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Temporary Meta Machine Learning Jobs in Texas (NOW HIRING)

Tihinsurance

Machine Learning Engineer

Dallas, TX · On-site

Regular or Temporary: Regular Language Fluency: English (Required) Work Shift: 1st Shift (United States of America) Please review the following We are building the foundation of the machine learning ...

Meta

Manager, Technical Accounting and Policy

Austin, TX · On-site +1

$173K/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

Director of Strategic Projects

Austin, TX · On-site

$246K/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

Austin, TX

$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

Associate General Counsel, Commercial

Austin, TX · On-site +1

$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

ASIC Engineer, Design Verification

Austin, TX · On-site +1

$178K/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 Analyst, Global Operations

Austin, TX

$125K/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

Critical Facility Engineer

Temple, TX · On-site

$104K/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

Network Engineer, Optical Deployment

Temple, TX · On-site

$135K/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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All JobsMeta Machine Learning JobsTemporary Meta Machine Learning JobsTemporary Meta Machine Learning Jobs in Texas

Temporary Meta Machine Learning information

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.

What are the most commonly searched types of Meta Machine Learning jobs in Texas?

The most popular types of Meta Machine Learning jobs in Texas are:

What are popular job titles related to Temporary Meta Machine Learning jobs in Texas?

For Temporary Meta Machine Learning jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Temporary Meta Machine Learning jobs in Texas look for?

The top searched job categories for Temporary Meta Machine Learning jobs in Texas are:

What cities in Texas are hiring for Temporary Meta Machine Learning jobs?

Cities in Texas with the most Temporary Meta Machine Learning job openings:

Temporary Meta Machine Learning jobs near you

Executive Director, Machine Learning & Gen AI Platforms (Home Lending)

Plano, TX • On-site

JPMorgan Chase & Co.
Finance and Insurance • 10K+ employees
Learn more about JPMorgan Chase & Co.external

Full-time

Medical, Retirement

Re-posted 5 days ago

JPMorgan Chase & Co. rating

7.9

Company rating: 7.9 out of 10

Based on 500 frontline employees who took The Breakroom Quiz

Job description


Join a team where your ideas move from experimentation to production at enterprise scale. You'll help shape how we build, govern, and operate modern AI platforms-working with partners across product and engineering to deliver durable, secure, and high-performing capabilities that improve customer and business outcomes.
As an Executive Director at JPMorganChase within Consumer and Community Banking on the Home Lending Architecture team, you will lead innovation across machine learning platforms, Generative AI platforms, and Home Lending data platform architecture. You will work closely with product owners and software engineering teams to design end-to-end solutions, guide technical decisions, and turn prototypes into production-ready platforms. You'll also mentor other AI engineers and help build a culture of continuous learning and architecture evolution.
Job responsibilities
  • Own and champion architecture solutions across data platforms, machine learning platforms, and Generative AI platform capabilities
  • Partner with engineering teams to provide hands-on solution design support and enable reliable implementation of processes and procedures
  • Represent product areas in architecture governance forums, driving accountability for code-level decisions, control obligations, cost of ownership, maintainability, and operational outcomes
  • Evaluate current technology and lead assessments of new technologies using established standards and frameworks
  • Serve as a subject matter expert across a wide range of machine learning techniques and optimizations, including distributed deployment, training, and serving
  • Design and implement Generative AI workflows using large language models, including evaluation methods and feedback loops for model and pipeline improvement
  • Translate experimental results into production-ready solutions by collaborating closely with engineering teams across the delivery lifecycle
  • Improve accuracy, latency, and reliability by identifying bottlenecks and driving performance and scalability optimizations
  • Collaborate with product and engineering to deliver tailored, science- and technology-driven solutions that meet clear business needs
  • Influence product design and technical operating models by advocating for leading-edge technologies and practical, secure adoption patterns

Required qualifications, capabilities and skills
  • Formal training or certification on data architecture concepts and 10+ years of applied experience
  • 10+ years of experience leading technologists to anticipate, manage, and solve complex technical challenges
  • Advanced proficiency in one or more programming languages (Python, Java, or C/C++), with intermediate Python required
  • Hands-on experience with system design, application development, testing, and operational stability in production environments
  • Advanced knowledge of software architecture and technical processes, including significant depth in cloud and machine learning technologies
  • Hands-on experience with machine learning techniques, including natural language processing, large language models, and deep learning frameworks (such as PyTorch or TensorFlow)
  • Applied experience in areas such as GPU optimization, fine-tuning, embedding models, inference optimization, prompt engineering, evaluation, and retrieval-augmented generation
  • Practical cloud-native experience, especially with Amazon Web Services
  • Experience with data engineering patterns and tools, including streaming, extract-transform-load or extract-load-transform pipelines, and analytics tooling
  • Ability to independently drive design and delivery from ideation through implementation
  • Strong communication skills and leadership presence, with the ability to partner effectively across engineering, product, and machine learning practitioners

Preferred qualifications, capabilities and skills
  • Experience with distributed training frameworks and experiment tracking tools (such as Ray and MLflow)
  • Experience with embedding-based search and ranking, recommender systems, graph-based methods, or related advanced approaches
  • Knowledge of reinforcement learning or meta-learning methods
  • Deep understanding of large language model techniques such as agentic workflows, planning, and reasoning approaches
  • Experience building and deploying machine learning solutions on Amazon Web Services using managed training and container orchestration services
  • Familiarity with modern data publishing and consumption patterns across teams and platforms
  • Proficiency with data architecture toolsets such as data modeling tools and cloud-based data platforms

About Us
Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans
About the Team
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.
The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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