... are embedded into delivery and operations • Troubleshoot production issues, drive root-cause ... machine learning engineering or applied machine learning software engineering • Demonstrated ...
... are embedded into delivery and operations • Troubleshoot production issues, drive root-cause ... machine learning engineering or applied machine learning software engineering • Demonstrated ...
Data Scientist I (Assistant)
Rahway, NJ · On-site
$104K - $114K/yr
... machine learning workflows and rigorous statistical analyses to help accelerate the discovery of next-generation medicines. As an embedded member of a cross-functional scientific computing group, you ...
Data Scientist I (Assistant)
Rahway, NJ · On-site
$104K - $114K/yr
... machine learning workflows and rigorous statistical analyses to help accelerate the discovery of next-generation medicines. As an embedded member of a cross-functional scientific computing group, you ...
... through embedded deployment, ensuring that perception systems run efficiently on resource-constrained robotic hardware. You will also leverage modern machine learning approaches to push the ...
... through embedded deployment, ensuring that perception systems run efficiently on resource-constrained robotic hardware. You will also leverage modern machine learning approaches to push the ...
... through embedded deployment, ensuring that perception systems run efficiently on resource-constrained robotic hardware. You will also leverage modern machine learning approaches to push the ...
... through embedded deployment, ensuring that perception systems run efficiently on resource-constrained robotic hardware. You will also leverage modern machine learning approaches to push the ...
Senior Data Scientist
Manhattan, NY · On-site
$110K - $124K/yr
... Machine Learning Team focused on the application of data science, machine learning and AI to ... Collaborate with business partners to translate business context into technical solutions embedded ...
Quick apply
Senior Data Scientist
Manhattan, NY · On-site
$110K - $124K/yr
... Machine Learning Team focused on the application of data science, machine learning and AI to ... Collaborate with business partners to translate business context into technical solutions embedded ...
RESEARCH SCHOLAR
New York, NY · On-site
$27/hr
Develop and evaluate models in machine learning and reinforcement learning * Publish papers in top ... Salary In compliance with NYC's Pay Transparency Act, the hourly rate for this position is $27.00 ...
RESEARCH SCHOLAR
New York, NY · On-site
$27/hr
Develop and evaluate models in machine learning and reinforcement learning * Publish papers in top ... Salary In compliance with NYC's Pay Transparency Act, the hourly rate for this position is $27.00 ...
In this role, you will operate at the intersection of application security, machine learning, and ... Partner closely with engineering, platform, and AI research teams to ensure security is embedded as ...
Quick apply
In this role, you will operate at the intersection of application security, machine learning, and ... Partner closely with engineering, platform, and AI research teams to ensure security is embedded as ...
Sr. Data / M/L Engineer
Manhattan, NY · On-site
$76.50 - $85/hr
Temporary Salary: $76.50-85 Hourly Start Date: Jul 13, 2026 Hybrid on site in Union Square, NY. No ... machine learning models for predictive and prescriptive analytics -Establish scalable data ...
Sr. Data / M/L Engineer
Manhattan, NY · On-site
$76.50 - $85/hr
Temporary Salary: $76.50-85 Hourly Start Date: Jul 13, 2026 Hybrid on site in Union Square, NY. No ... machine learning models for predictive and prescriptive analytics -Establish scalable data ...
Responsibilities : • Define enterprise-wide AI, ML, and data science standards embedded into self ... Required : • Advanced degree in Data Science, Machine Learning, Statistics, or related ...
Responsibilities : • Define enterprise-wide AI, ML, and data science standards embedded into self ... Required : • Advanced degree in Data Science, Machine Learning, Statistics, or related ...
Software Engineer, Data Platform
New York, NY · Remote
$168K - $324K/yr
About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction ... Build and integrate the components of Ramp's Analytics Platform and Machine Learning Platform.
Quick apply
Software Engineer, Data Platform
New York, NY · Remote
$168K - $324K/yr
About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction ... Build and integrate the components of Ramp's Analytics Platform and Machine Learning Platform.
Software Engineer
Manhattan, NY · On-site
Experience with embedded systems and machine learning programing * platforms including TensorFlow, PyTorch etc Additional Information All your information will be kept confidential according to EEO ...
