Product Manager, AutoML
$120K - $170K/yr
Hive's AutoML platform allows our customers to easily train, evaluate, and deploy customized machine learning models. Beginning with their own data, Hive's AutoML platform guides our customers ...
Product Manager, AutoML
$120K - $170K/yr
Hive's AutoML platform allows our customers to easily train, evaluate, and deploy customized machine learning models. Beginning with their own data, Hive's AutoML platform guides our customers ...
Product Manager, AutoML
Seattle, WA · On-site
$120K - $170K/yr
Hive's AutoML platform allows our customers to easily train, evaluate, and deploy customized machine learning models. Beginning with their own data, Hive's AutoML platform guides our customers ...
Product Manager, AutoML
Seattle, WA · On-site
$120K - $170K/yr
Hive's AutoML platform allows our customers to easily train, evaluate, and deploy customized machine learning models. Beginning with their own data, Hive's AutoML platform guides our customers ...
MLOps Engineer
San Francisco, CA · On-site
Leverage AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment Skills Required: * Develop and maintain ML ...
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MLOps Engineer
San Francisco, CA · On-site
Leverage AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment Skills Required: * Develop and maintain ML ...
ML Ops Engineer
Concord, CA · On-site
... Leverage AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment Qualifications 10+ Years of professional ...
ML Ops Engineer
Concord, CA · On-site
... Leverage AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment Qualifications 10+ Years of professional ...
MLOps Engineer
Charlotte, NC · On-site
Leverage AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment Qualifications * 10+ Years of professional ...
MLOps Engineer
Charlotte, NC · On-site
Leverage AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment Qualifications * 10+ Years of professional ...
MLOPS Engineer
Concord, CA · On-site
Leverage AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment Qualifications: * 10+ Years of professional ...
Quick apply
MLOPS Engineer
Concord, CA · On-site
Leverage AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment Qualifications: * 10+ Years of professional ...
Build, train, and deploy machine learning models using Azure AutoML and other Azure-based services. Design and implement scalable, production-ready ML solutions in a cloud environment. Collaborate ...
Build, train, and deploy machine learning models using Azure AutoML and other Azure-based services. Design and implement scalable, production-ready ML solutions in a cloud environment. Collaborate ...
ML Ops Engineer
Charlotte, NC · On-site
Leverage AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment Qualifications * 10+ Years of professional ...
Quick apply
ML Ops Engineer
Charlotte, NC · On-site
Leverage AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment Qualifications * 10+ Years of professional ...
Data Scientist
Irving, TX · On-site
Experience with Azure AutoML Experience with cloud computing platforms, preferably Microsoft Azure.
Data Scientist
Irving, TX · On-site
Experience with Azure AutoML Experience with cloud computing platforms, preferably Microsoft Azure.
ML Architect/ Data Scientist (Inventory Forecasting) - R01563519
Dallas, TX · On-site +1
$150K - $160K/yr
Build, train, and deploy machine learning models using Azure AutoML and other Azure-based services. * Design and implement scalable, production-ready ML solutions in a cloud environment.
ML Architect/ Data Scientist (Inventory Forecasting) - R01563519
Dallas, TX · On-site +1
$150K - $160K/yr
Build, train, and deploy machine learning models using Azure AutoML and other Azure-based services. * Design and implement scalable, production-ready ML solutions in a cloud environment.
Senior Data Scientist
Spring, TX · On-site +1
Hands-on experience with AutoML platforms (e.g., Dataiku) and familiarity with Azure AutoML and Mosaic AI AutoML (Databricks) * Deep understanding of Azure cloud technologies, including Azure Machine ...
Senior Data Scientist
Spring, TX · On-site +1
Hands-on experience with AutoML platforms (e.g., Dataiku) and familiarity with Azure AutoML and Mosaic AI AutoML (Databricks) * Deep understanding of Azure cloud technologies, including Azure Machine ...
AI/ML Engineer
Washington, DC · On-site
Key Responsibilities - Design and deliver solutions involving: • Natural Language Processing (NLP) • Computer Vision • Predictive Analytics • Generative AI • AutoML - Work within the client ...
AI/ML Engineer
Washington, DC · On-site
Key Responsibilities - Design and deliver solutions involving: • Natural Language Processing (NLP) • Computer Vision • Predictive Analytics • Generative AI • AutoML - Work within the client ...
AI Engineer
Hillsboro, OR · On-site
Perform lightweight training with AWS SageMaker, AutoML, and deploy inference endpoints. AWS Engineering: Utilize AWS services (Lambda, API Gateway, S3, DynamoDB, SageMaker, Bedrock) for scalable AI ...
