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Temporary Meta Machine Learning Jobs in California

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 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 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 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 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 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:
Research Scientist, Post-Training (Tech Leadership)- Meta Superintelligence Labs

Research Scientist, Post-Training (Tech Leadership)- Meta Superintelligence Labs

Meta

Menlo Park, CA • On-site

$219K - $301K/yr

Full-time

Posted 2 days ago


Meta rating

7.5

Company rating: 7.5 out of 10

Based on 43 frontline employees who took The Breakroom Quiz

117th of 184 rated software companies


Job description

Meta is seeking Research Scientists to join the Post-Training team within Meta Superintelligence Labs (MSL). High-quality data is the core of AI progress at MSL, fueling the complex capabilities we build, how our models reason, and how they interact with the world. As a Research Scientist, you will provide the technical vision to design, generate, and curate the critical post-training data (SFT, RLHF) that aligns and enhances our frontier AI systems. You will conduct research to develop and optimize post-training recipes that directly improve model quality. This is a highly technical research role requiring sound scientific judgment, creativity, and the ability to drive ambitious research agendas with independence. The data strategies you develop will directly influence research direction and major model lines within MSL, making data quality, methodological rigor, and clear communication important. You will collaborate closely with technical leadership to ensure our data pipelines capture the most important capabilities-ranging from expert domains (STEM, GDP-valuable tasks, finance, legal, health) to advanced agentic tasks (search, Deep Research, computer use, coding, UI generation, and shopping agents). We are looking for exceptional research talent-researchers who have shaped the field of machine learning and are ready to do so again at the frontier of AI. If you are passionate about defining how we teach and align AI systems and want to shape the scientific foundations of frontier AI development, we encourage you to apply for this exciting opportunity at the core of MSL.
Responsibilities
Provide scientific leadership in designing novel methodologies for post-training data collection, curation, and synthetic data generation
• Define data quality frameworks and alignment strategies that guide capability development across MSL, particularly for complex reasoning and agentic behaviors
• Drive the scientific vision for eliciting high-quality data in expert domains (finance, legal, health, STEM) and complex agentic trajectories (Deep Research, Computer Use, UI generation)
• Conduct research to develop and optimize post-training recipes that directly improve model quality
• Partner with cross-functional research teams across product and model training to identify and prioritize gaps in model capabilities
• Lead research workstreams that shape the long-term direction of data-centric AI at MSL, working independently while also contributing to team goals and organizational priorities
Minimum Qualifications
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Ph.D. in Computer Science, Machine Learning, or a related technical field
• 5+ years of experience in machine learning research, with a focus on deep learning, data alignment, NLP, or related areas
• Demonstrated ability to lead technical research projects from conception to production
• Collaborative communication skills and experience collaborating with technical leadership
Preferred Qualifications
• Multiple first-author publications at top-tier peer-reviewed venues (NeurIPS, ICML, ICLR, ACL, EMNLP, or similar) related to language model alignment, synthetic data generation, RLHF, or deep learning
• Recognized expertise in data-centric AI, post-training methodologies, or complex reasoning data
• Track record of research that has substantially influenced the field of deep learning
• Hands-on experience with language model post-training, RLHF, DPO, or related alignment techniques
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.
Equal Employment Opportunity
Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here.

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