Expert
Palo Alto, CA · On-site
Role - Machine Learning Expert (This role is open to US Citizens, Green Card holders, GC-EAD only ... Hundreds of Fortune 1000 and innovative startup clients with thousands of successful projects ...
Machine Learning Expert
Palo Alto, CA · On-site
Role - Machine Learning Expert (This role is open to US Citizens, Green Card holders, GC-EAD only ... Hundreds of Fortune 1000 and innovative startup clients with thousands of successful projects ...
Hundreds of Fortune 1000 and innovative startup clients with thousands of successful projects ... machine learning, deep learning, NLP, computer vision, reinforcement learning, and/or other AI ...
Hundreds of Fortune 1000 and innovative startup clients with thousands of successful projects ... machine learning, deep learning, NLP, computer vision, reinforcement learning, and/or other AI ...
Advex is a seed stage tech startup focused on solving challenges in computer vision through effective data collection. As a Machine Learning Engineer, you will shape the technical direction of the ...
Advex is a seed stage tech startup focused on solving challenges in computer vision through effective data collection. As a Machine Learning Engineer, you will shape the technical direction of the ...
Machine Learning Engineer (This role is open to US Citizens, Green Card holders, GC-EAD only. We do ... Hundreds of Fortune 1000 and innovative startup clients with thousands of successful projects ...
Machine Learning Engineer (This role is open to US Citizens, Green Card holders, GC-EAD only. We do ... Hundreds of Fortune 1000 and innovative startup clients with thousands of successful projects ...
Interface with our world-class machine learning research team to help turn core research into ... Wear many hats to make things happen in a dynamic startup environment * Bring your own unique ...
Quick apply
Interface with our world-class machine learning research team to help turn core research into ... Wear many hats to make things happen in a dynamic startup environment * Bring your own unique ...
Interface with our world-class machine learning research team to help turn core research into ... Wear many hats to make things happen in a dynamic startup environment * Bring your own unique ...
Interface with our world-class machine learning research team to help turn core research into ... Wear many hats to make things happen in a dynamic startup environment * Bring your own unique ...
Machine Learning Engineer
Torrance, CA · On-site
$160K - $250K/yr
As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ... Prior experience working in a startup environment Compensation For this role, the target salary ...
Quick apply
Machine Learning Engineer
Torrance, CA · On-site
$160K - $250K/yr
As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ... Prior experience working in a startup environment Compensation For this role, the target salary ...
Machine Learning Infrastructure Engineer
San Francisco, CA · On-site
$126K - $166K/yr
... Machine Learning Infrastructure Engineer Location: Onsite in San Francisco Compensation ... AI startup based in San Francisco and backed by Elad Gil (#1 Solo VC), Eric Schmidt (former Google ...
Machine Learning Infrastructure Engineer
San Francisco, CA · On-site
$126K - $166K/yr
... Machine Learning Infrastructure Engineer Location: Onsite in San Francisco Compensation ... AI startup based in San Francisco and backed by Elad Gil (#1 Solo VC), Eric Schmidt (former Google ...
Interface with our world-class machine learning research team to help turn core research into ... Wear many hats to make things happen in a dynamic startup environment * Bring your own unique ...
Interface with our world-class machine learning research team to help turn core research into ... Wear many hats to make things happen in a dynamic startup environment * Bring your own unique ...
Machine Learning Engineer
Los Angeles, CA · On-site
$160K - $250K/yr
As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ... Prior experience working in a startup environment Compensation For this role, the target salary ...
Machine Learning Engineer
Los Angeles, CA · On-site
$160K - $250K/yr
As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ... Prior experience working in a startup environment Compensation For this role, the target salary ...
Software Engineer, Machine Learning
San Francisco, CA · On-site
$160K - $220K/yr
Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact. You Will * Conceptualize, develop, and deploy machine learning models that ...
Software Engineer, Machine Learning
San Francisco, CA · On-site
$160K - $220K/yr
Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact. You Will * Conceptualize, develop, and deploy machine learning models that ...
Machine Learning Engineer
San Francisco, CA · On-site +1
$160K/yr
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of ... The Data Science team is hiring an experienced Machine Learning Engineer with a background building ...
Machine Learning Engineer
San Francisco, CA · On-site +1
$160K/yr
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of ... The Data Science team is hiring an experienced Machine Learning Engineer with a background building ...
