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Hourly Embedded Machine Learning Jobs in New York

Fox

Machine Learning Engineer I

New York, NY · Hybrid

$74K - $130K/yr

Rotate across two ML-focused teams embedded within operating business units * Build, train, evaluate, and deploy production machine learning models * Work with large-scale, real-world datasets and ...

PROPRIUS

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

Expert level coding skills (Python, C++ at minimum) * 3+ years' experience working with machine learning in embedded applications: model quantization, fixed point neural networks (CNN and RNN)

Meta

Product Manager, Machine Learning

New York, NY · On-site

$173K/yr

Product Manager, Machine Learning Responsibilities: * Display strong leadership, organizational and ... Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual ...

Distributed Spectrum Inc

Embedded Engineer

New York, NY · On-site

$150K - $220K/yr

Design, develop, test, and deploy performant and robust software on embedded and edge compute ... Familiarity with the fundamentals of signal processing, machine learning, computer vision, or ...

CVS Health

Senior Machine Learning Engineer

New York, NY · On-site

$111K - $222K/yr

We're looking for a Senior Machine Learning Engineer to help build and scale the next generation of ... hourly rate or base annual full-time salary for all positions in the job grade within which this ...

Meta

Software Engineer, Machine Learning

New York, NY

$183K/yr

Software Engineer, Machine Learning Responsibilities: * Collaborate with cross-functional teams ... Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual ...

Carlyle

AlpInvest Embedded Data Scientist

New York, NY · On-site +1

$180K - $200K/yr

Join our dynamic Investment Data Science Team as an Embedded Data Scientist to partner directly ... The ideal candidate can move seamlessly between developing machine learning models and engaging ...

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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?

AspectHourly Embedded Machine LearningHourly Data Scientist
CredentialsKnowledge of embedded systems, programming, ML algorithmsDegree in Data Science, Statistics, or related field
Work EnvironmentEmbedded hardware, IoT devices, real-time systemsData analysis, modeling, visualization in office or cloud
Industry UsageConsumer electronics, automotive, IoT devicesFinance, 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:
Hourly Embedded Machine Learning jobs near you

Machine Learning Engineer

Kforce Technology Staffing

Armonk, NY • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New

Job description

RESPONSIBILITIES:
Kforce has a client in Armonk, NY that is seeking a Lead Machine Learning Engineer to support a leading Energy and Utilities organization by designing and delivering scalable machine learning solutions that drive operational efficiency and business decision-making. This role will own the end-to-end machine learning architecture, lead the design of predictive models and recommendation engines, and guide models from prototype through production deployment.
Responsibilities:
* Design and own the overall machine learning system architecture and model lifecycle
* Develop scalable predictive models and recommendation engines to support operational and resource planning initiatives
* Lead technical design decisions and mentor small delivery teams throughout the development lifecycle
* Translate business requirements into machine learning solutions and production-ready models
* Partner with data engineers, data scientists, and business stakeholders to deliver high-impact analytics solutions
* Deploy, monitor, and optimize machine learning models using Azure Machine Learning
* Establish best practices for model governance, performance monitoring, and continuous improvement
* Maintain CI/CD workflows, version control, and containerized deployments using GitHub and Docker
REQUIREMENTS:
* 8+ years of experience in Machine Learning Engineering, Data Engineering, or AI solution development
* Proven experience designing enterprise-scale machine learning architectures and deploying production ML solutions
* Strong Python development experience including pandas, scikit-learn, XGBoost/LightGBM, and PyTorch (preferred)
* Advanced SQL skills with experience working in Snowflake
* Hands-on experience with Azure Machine Learning, GitHub, and Docker
* Strong understanding of MLOps, model deployment, monitoring, and lifecycle management
* Experience leading technical teams and delivering enterprise analytics solutions
Preferred Qualifications:
* Experience with optimization algorithms, operations research, or resource planning
* Experience within the Energy and Utilities industry or another regulated environment
* Familiarity with enterprise operational data platforms and utility data ecosystems
* Strong communication skills with the ability to bridge business needs and technical solutions
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
By clicking ?Apply Today? you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.

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