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C2C Machine Learning Engineer Jobs (NOW HIRING)

HeyMilo AI

Machine Learning Engineer

Manhattan, NY

Machine Learning Engineer Company: HeyMilo AI Location: New York, NY, USA Contract Details: Full-time HeyMilo AI is a fast-growing startup based in New York City that specializes in developing ...

Forhyre

Machine Learning Engineer

New York, NY

We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...

RAPID EAGLE INC

Machine Learning Engineer

Sunnyvale, CA · Remote

$70 - $80/hr

Health insurance Machine Learning Engineer 100% Remote We are seeking a highly skilled Machine Learning Engineer to design, develop, deploy, and maintain scalable machine learning solutions that ...

Rapid Eagle Inc

Machine Learning Engineer

$70 - $80/hr

Health insurance Machine Learning Engineer 100% Remote We are seeking a highly skilled Machine Learning Engineer to design, develop, deploy, and maintain scalable machine learning solutions that ...

Full Scope

Machine Learning Engineer

Reston, VA

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly Salary: Competitive We are seeking a highly skilled and motivated Machine Learning Engineer to join ...

Paylocity

Machine Learning Engineer

Schaumburg, IL · On-site

Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing infrastructure and ...

Paylocity

Machine Learning Engineer

Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing infrastructure and ...

Willing Tech

Machine Learning Engineer

San Francisco, CA · On-site +1

$172K - $384K/yr

They're now looking for a Machine Learning Engineer to help build the next generation of AI-powered tools that generate structured visuals from scientific inputs . If you're excited by real-world ...

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C2C Machine Learning Engineer information

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$128.8K

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How much do c2c machine learning engineer jobs pay per year?

As of Jun 18, 2026, the average yearly pay for c2c machine learning engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What is a C2C Machine Learning Engineer?

A C2C (Corp-to-Corp) Machine Learning Engineer is a professional who works as an independent consultant or through a company, typically on contract, to design, develop, and deploy machine learning models for clients. They have expertise in data science, programming, and machine learning frameworks, and often work on projects involving data analysis, predictive modeling, and artificial intelligence solutions. C2C indicates the business arrangement between two companies rather than direct employment. This role requires both strong technical skills and the ability to manage client relationships and project deliverables.

What are the key skills and qualifications needed to thrive as a C2C Machine Learning Engineer, and why are they important?

To thrive as a C2C Machine Learning Engineer, you need a strong background in computer science, statistics, and machine learning algorithms, typically supported by a relevant degree. Experience with programming languages like Python or Java, ML frameworks (such as TensorFlow or PyTorch), and cloud platforms is essential, along with knowledge of data engineering tools. Strong problem-solving, collaboration, and communication skills help you work effectively with cross-functional teams and adapt solutions to user needs. These skills are crucial for delivering scalable, high-impact machine learning solutions that drive value in customer-to-customer (C2C) environments.

How does a C2C Machine Learning Engineer typically collaborate with cross-functional teams during project development?

As a C2C (Customer-to-Customer) Machine Learning Engineer, you’ll frequently collaborate with product managers, data scientists, backend engineers, and UX designers to develop solutions that enhance user experience on C2C platforms. You may participate in regular sprint meetings to discuss progress, refine models based on user feedback, and ensure seamless integration of ML features into the overall product. Effective communication and the ability to translate technical findings into actionable insights are crucial, as you’ll often coordinate with non-technical stakeholders to align on business goals and implementation strategies.
Machine Learning Engineer

Machine Learning Engineer

Apex Informatics

Cincinnati, OH • On-site

Full-time

Posted 6 days ago

Job description

Below is my newest requirement. Please send Full Legal Name, LinkedIn, Location, Contact Details, C2C rate, and work authorization status with each submittal.
Client: Kroger
Location: Hybrid onsite in Cincinnati OH (local only)
Interview Mode: Virtual Interview
Type: Contract
Work authorization: Cannot work with OPT or CPT
Rate: Open (market rate)
We are seeking a dynamic Senior Machine Learning Engineer to lead the integration and operationalization of machine learning models. This role requires collaboration with data scientists and leadership teams, and a strong foundation in MLOps methodologies. Experience in diverse ML platforms, including Google Vertex AI and other cloud and open-source technologies, is essential. The candidate will bridge MLOps, data science, and leadership to ensure the smooth functioning of our ML infrastructure.
Qualifications:
Minimum of 4 years of experience in MLOps, with a demonstrated ability to work with various ML platforms.
Strong proficiency in Python and familiarity with data science methodologies.
Experience with cloud technologies, particularly Google Cloud and Vertex AI, and adaptability to technologies like Microsoft Azure or open-source tools.
Excellent communication skills, capable of bridging technical and business domains
Experience in developing state-of-the-art techniques for multi-stage, personalized, context-aware, and sequential recommender systems.
Hands-on experience working on recommender systems, drawing from ML techniques such as embedding based retrieval, reinforcement learning, transformers, and LLMs.
Capable software engineering skills to lead a multi stage recommender system model lifecycle from inception to production.

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