AI Engineer
Hillsboro, OR · On-site
Perform lightweight training with AWS SageMaker, AutoML, and deploy inference endpoints. AWS Engineering: Utilize AWS services (Lambda, API Gateway, S3, DynamoDB, SageMaker, Bedrock) for scalable AI ...
Key Responsibilities - Design and deliver solutions involving: • Natural Language Processing (NLP) • Computer Vision • Predictive Analytics • Generative AI • AutoML - Work within the client ...
Key Responsibilities - Design and deliver solutions involving: • Natural Language Processing (NLP) • Computer Vision • Predictive Analytics • Generative AI • AutoML - Work within the client ...
AIML Architect
Charlotte, NC · Hybrid
Strong knowledge of H2O.ai (Driverless AI or H2O3), AutoML frameworks, and enterprise ML workflows. * Proficient with MLflow for experiment tracking, model packaging, deployment, and lifecycle ...
AIML Architect
Charlotte, NC · Hybrid
Strong knowledge of H2O.ai (Driverless AI or H2O3), AutoML frameworks, and enterprise ML workflows. * Proficient with MLflow for experiment tracking, model packaging, deployment, and lifecycle ...
Databricks Architect/Admin
Hartford, CT · Hybrid
$65.25 - $85.75/hr
Knowledge of MLflow, AutoML, AI/ML concepts, and automation frameworks * Experience with Oracle, Git, Jira, ServiceNow, and ETL tools like Fivetran/Ab Initio Preferred: * Experience with Generative ...
Databricks Architect/Admin
Hartford, CT · Hybrid
$65.25 - $85.75/hr
Knowledge of MLflow, AutoML, AI/ML concepts, and automation frameworks * Experience with Oracle, Git, Jira, ServiceNow, and ETL tools like Fivetran/Ab Initio Preferred: * Experience with Generative ...
Experience with multi-fidelity optimization, neural architecture search, or large-scale AutoML systems. * Familiarity with surrogate modeling, physics-informed neural networks, or uncertainty ...
Experience with multi-fidelity optimization, neural architecture search, or large-scale AutoML systems. * Familiarity with surrogate modeling, physics-informed neural networks, or uncertainty ...
... AutoML-Tools zur Beschleunigung von Prototypen und Experimenten Sicherstellung von Skalierbarkeit, Sicherheit und stabilen Betriebsprozessen der entwickelten Losungen Fachliche Anforderungen:
... AutoML-Tools zur Beschleunigung von Prototypen und Experimenten Sicherstellung von Skalierbarkeit, Sicherheit und stabilen Betriebsprozessen der entwickelten Losungen Fachliche Anforderungen:
AIML Engineer
Scottsdale, AZ · On-site
... AutoML Vertex AI Build tools Mandatory Skills : MLOPS,GenAI - LLMOps,Python - Data Science,Machine Learning - AIOPS,Deep Learning - AIOPS
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AIML Engineer
Scottsdale, AZ · On-site
... AutoML Vertex AI Build tools Mandatory Skills : MLOPS,GenAI - LLMOps,Python - Data Science,Machine Learning - AIOPS,Deep Learning - AIOPS
AI Engineer
Hillsboro, OR · On-site
Perform lightweight training with AWS SageMaker, AutoML, and deploy inference endpoints. AWS Engineering: Utilize AWS services (Lambda, API Gateway, S3, DynamoDB, SageMaker, Bedrock) for scalable AI ...
AI Engineer
Hillsboro, OR · On-site
Perform lightweight training with AWS SageMaker, AutoML, and deploy inference endpoints. AWS Engineering: Utilize AWS services (Lambda, API Gateway, S3, DynamoDB, SageMaker, Bedrock) for scalable AI ...
Automl information
What are some common challenges faced by professionals working in AutoML roles, and how can they be addressed?
Professionals in AutoML roles often encounter challenges related to automating complex machine learning workflows, ensuring model interpretability, and managing large-scale data pipelines. Balancing automation with customization to meet specific business needs can be tricky, as off-the-shelf solutions may not fit every scenario. Collaborating closely with data scientists, engineers, and domain experts helps in customizing AutoML solutions and overcoming integration issues. Staying updated on the latest tools and frameworks and continuously testing models in production are also essential for success.
What are the key skills and qualifications needed to thrive as an AutoML Engineer, and why are they important?
