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Temporary Meta Machine Learning Jobs in California

Meta Product Managers work with cross-functional teams of engineers, designers, data scientists and ... Product Manager, Machine Learning Responsibilities: * Display strong leadership, organizational and ...

Meta Product Managers work with cross-functional teams of engineers, designers, data scientists and ... Product Manager, Machine Learning Responsibilities: * Display strong leadership, organizational and ...

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 ...

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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:
Machine Learning Hardware Architect - Silicon

Machine Learning Hardware Architect - Silicon

Meta

Sunnyvale, CA

$212K/yr

Full-time

Posted 15 days ago


Meta rating

7.5

Company rating: 7.5 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

136th of 209 rated software companies


Job description

Meta’s mission is to give people the power to build community and bring the world closer together. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities — we're just getting started.Reality Labs (RL) focuses on delivering Meta's vision through Virtual Reality (VR) and Augmented Reality (AR). The compute performance and power efficiency requirements of Virtual and Augmented Reality require custom silicon. Reality Labs 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 & VR devices where our real and virtual world will mix and match throughout the day. We believe the only way to achieve our goals is to look at the entire stack, from transistors, through architecture, firmware, and algorithms. In this position you will work with Machine Learning Hardware Architects, Digital Designers, and Software engineers to develop custom Machine Learning Hardware accelerators for delivery into multiple SoCs. You will collaborate with a world-class group of researchers and architects to implement and contribute to the development and optimization of low power machine learning accelerators and state-of-the-art SoCs.
Machine Learning Hardware Architect - Silicon Responsibilities:
  • Technical lead for ML Hardware engineers, driving design from Architecture through to Product for AR/VR optimized silicon
  • Lead designs to surpass state of the art for metrics such as compute, bandwidth, and power consumption
  • Work across disciplines, brainstorm big ideas, work in new technology areas, juggle/coordinate multiple initiatives, drive a concept into a prototype and ultimately guide the transition into a high-volume consumer product
  • Travel both domestically and internationally

Minimum Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 12+ years of experience as a Hardware Design Engineer or Silicon Architect for production silicon shipped in volume
  • Experience in Machine Learning IPs Silicon development
  • Experience in digital design µArchitecture, RTL coding
  • Experience with methods for partitioning a solution across hardware and software, evaluating trade-offs such as speed, performance, power, area
  • Results oriented, proactive with demonstrated creative & critical thinking

Preferred Qualifications:
  • Master/PhD degree in EE/CS or equivalent areas
  • Knowledge of Physical Design and Low power implementation
  • Experience with Firmware, DSP coding and optimization
  • Collaborate and/or lead in a team environment
  • Experience with SoC Architecture and subsystem Integration
  • Knowledge of industry trends and disruptive technologies
  • Experience in deep learning algorithms and techniques, e.g., convolutional neural networks, transformers, LLMs

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.
$212,000/year to $294,000/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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