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Temporary Meta Machine Learning Jobs in Edison, NJ

Meta

Product Designer, Human Interface

New York, NY

$139K/yr

Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is committed to providing reasonable accommodations ...

Meta

Research Engineer, Monetization AI

New York, NY

$154K/yr

Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is committed to providing reasonable accommodations ...

Meta

Production Engineering

New York, NY

$154K/yr

Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is committed to providing reasonable accommodations ...

Meta

Data Center Site Selection Manager

New York, NY

$170K/yr

Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is committed to providing reasonable accommodations ...

Meta

Client Partner, Retail

New York, NY

$177K/yr

Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is committed to providing reasonable accommodations ...

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Temporary Meta Machine Learning information

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How much do temporary meta machine learning jobs pay per hour?

As of Jun 24, 2026, the average hourly pay for temporary meta machine learning in Edison, NJ is $23.63, according to ZipRecruiter salary data. Most workers in this role earn between $20.38 and $26.39 per hour, depending on experience, location, and employer.

What are some common challenges faced by professionals in temporary machine learning roles at Meta, and how can they be addressed?

Professionals in temporary machine learning roles at Meta often encounter challenges such as quickly acclimating to complex codebases, integrating with established teams, and delivering impactful results within a limited timeframe. Success in these roles typically requires strong technical skills, adaptability, and effective communication. Proactively seeking guidance, leveraging available documentation, and collaborating closely with permanent team members can help overcome these hurdles and maximize contributions during the temporary assignment.

What is the difference between Temporary Meta Machine Learning vs Data Scientist?

AspectTemporary Meta Machine LearningData Scientist
CredentialsTypically requires a background in computer science, statistics, or related fields; certifications in machine learning or data analysis are commonRequires a degree in computer science, statistics, or related fields; certifications like Certified Data Scientist are advantageous
Work EnvironmentProject-based, often contract roles within tech companies, startups, or consulting firmsFull-time or contract roles in various industries including finance, healthcare, and tech
Industry UsagePrimarily in tech, AI, and machine learning-focused companiesWidely used across multiple industries including finance, healthcare, marketing, and tech

Temporary Meta Machine Learning roles focus on short-term projects involving machine learning model development and deployment, often requiring specialized technical skills. Data Scientist roles are broader, encompassing data analysis, statistical modeling, and insights generation across diverse industries. While both roles require strong analytical skills and technical knowledge, Temporary Meta Machine Learning positions are more specialized in AI and machine learning applications.

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

To thrive as a Temporary Meta Machine Learning Engineer, you need a strong background in computer science, statistics, and machine learning, typically with experience in Python and relevant ML frameworks. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms, and version control systems is often required, along with a proven ability to rapidly learn new technologies. Strong problem-solving skills, adaptability, and effective communication are essential for collaborating within dynamic teams and meeting project goals on tight timelines. These skills ensure that you can quickly contribute to impactful ML projects, deliver results efficiently, and integrate well into fast-paced, innovative environments.

What are Temporary Meta Machine Learning jobs?

Temporary Meta Machine Learning jobs are short-term positions at Meta (formerly Facebook) that focus on developing, deploying, or researching machine learning models and technologies. These roles may support ongoing projects, fill gaps during employee leave, or address spikes in workload. Responsibilities can include data preprocessing, model training, evaluation, and collaborating with cross-functional teams. Temporary roles often give candidates exposure to Meta's cutting-edge AI tools and processes, and may sometimes lead to permanent opportunities.
Temporary Meta Machine Learning jobs near you
Infographic showing various Temporary Meta Machine Learning job openings in Edison, NJ as of June 2026, with employment types broken down into 2% Locum Tenens, 89% Full Time, 5% Temporary, 2% Contract, and 2% Nights. Highlights an 75% Physical, 9% Hybrid, and 16% Remote job distribution, with an average salary of $49,141 per year, or $23.6 per hour.

Machine Learning Scientist - Natural Language Processing (NLP) - Senior Associate - Machine Learn...

JPMorganChase

Manhattan, NY • On-site

$65K - $65K/yr

Full-time

Posted 18 days ago

Job description

Job Summary:
JPMorgan Chase is a leading global financial institution that invests heavily in innovation and technology. They are seeking a Machine Learning Scientist – Natural Language Processing (NLP) - Senior Associate to develop and deploy machine learning solutions, particularly in Generative AI, while collaborating across various business units to drive transformational change.
Responsibilities:
• Research and develop state-of-the-art machine learning models to solve real-world problems and apply them to tasks involving Generative AI (GenAI)
• Act as a thought partner for JPMC leaders and help the business identify and implement new machine learning methods that deliver impact
• Drive cross-functional collaboration with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy, and Business Management to deploy solutions into production
• Lead firm-wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business
Qualifications:
Required:
• PhD in a quantitative discipline, e.g., Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science, OR an MS with at least 2 years of industry or research experience in the field
• Solid background in Generative AI (GenAI) and hands-on experience and solid understanding of machine learning and deep learning methods and toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
• Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
• Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
• Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences
Preferred:
• Strong background in Mathematics and Statistics; Familiarity with the financial services industries and continuous integration models and unit test development
• Knowledge in search/ranking or Meta Learning
• Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large-scale distributed environment, and ability to develop and debug production-quality code
• Published research in areas of Machine Learning or Deep Learning at a major conference or journal
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.

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