Software Engineer
Manhattan, NY · On-site
Experience with embedded systems and machine learning programing * platforms including TensorFlow, PyTorch etc Additional Information All your information will be kept confidential according to EEO ...
Software Engineer
Manhattan, NY · On-site
Experience with embedded systems and machine learning programing * platforms including TensorFlow, PyTorch etc Additional Information All your information will be kept confidential according to EEO ...
Software Engineer
Manhattan, NY · On-site
Experience with embedded systems and machine learning programing * platforms including TensorFlow, PyTorch etc Additional Information All your information will be kept confidential according to EEO ...
Software Engineer, Data Platform
New York, NY · On-site
$168K - $324K/yr
About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction ... Build and integrate the components of Ramp's Analytics Platform and Machine Learning Platform.
Software Engineer, Data Platform
New York, NY · On-site
$168K - $324K/yr
About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction ... Build and integrate the components of Ramp's Analytics Platform and Machine Learning Platform.
Staff Data Scientist - Fraud & Risk
New York, NY · On-site
$180K - $210K/yr
Stay current with advancements in AI and machine learning, applying innovative approaches to real-world problems. * Model Socure's embedded leadership competencies: continuous learning, effective ...
Staff Data Scientist - Fraud & Risk
New York, NY · On-site
$180K - $210K/yr
Stay current with advancements in AI and machine learning, applying innovative approaches to real-world problems. * Model Socure's embedded leadership competencies: continuous learning, effective ...
Algorithm Developer II
New York, NY · On-site
$38 - $58/hr
US Citizen, GC Holders or Authorized to Work in the US In this role, you will be embedded into the ... Deep Learning, Computer Vision, LLMs, Machine Learning or Artificial Intelligence - One or more ...
Algorithm Developer II
New York, NY · On-site
$38 - $58/hr
US Citizen, GC Holders or Authorized to Work in the US In this role, you will be embedded into the ... Deep Learning, Computer Vision, LLMs, Machine Learning or Artificial Intelligence - One or more ...
... solutions embedded into business workflows. This is a front-line execution role , focused on ... Data scientists * Machine learning engineers * Applied AI engineers * Partner directly with ...
... solutions embedded into business workflows. This is a front-line execution role , focused on ... Data scientists * Machine learning engineers * Applied AI engineers * Partner directly with ...
Research Scientist 4 - Machine Learning and Inference Research, LLM Post-Training
New York, NY · On-site
The Machine Learning and Inference Research team is a dedicated research team building up Netflix ... Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation ...
Research Scientist 4 - Machine Learning and Inference Research, LLM Post-Training
New York, NY · On-site
The Machine Learning and Inference Research team is a dedicated research team building up Netflix ... Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation ...
Cloud Security Senior Manager - Azure Infrastructure & AI
Jersey City, NJ · On-site
$71.75 - $95.25/hr
... Azure Machine Learning, Cognitive Services, and AI Studio, with protections embedded from development through deployment • Developing AI security playbooks and governance controls covering ...
Cloud Security Senior Manager - Azure Infrastructure & AI
Jersey City, NJ · On-site
$71.75 - $95.25/hr
... Azure Machine Learning, Cognitive Services, and AI Studio, with protections embedded from development through deployment • Developing AI security playbooks and governance controls covering ...
Research Scientist 4 - Machine Learning and Inference Research, LLM Post-Training
New York, NY · On-site
The Machine Learning and Inference Research team is a dedicated research team building up Netflix ... Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation ...
Research Scientist 4 - Machine Learning and Inference Research, LLM Post-Training
New York, NY · On-site
The Machine Learning and Inference Research team is a dedicated research team building up Netflix ... Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation ...
Research Scientist 4 - Machine Learning and Inference Research, LLM Post-Training
New York, NY · On-site
The Machine Learning and Inference Research team is a dedicated research team building up Netflix ... Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation ...
Research Scientist 4 - Machine Learning and Inference Research, LLM Post-Training
New York, NY · On-site
The Machine Learning and Inference Research team is a dedicated research team building up Netflix ... Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation ...
Hourly Embedded Machine Learning information
What are the key skills and qualifications needed to thrive as an Hourly Embedded Machine Learning Engineer, and why are they important?