To thrive as an AutoML Engineer, you need strong proficiency in machine learning, data science, and programming (often Python), typically supported by a degree in computer science, data science, or a related field. Familiarity with AutoML platforms (such as Google AutoML, H2O.ai, or AutoKeras), cloud services, and experience with ML frameworks like TensorFlow or scikit-learn are essential. Analytical thinking, problem-solving abilities, and effective communication help you translate business needs into automated solutions and collaborate with cross-functional teams. These skills are vital for efficiently developing robust, scalable machine learning pipelines that accelerate model deployment and drive business value.
What is the difference between Automl vs Data Scientist?
| Aspect | Automl | Data Scientist |
|---|---|---|
| Required Credentials | Typically certifications in machine learning, data analysis, or related tools | Degree in data science, statistics, computer science, or related fields |
| Work Environment | Focus on developing and deploying automated machine learning models, often in tech or AI companies | Analyze data, build models, and generate insights across various industries |
| Employer & Industry Usage | Used by companies seeking scalable ML solutions, including tech, finance, and healthcare | Employed across industries for data analysis, predictive modeling, and decision support |
Automl focuses on automating machine learning processes, making it easier to develop models without extensive coding. Data Scientists, however, perform in-depth data analysis, model building, and interpretation. While Automl tools assist Data Scientists, their roles differ in scope and expertise required.
What is AutoML?
AutoML, or Automated Machine Learning, refers to the process of automating the end-to-end tasks of applying machine learning to real-world problems. This includes steps like data preprocessing, feature selection, algorithm selection, and hyperparameter tuning. AutoML tools are designed to make machine learning more accessible to non-experts and to improve efficiency for experts by reducing the manual effort and expertise needed to build effective models. Popular AutoML platforms include Google Cloud AutoML, H2O AutoML, and Auto-sklearn.
More about Automl jobs
What are the most commonly searched types of Automl jobs? The most popular types of Automl jobs are:
What job categories do people searching Automl jobs look for? The top searched job categories for Automl jobs are:
Job description
About Hive
Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive's solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more.
Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI.
About the Role
As a Product Manager for AutoML, you will be an essential part of the Hive team, working effectively across all disciplines to build, launch, and iterate features for our AutoML platform. Hive's AutoML platform allows our customers to easily train, evaluate, and deploy customized machine learning models. Beginning with their own data, Hive's AutoML platform guides our customers through the process of creating a fully-functional model accessible via an API endpoint just like Hive pre-trained models.
In this role, you will work closely with all stakeholders to define product requirements and see implementation through to completion, leading development efforts between engineering and design. You are passionate about organization, experienced in working with agile teams, have a good understanding of best practices in software engineering, highly effective in communicating and problem solving, and have experience managing enterprise projects.
Responsibilities
- Own the roadmap, functional requirements, and development timeline for Hive's AutoML platform
- Develop a clear product vision and roadmap, mock up concepts, write specs and oversee execution from inception to completion
- Work with the executive team to determine top priorities, help define new features, and improve our AutoML platform habitually
- Work with teams to drive alignment, remove blockers, anticipate and make tradeoffs, and balance business needs against technical constraints throughout project lifecycles
- Analyze customer data and feedback to identify opportunities for feature enhancements
- Help engineering and product teams estimate and decompose complex projects into manageable parts with delivery plans, and track progress against those plans
- Clearly communicate product benefits to our customers and internal stakeholders
- Measure engineering velocity, and help identify and establish new best practices to improve the speed and security at which projects are delivered
- Maintain awareness of industry best practices for data maintenance handling as it relates to your role
- Adhere to policies, guidelines and procedures pertaining to the protection of information assets
- Report actual or suspected security and/or policy violations/breaches to an appropriate authority
Requirements
- You have a Bachelor's Degree in Computer Science, Engineering, or similar field
- You have 2+ years of Product Management experience and a track record of building web products, preferably in a startup or fast-paced environment
- You have technical experience with any of the following: data, analytics, design or engineering
- You have experience working with engineering, design, and customers in enterprise software or related technical fields
- You have technical depth that lets you understand tradeoffs and ask engineers insightful questions about architecture and product decisions alike
- You have excellent verbal and written communication and presentation skills
- You have experience leading a team, and effectively implementing team goals and deadlines
- You are comfortable with - and can thrive in - an environment that is fast paced in a competitive industry
- You are detail-oriented, organized, collaborative, and hands-on
- Beyond just shipping new products, you obsess about continuous product improvement
Who We Are
We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Hive, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company.
Thank you for your interest in Hive and we hope to meet you soon!
The current expected base salary for this position ranges from $120,000 - $170,000. Actual compensation may vary depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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