You thrive in a fast-paced startup environment and are motivated by building models that don't just ... What You'll Do You'll develop machine learning models that move beyond experimentation and into ...
You thrive in a fast-paced startup environment and are motivated by building models that don't just ... What You'll Do You'll develop machine learning models that move beyond experimentation and into ...
Software Engineer, Machine Learning
Bodega Bay, CA · On-site
$160K - $220K/yr
Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact. You Will * Conceptualize, develop, and deploy machine learning models that ...
Quick apply
Software Engineer, Machine Learning
Bodega Bay, CA · On-site
$160K - $220K/yr
Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact. You Will * Conceptualize, develop, and deploy machine learning models that ...
Machine Learning Engineer
San Francisco, CA · Remote
$160K/yr
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of ... The Data Science team is hiring an experienced Machine Learning Engineer with a background building ...
Quick apply
Machine Learning Engineer
San Francisco, CA · Remote
$160K/yr
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of ... The Data Science team is hiring an experienced Machine Learning Engineer with a background building ...
Responsibilities : • Develop, optimize, and deploy lightweight machine learning models for edge ... paced startup environment. • Ability to provide mentorship, technical guidance, and career ...
Responsibilities : • Develop, optimize, and deploy lightweight machine learning models for edge ... paced startup environment. • Ability to provide mentorship, technical guidance, and career ...
Head of Machine Learning - 1811
San Francisco, CA · Remote
$180K - $250K/yr
Previous leadership experience at a fast-growing startup (approximately 20-400 employees). Technical Qualifications Candidates should have expertise in: * End-to-end Machine Learning lifecycle
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Head of Machine Learning - 1811
San Francisco, CA · Remote
$180K - $250K/yr
Previous leadership experience at a fast-growing startup (approximately 20-400 employees). Technical Qualifications Candidates should have expertise in: * End-to-end Machine Learning lifecycle
As a Machine Learning Engineer, you'll be integral in developing state-of-the-art AI intelligence ... Atoms is a robotics startup that develops industrial robotics and physical AI systems to automate ...
As a Machine Learning Engineer, you'll be integral in developing state-of-the-art AI intelligence ... Atoms is a robotics startup that develops industrial robotics and physical AI systems to automate ...
... Machine Learning Scientist with deep expertise in building and deploying production machine ... You thrive in a fast-paced startup environment and are motivated by building models that don't just ...
... Machine Learning Scientist with deep expertise in building and deploying production machine ... You thrive in a fast-paced startup environment and are motivated by building models that don't just ...
Commission Machine Learning Startup information
What is the difference between Commission Machine Learning Startup vs Data Scientist?
| Aspect | Commission Machine Learning Startup | Data Scientist |
|---|---|---|
| Credentials | Degree in Computer Science, Data Science, or related fields; experience with ML models | Degree in Computer Science, Statistics, or related fields; proficiency in programming and data analysis |
| Work Environment | Startup setting, fast-paced, innovative projects, often remote or flexible | Corporate or research environment, collaborative teams, often office-based |
| Industry Usage | Tech startups, AI-focused companies, innovative product development | Tech firms, finance, healthcare, research institutions |
| Search & Comparison Intent | Understanding roles in ML startups, freelance or commission-based opportunities | Career development, skill requirements, industry roles |
Commission Machine Learning Startup roles focus on developing ML solutions within startup environments, often with flexible or freelance arrangements. Data Scientists typically work in established companies, applying statistical and programming skills to analyze data. Both roles require similar credentials but differ in work setting and industry focus.
What are the most commonly searched types of Machine Learning Startup jobs in California? The most popular types of Machine Learning Startup jobs in California are:
What cities in California are hiring for Commission Machine Learning Startup jobs? Cities in California with the most Commission Machine Learning Startup job openings:
Full-time
Re-posted 28 days ago
Job description
Job Summary:
Abaka AI is built on the mission to be the world’s most trusted data partner for AI companies, supporting global partners with reliable and scalable data solutions. The Machine Learning Engineer will design and develop scalable training pipelines for multimodal AI systems, collaborate with data engineering and research teams, and influence core decisions around model training strategy and infrastructure.