To thrive as an Hourly Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer engineering or a related field. Familiarity with tools such as TensorFlow Lite, embedded Linux, microcontroller development environments, and model optimization frameworks is typically required. Strong problem-solving skills, adaptability, and effective communication help you address complex technical challenges and collaborate with cross-functional teams. These skills are crucial for designing efficient, real-time ML solutions that operate reliably on resource-constrained embedded devices.
How does an Hourly Embedded Machine Learning professional typically collaborate with hardware and software teams during a project?
As an Hourly Embedded Machine Learning professional, you will often work closely with both hardware and software engineering teams to ensure that machine learning models are efficiently integrated into embedded systems. This typically involves frequent communication to align on hardware constraints, such as memory and processing power, and to optimize algorithms for real-time performance. You may also participate in joint debugging sessions and code reviews to address integration issues and streamline deployment. Collaboration is key, as successful projects depend on the seamless interaction between machine learning solutions and the embedded hardware platform.
What is an Hourly Embedded Machine Learning engineer?
An Hourly Embedded Machine Learning engineer is a professional who specializes in developing and deploying machine learning models on embedded systems, such as microcontrollers, IoT devices, or edge devices, and is compensated on an hourly basis rather than a salaried or project-based arrangement. These engineers work to optimize algorithms so they can run efficiently on devices with limited computing power, memory, and energy resources. Their responsibilities often include model selection, quantization, optimization, and integration of machine learning pipelines into hardware. Hiring on an hourly basis allows for flexibility in project scope and duration, making it ideal for companies with specific, time-limited needs. They often collaborate with hardware engineers, data scientists, and software developers to create intelligent embedded solutions.
What is the difference between Hourly Embedded Machine Learning vs Hourly Data Scientist?
| Aspect | Hourly Embedded Machine Learning | Hourly Data Scientist |
|---|---|---|
| Credentials | Knowledge of embedded systems, programming, ML algorithms | Degree in Data Science, Statistics, or related field |
| Work Environment | Embedded hardware, IoT devices, real-time systems | Data analysis, modeling, visualization in office or cloud |
| Industry Usage | Consumer electronics, automotive, IoT devices | Finance, healthcare, marketing, research |
Hourly Embedded Machine Learning specialists focus on integrating ML models into embedded systems and hardware, often working with IoT devices and real-time constraints. In contrast, Hourly Data Scientists analyze large datasets to develop predictive models primarily in cloud or office environments. While both roles require programming skills, embedded ML emphasizes hardware integration, whereas data science centers on data analysis and visualization.
What are the most commonly searched types of Embedded Machine Learning jobs in New York? The most popular types of Embedded Machine Learning jobs in New York are:
What are popular job titles related to Hourly Embedded Machine Learning jobs in New York? For Hourly Embedded Machine Learning jobs in New York, the most frequently searched job titles are:
What job categories do people searching Hourly Embedded Machine Learning jobs in New York look for? The top searched job categories for Hourly Embedded Machine Learning jobs in New York are:
What cities in New York are hiring for Hourly Embedded Machine Learning jobs? Cities in New York with the most Hourly Embedded Machine Learning job openings:
Full-time
Posted 28 days ago
Job description
Job Summary:
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers and businesses. In this role as a Senior Associate, Generative AI Engineer, you will design, build, and support production generative AI products and APIs, collaborating with various engineering teams to ensure reliability and performance.
