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Temporary Meta Machine Learning Jobs (NOW HIRING)

Our team has built SW, ML, and HW products across Meta, CTRL-labs, Google, Apple, Fitbit, Peloton ... RESPONSIBILITIES This role involves developing software and machine learning algorithms for use in ...

Description Quantum Machines (QM) is a global leader in quantum computing control systems. Through ... Experience with sim-to-real, multi-objective RL, or meta-learning- advantage

Meta is seeking talented experienced engineers to join our teams in building cutting-edge products ... Software Engineer, Machine Learning Responsibilities: * Collaborate with cross-functional teams ...

Meta is seeking talented experienced engineers to join our teams in building cutting-edge products ... Software Engineer, Machine Learning Responsibilities: * Collaborate with cross-functional teams ...

Meta is seeking talented experienced engineers to join our teams in building cutting-edge products ... Software Engineer, Machine Learning Responsibilities: * Collaborate with cross-functional teams ...

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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 Sep 3, 2026, the average hourly pay for temporary meta machine learning in the United States is $22.82, according to ZipRecruiter salary data. Most workers in this role earn between $19.71 and $25.48 per hour, depending on experience, location, and employer.

What is a temporary Meta machine learning job?

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.

What are the key skills and qualifications needed to thrive as a temporary Meta machine learning engineer?

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 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.

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Infographic showing various Temporary Meta Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $47,468 per year, or $22.8 per hour.

Machine Learning Digital Design Engineer

Meta

Sunnyvale, CA

$178K/yr

Full-time

Re-posted 21 days ago


Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

138th of 247 rated software companies


Job description

Meta is seeking highly skilled Design Engineers to join our team. In this role, you will contribute to the development of advanced technology solutions, including machine learning and network acceleration. You will collaborate with researchers and engineers to design, implement, and optimize low-power hardware accelerators, state-of-the-art SoCs, and custom silicon solutions that enable the next generation of innovative devices and hardware.
Machine Learning Digital Design Engineer Responsibilities:
  • Contribute to ASIC digital µArchitecture and design
  • Assist performance/power analysis of the design and help meet power and performance targets
  • Work with architects to map algorithms onto the hardware and specify requirements for IP and subsystems integration
  • Collaborate with adjacent teams such as Verification, Physical Design, and Design-for-Test
  • Develop micro-architecture, RTL coding, and design verification for complex IPs
  • Drive IP/sub-system micro-architecture and RTL design in collaboration with DV and PD leads

Minimum Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 8+ years of experience as a Hardware Design Engineer for production silicon shipped in volume
  • Experience in digital design µArchitecture, RTL coding, and micro-architecture development
  • Experience communicating technical design decisions and trade-offs to cross-functional partners such as verification, physical design, and architecture teams

Preferred Qualifications:
  • Experience in ML accelerator subsystems and top level design
  • Experience in SoC integration and ASIC architecture
  • Knowledge of microcontrollers, DSP, CDC and power sequence
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. 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 for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$178,000/year to $250,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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