Responsibilities:
• Design, build, and optimize scalable machine learning pipelines for multimodal model training, fine-tuning, and evaluation across text, image, audio, video, and 3D data.
• Work closely with data engineering and research teams to develop efficient data workflows, including collection, preprocessing, annotation, versioning, and model integration.
• Implement and refine training strategies for large-scale AI systems, including vision, video, and diffusion models, ensuring reproducibility, efficiency, and strong model performance.
• Develop tools and automation frameworks that accelerate model experimentation, hyperparameter tuning, and deployment.
• Identify and address performance bottlenecks in data or training pipelines to improve throughput, stability, and resource utilization.
• Collaborate with product and infrastructure teams to ensure smooth integration of model outputs into both internal and client-facing applications.
• Support internal best practices for model governance, experiment tracking, and documentation to maintain high engineering standards and reproducibility.
Qualifications:
Required:
• Strong academic background in computer science, artificial intelligence, machine learning, or related fields.
• 3+ years of experience in applied machine learning or ML engineering, with a demonstrated ability to deliver production-ready models or pipelines.
• Proficient in Python and ML frameworks such as PyTorch, TensorFlow, or JAX, with hands-on experience in large-scale distributed training and inference systems.
• Familiarity with multimodal data processing (e.g., text-image pairing, video understanding, speech-audio modeling) and dataset optimization for model training.
• Solid understanding of ML system design, including feature pipelines, data loaders, model serving, and evaluation frameworks.
• Experience with modern infrastructure tools such as Kubernetes, Ray, Airflow, or MLflow, along with cloud-based training environments (AWS, GCP, Azure).
• Excellent communication and collaboration skills, capable of working effectively across engineering, research, and product teams to accomplish shared goals.
• Self-driven and adaptable, comfortable operating in a fast-paced startup environment, and able to demonstrate strong ownership and urgency in execution.
Preferred:
• Master’s degree or Ph.D. is preferred.
Company:
Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA, with a team of 51-200 employees. The company is currently Growth Stage.
Abaka AI is built on the mission to be the world’s most trusted data partner for AI companies, supporting global partners with reliable and scalable data solutions. The Machine Learning Engineer will design and develop scalable training pipelines for multimodal AI systems, collaborate with data engineering and research teams, and influence core decisions around model training strategy and infrastructure.
Responsibilities:
• Design, build, and optimize scalable machine learning pipelines for multimodal model training, fine-tuning, and evaluation across text, image, audio, video, and 3D data.
• Work closely with data engineering and research teams to develop efficient data workflows, including collection, preprocessing, annotation, versioning, and model integration.
• Implement and refine training strategies for large-scale AI systems, including vision, video, and diffusion models, ensuring reproducibility, efficiency, and strong model performance.
• Develop tools and automation frameworks that accelerate model experimentation, hyperparameter tuning, and deployment.
• Identify and address performance bottlenecks in data or training pipelines to improve throughput, stability, and resource utilization.
• Collaborate with product and infrastructure teams to ensure smooth integration of model outputs into both internal and client-facing applications.
• Support internal best practices for model governance, experiment tracking, and documentation to maintain high engineering standards and reproducibility.
Qualifications:
Required:
• Strong academic background in computer science, artificial intelligence, machine learning, or related fields.
• 3+ years of experience in applied machine learning or ML engineering, with a demonstrated ability to deliver production-ready models or pipelines.
• Proficient in Python and ML frameworks such as PyTorch, TensorFlow, or JAX, with hands-on experience in large-scale distributed training and inference systems.
• Familiarity with multimodal data processing (e.g., text-image pairing, video understanding, speech-audio modeling) and dataset optimization for model training.
• Solid understanding of ML system design, including feature pipelines, data loaders, model serving, and evaluation frameworks.
• Experience with modern infrastructure tools such as Kubernetes, Ray, Airflow, or MLflow, along with cloud-based training environments (AWS, GCP, Azure).
• Excellent communication and collaboration skills, capable of working effectively across engineering, research, and product teams to accomplish shared goals.
• Self-driven and adaptable, comfortable operating in a fast-paced startup environment, and able to demonstrate strong ownership and urgency in execution.
Preferred:
• Master’s degree or Ph.D. is preferred.
Company:
Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA, with a team of 51-200 employees. The company is currently Growth Stage.