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Temporary Meta Machine Learning Jobs in Washington

Junior Machinist

Lanham, MD ยท On-site

$26 - $36/hr

This is a temporary 3-month training position designed for individuals looking to start a career in ... The Junior Machinist will be exposed to learning the following responsibilities: * Review samples ...

Certified Scrum Master (CSM) or formal training in AI, machine learning, or advanced business ... Travel: May be required up to 25% of the time to CONUS locations for temporary duty (TDY)

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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 Washington? The most popular types of Meta Machine Learning jobs in Washington are:
What are popular job titles related to Temporary Meta Machine Learning jobs in Washington? For Temporary Meta Machine Learning jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Temporary Meta Machine Learning jobs in Washington look for? The top searched job categories for Temporary Meta Machine Learning jobs in Washington are:
What cities in Washington are hiring for Temporary Meta Machine Learning jobs? Cities in Washington with the most Temporary Meta Machine Learning job openings:
Data Engineer and Analyst

Data Engineer and Analyst

DevTech Systems, Inc.

Washington, DC โ€ข Remote

Full-time

Posted 14 days ago


Job description

Salary:

DevTech is a mission-driven firm specializing in innovative, data-driven solutions that help governments, civil society, and the private sector strengthen public financial systems, unlock investment, and make informed decisions in complex environments. We combine advanced analytics, contextual insight, and blended finance strategies to deliver practical, forward-looking solutions worldwide. Guided by our core values of integrity, innovation, evidence-driven impact, resilience, and collaboration, DevTech works transparently and in close partnership with clients and communities to achieve measurable results and lasting impact.


DevTech is looking for a Data Engineer and Analyst to work as an institutional contractor on its Analytics, Data, Visualization, and Information Services 2.0 (ADVISE 2.0) contract with the United States Department of State. The Data Engineer and Analyst will work with the Office of Global Food Security (GFS) to support Humanitarian Assistance (HA) across the State Department. The Data Engineer and Analyst will support the Humanitarian Data, Assessment, & Coordination unit within GFS Technical Quality & Assurance Division. The Humanitarian Data, Assessment, & Coordination unit strives to create and share decision support products with humanitarian assistance decision makers to improve their understanding of humanitarian needs, internal and external humanitarian data, and to improve the quality and targeting of global humanitarian assistance in crisis settings.


Overall, we are seeking a data-savvy professional who can bridge engineering and analysis. This hybrid Data Engineer and Data Analyst role involves building and maintaining data systems, exploring and interpreting complex humanitarian datasets, and empowering colleagues to make informed, evidence-based decisions. The ideal candidate combines technical expertise with intellectual curiosity, strong analytical skills, and a passion for using data to support humanitarian outcomes.


Responsibilities are as follows:
Data Engineering & Infrastructure (60%)
Design, develop, and maintain scalable data pipelines and ETL/ELT workflows to support humanitarian operational and analytical needs.
Build and optimize data models, schemas, and cloud-based data architectures to support dashboards, machine learning workflows, and advanced analytics.
Respond quickly to database problems that arise and carry out periodic maintenance and troubleshooting. Monitor the system performance by performing regular tests, troubleshooting, and integrating new features.
Integrate heterogeneous humanitarian data sources.
Implement data quality, validation, and monitoring processes to ensure accuracy, reliability, and transparency.
Maintain an awareness of trends and developments in database maintenance.
Maintain documentation, metadata, and data governance standards in alignment with state department policies.
Occasionally, respond quickly to data needs for responses to rapid onset disasters or urgent decision-making requests.


Data Analysis, Insights, & Decision Support (40%)
Explore and analyze complex humanitarian datasets to identify trends, anomalies, risks, and opportunities.
Produce actionable insights that inform policy, resource allocation, program design, and crisis response.
Support predictive analytics or light machine-learning workflows where appropriate.
Communicate analytical findings clearly to technical and non-technical audiences.


Data Leadership, Guidance & Collaboration
Serve as a subject-matter resource for data best practices, including how to access, interpret, and apply available datasets.
Work closely with the team business analyst and HA decision makers to understand their data needs and translate them into analytical or technical solutions.
Provide training, informal guidance, and practical tools to staff who rely on data for decision-making.
Demonstrate flexibility by taking on adjacent responsibilities as needed in a small, fast moving team environment to ensure project goals are met.
Engage in continuous learning about the humanitarian sector.


General
As needed, may serve on temporary detail within the bureau to meet operational needs during staff shortages. Duties performed while on detail will be aligned with the Teams existing duties and responsibilities and will be directly related to the scope of work provided.
In compliance with the Department of State and contractor policies and procedures, consistently model behaviors that demonstrate a commitment to fostering a non-hostile work environment free of discrimination, bias, unfairness, exclusion, offensive behaviors, and harassment of any kind.
Demonstrate consistent accountability for adherence to and knowledge of laws, executive orders, and Department of States policies which prohibit Equal Employment Opportunity (EEO) and non-EEO infringements as well as the Agencys zero tolerance for sexual misconduct, including harassment, exploitation, and abuse of any kind. Understand reporting criteria and report up in a timely manner.


Requirements
Bachelors degree in Data Science, Computer Science, Statistics, Information Systems, or a related field. Masters degree or equivalent experience preferred.
Hands-on experience in both:
o Data engineering (pipelines, ETL/ELT, SQL, cloud tools)
o Data analysis (exploratory analysis, dashboarding, basic data science methods)
Proficiency with SQL and modern programming/scripting languages (Python preferred).
Familiarity with cloud platforms (e.g. AWS, Databricks) and common data engineering tools.
Strong analytical thinking, problem-solving skills, and intellectual curiosity.
Ability to explain complex concepts to diverse stakeholders.
A team player but able to work independently.
Multi-tasking and time-management skills, with the ability to prioritize tasks.
Excellent interpersonal skills.
Ability to work well in a diverse team.
The candidate must be a U.S. citizen to qualify for the required U.S. government security clearance for this project.


This positions place of performance is Washington D.C. Remote work has been authorized for this position.