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Temporary Meta Machine Learning Jobs in California

Krea

Machine Learning Engineer

San Francisco, CA

Machine Learning Engineer At Krea, we are building next-generation AI creative tools. We are ... Meta AI Research laboratory (FMK as Facebook AI Research) or founding members of OpenAI.

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine ... Fine-tune large language models (LLMs) and implement meta-learning methods to enhance model ...

Nace AI

Machine Learning Engineer

Palo Alto, CA

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine ... Fine-tune large language models (LLMs) and implement meta-learning methods to enhance model ...

Meta

Research Engineer, MRS AI

Menlo Park, CA

$121K/yr

Degree must be completed prior to joining Meta * Research experience in machine learning, deep learning, and/or recommender systems, natural language processing * Programming experience in Python and ...

Meta

Fundamental AI Researcher - FAIR

Menlo Park, CA

$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

Research Engineer, Monetization AI

Sunnyvale, CA

$183K/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

Menlo Park, CA

$183K/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

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.
What are the most commonly searched types of Meta Machine Learning jobs in California? The most popular types of Meta Machine Learning jobs in California are:
What are popular job titles related to Temporary Meta Machine Learning jobs in California? For Temporary Meta Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Temporary Meta Machine Learning jobs in California look for? The top searched job categories for Temporary Meta Machine Learning jobs in California are:
What cities in California are hiring for Temporary Meta Machine Learning jobs? Cities in California with the most Temporary Meta Machine Learning job openings:
Temporary Meta Machine Learning jobs near you
Design Verification Engineer - Machine Learning Accelerators

Design Verification Engineer - Machine Learning Accelerators

Meta

Sunnyvale, CA

$178K/yr

Full-time

Posted 8 days ago

Meta rating

7.5

Company rating: 7.5 out of 10

Based on 43 frontline employees who took The Breakroom Quiz

123rd of 191 rated software companies

Job description

Reality Labs focuses on delivering Meta's vision through Augmented Reality (AR) and Smart Devices. Compute power requirements of these devices require custom silicon. Meta’s Silicon team is driving the state of the art forward with breakthrough work in computer vision, machine learning, mixed reality, graphics, displays, sensors, and new ways to map the human body. Our chips will enable AR devices where our real and virtual world will mix and match throughout the day, and smart devices that provide assistance and enhanced capabilities in our day-to-day activities. We believe the only way to achieve our goals is to look at the entire stack, through algorithms to architecture, transistors to firmware. As a Design Verification Engineer at Meta’s Reality Labs, you will work with a multidisciplinary group of researchers and engineers, and use your digital design and verifications skills to implement the testing infrastructure to validate new core IP implementations and contribute to development and optimization of state of the art machine learning algorithms. You will work closely with researchers, architects and designers in creating test bench requirements and test cases for multiple state of the art machine learning IPs.
Design Verification Engineer - Machine Learning Accelerators Responsibilities:
  • Work with cross-functional leads, including product managers, systems architects, researchers, and software architects, to develop industry leading Machine Learning IP’s optimized for Mixed Reality and Smart Devices and use-cases, defining verification methodologies for each of the different core IPs
  • Define, track, and lead the execution of detailed test plans for the different modules and top levels
  • Implement scalable test benches including checkers, reference models, assertions in System Verilog
  • Drive Design Verification to closure based on defined verification metrics on test plan, functional and code coverage
  • Collaborate with cross-functional teams such as Design, Model, Emulation and Silicon validation teams towards ensuring design quality targets are met across pre- and post-Silicon product lifecycle
  • Support hand-off and integration of developed subsystems/IP blocks into larger SOC environments
  • Develop and drive continuous Design Verification improvements using the latest verification methodologies, tools and technologies from the industry

Minimum Qualifications:
  • 10+ years of hands-on experience in SystemVerilog/UVM methodology and C/C++ based verification
  • 10+ years of experience in IP/sub-system and/or SoC level verification based on SystemVerilog UVM/OVM based methodologies
  • Experience in one or more of the following areas along with functional verification - SV Assertions, Formal, Emulation
  • Experience in EDA tools and scripting (Python, TCL, Perl, Shell) used to build tools and flows for verification environments
  • Track record of 'first-pass success' in ASIC development cycles
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

Preferred Qualifications:
  • Masters in Electrical Engineering or Computer Science
  • 5+ years of experience with Design verification/validation of machine learning applications and accelerators
  • 5+ years of experience with Software/Hardware Co-design at firmware, ISA, and application level
  • 5+ years of experience with low power design
  • 5+ years of experience in verification of numerical compute based designs
  • Experience with revision control systems like Mercurial(Hg), Git
  • FPGA/emulation debug experience

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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