Responsibilities:
• Build and operate production generative artificial intelligence services and reusable backend application programming interfaces for firmwide use
• Combine enterprise data assets with large language and multimodal models to deliver high-quality user experiences
• Design scalable architectures with clear interfaces and separation of concerns to enable broader developer adoption
• Implement batch and real-time processing patterns to support high-throughput, low-latency use cases
• Collaborate with cloud engineering and site reliability engineering partners to deliver resilient, observable systems
• Translate research concepts into production-ready software through experimentation, evaluation, and iterative hardening
• Optimize system performance, scalability, and cost across inference, storage, and compute
• Define and track measurable outcomes, including objectives and key results aligned to business needs
• Ensure responsible artificial intelligence practices, controls, and governance are embedded into delivery and operations
• Troubleshoot production issues, drive root-cause analysis, and implement preventative improvements
Qualifications:
Required:
• PhD in a quantitative discipline such as Computer Science, Mathematics, or Statistics, or equivalent practical experience
• 3+ years of experience as an individual contributor in machine learning engineering or applied machine learning software engineering
• Demonstrated experience delivering production machine learning services in an enterprise environment, including being accountable for service health
• Strong fundamentals in statistics, optimization, and machine learning theory with applied depth in natural language processing and/or computer vision
• Hands-on experience building distributed, multi-threaded, and scalable systems (for example Ray, Horovod, or DeepSpeed)
• Strong software engineering fundamentals, including data structures, algorithms, and software development lifecycle best practices
• Experience designing and delivering service-oriented systems and application programming interfaces with scalability and performance requirements
• Ability to define success metrics and write clear objectives and key results aligned to business expectations
• Strong problem-framing skills to align machine learning solutions to business objectives and constraints
• Excellent communication skills with the ability to influence and build trust across technical and non-technical stakeholders
Preferred:
• Experience designing and implementing pipeline workflows using directed acyclic graph frameworks (for example Kubeflow, DVC, or Ray)
• Experience building batch and streaming microservices exposed via gRPC and/or GraphQL
• Demonstrable experience with parameter-efficient fine-tuning, quantization, and quantization-aware fine-tuning for large language models
• Experience with advanced prompting strategies such as chain-of-thought, tree-of-thought, or graph-of-thought approaches
• Experience with multimodal large language model use cases (text plus image, speech, or video)
• Experience partnering closely with cloud engineering and site reliability engineering teams on production readiness and operations
• Experience measuring and improving model quality using offline evaluation and production monitoring
Company:
With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutions—carrying forth the innovative spirit of our heritage firms in global operations across 100 markets. Founded in 2000, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers and businesses. In this role as a Senior Associate, Generative AI Engineer, you will design, build, and support production generative AI products and APIs, collaborating with various engineering teams to ensure reliability and performance.
Responsibilities:
• Build and operate production generative artificial intelligence services and reusable backend application programming interfaces for firmwide use
• Combine enterprise data assets with large language and multimodal models to deliver high-quality user experiences
• Design scalable architectures with clear interfaces and separation of concerns to enable broader developer adoption
• Implement batch and real-time processing patterns to support high-throughput, low-latency use cases
• Collaborate with cloud engineering and site reliability engineering partners to deliver resilient, observable systems
• Translate research concepts into production-ready software through experimentation, evaluation, and iterative hardening
• Optimize system performance, scalability, and cost across inference, storage, and compute
• Define and track measurable outcomes, including objectives and key results aligned to business needs
• Ensure responsible artificial intelligence practices, controls, and governance are embedded into delivery and operations
• Troubleshoot production issues, drive root-cause analysis, and implement preventative improvements
Qualifications:
Required:
• PhD in a quantitative discipline such as Computer Science, Mathematics, or Statistics, or equivalent practical experience
• 3+ years of experience as an individual contributor in machine learning engineering or applied machine learning software engineering
• Demonstrated experience delivering production machine learning services in an enterprise environment, including being accountable for service health
• Strong fundamentals in statistics, optimization, and machine learning theory with applied depth in natural language processing and/or computer vision
• Hands-on experience building distributed, multi-threaded, and scalable systems (for example Ray, Horovod, or DeepSpeed)
• Strong software engineering fundamentals, including data structures, algorithms, and software development lifecycle best practices
• Experience designing and delivering service-oriented systems and application programming interfaces with scalability and performance requirements
• Ability to define success metrics and write clear objectives and key results aligned to business expectations
• Strong problem-framing skills to align machine learning solutions to business objectives and constraints
• Excellent communication skills with the ability to influence and build trust across technical and non-technical stakeholders
Preferred:
• Experience designing and implementing pipeline workflows using directed acyclic graph frameworks (for example Kubeflow, DVC, or Ray)
• Experience building batch and streaming microservices exposed via gRPC and/or GraphQL
• Demonstrable experience with parameter-efficient fine-tuning, quantization, and quantization-aware fine-tuning for large language models
• Experience with advanced prompting strategies such as chain-of-thought, tree-of-thought, or graph-of-thought approaches
• Experience with multimodal large language model use cases (text plus image, speech, or video)
• Experience partnering closely with cloud engineering and site reliability engineering teams on production readiness and operations
• Experience measuring and improving model quality using offline evaluation and production monitoring
Company:
With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutions—carrying forth the innovative spirit of our heritage firms in global operations across 100 markets. Founded in 2000, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.