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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:
Temporary Meta Machine Learning jobs near you
Principal AI Engineer - Evinova

Principal AI Engineer - Evinova

AstraZeneca

Gaithersburg, MD • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 4 days ago

AstraZeneca rating

8.4

Company rating: 8.4 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

15th of 74 rated pharmaceutical

Job description

WHY JOIN US?
Evinova is a health-tech business focused on accelerating better health outcomes by advancing digital transformation across the life sciences sector. By combining science-based expertise, evidence-led rigor, and deep human insight, we design digital solutions that enable healthcare to work better for everyone.
Operating at the intersection of healthcare, technology, data, and analytics, we are helping unlock the full potential of digital health, transforming how clinical research is conducted, how care is delivered, and how patients experience healthcare. Our solutions are built to scale, driving efficiency, improving decision-making, and ultimately delivering better outcomes for patients worldwide.
At Evinova, we are driven by a shared purpose to transform health through data and digital innovation. Our teams collaborate across disciplines to solve complex challenges, continuously learning and evolving in a fast-paced, high-impact environment.
We also recognize the importance of flexibility and balance. Our ways of working support both individual needs and team collaboration. To foster connection and collaboration, employees are expected to work from the office three days per week, creating opportunities for in-person teamwork, innovation, and meaningful connection.
Introduction to Role:
As Principal AI Engineer, you'll design and implement sophisticated agentic AI systems that power next-generation life sciences solutions. Working at the intersection of AI research and real-world healthcare applications, you'll build intelligent agents that can reason, plan, and act autonomously to solve complex clinical challenges.
What makes this role compelling:
  • Lead challenging projects in agentic AI, LLM orchestration, and multi-agent systems
  • Build AI agents that directly impact clinical trials, drug discovery, and ultimately patient care
  • Collaborate with product teams, clinical experts, and ML engineers in a fast-paced environment
  • Develop automated evaluation systems, prompt optimization techniques, and advanced agent architectures
  • Contribute to the AI in life sciences community through publications, conferences, and open-source work

Example impactful projects include: Intelligent AI agents for clinical document generation, advanced search systems for medical research, clinical trial optimization tools, synthetic patient data generation, and multi-modal healthcare AI assistants.
Accountabilities:
  • Design Advanced AI Systems
    • Build and deploy sophisticated agentic AI solutions using state-of-the-art LLMs
    • Develop novel approaches to agent memory, tool use, and multi-agent collaboration
    • Build sophisticated NLP systems for retrieval, information extraction, structured generation, graph reasoning.
  • Drive Technical Innovation
    • Create automated techniques for agent design, evaluation, and optimization
    • Systematically discover and validate effective prompt engineering approaches for agentic systems
    • Build specialized observability pipelines for continuous model and agent performance monitoring
  • Lead Cross-Functional Collaboration
    • Partner with product, design, and clinical teams to translate AI capabilities into impactful healthcare solutions
    • Mentor engineers and contribute to AI strategy across the organization
  • Contribute to the Field
    • Share expertise at conferences and through technical publications
    • Contribute to open-source projects and help advance best practices in healthcare AI

Essential Skills/Experience:
  • Master's Degree in a relevant field (such as mathematics, computer science, data science).
  • 4+ years of industry experience in applied machine learning, with a strong focus on deep learning, NLP, and generative AI.
  • Extensive prior experience exploring and testing language model behavior, prompting and building products with language models.
  • Expert knowledge of Python and advanced ML/LLM frameworks (e.g., TensorFlow, PyTorch, Google ADK, Crewai, LangChain, LlamaIndex)
  • Extensive experience with AWS services (e.g. SageMaker, Bedrock, MSK, EKS, ECS, OpenSearch).
  • Deep understanding of agentic AI systems and frameworks (e.g. agentic design patterns, multi-agent systems, reinforcement learning).
  • Excellent communication skills with the ability to articulate complex technical concepts to both technical and non-technical audiences

Desirable Skills/Experience:
  • Ph.D. in a relevant field (such as mathematics, computer science, data science).
  • Demonstrated technical leadership experience, including successful delivery of large-scale AI projects.
  • Experience developing complex agentic systems using LLMs.
  • Experience with low-level languages used for implementing high-performance ML code (C/C++, Rust, CUDA, etc.)
  • Contributions to open-source AI projects or development of proprietary AI frameworks.
  • Expertise in areas such as few-shot learning, meta-learning, explainable AI.
  • Experience with AI ethics, responsible AI practices, and navigating regulatory landscapes for AI deployment in the life science industry.

SO, WHAT'S NEXT?
To be considered for this exciting opportunity, please complete the full application on our website at your earliest convenience - it is the only way that our Recruiter and Hiring Manager can know that you feel well qualified for this opportunity. If you know someone who would be a great fit, please share this posting with them.
Where can I find out more?
  • Explore what we're building: www.evinova.com
  • Stay connected and see our impact in action: https://www.linkedin.com/company/evinova/

Apply today to bring smarter, faster clinical trials to life!
Evinova is an equal opportunity employer that is committed to diversity and inclusion and providing a workplace that is free from discrimination. Evinova is committed to accommodating persons with disabilities. Such accommodation is available on request in respect of all aspects of the recruitment, assessment and selection process and may be requested by emailing AZCHumanResources@astrazeneca.com.
#LI-Hybrid
The annual base pay for this position ranges from $144,648.80 - $189,851.55 USD. Base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience.
In addition, our positions offer a short-term incentive bonus opportunity; eligibility to participate in our equity-based long-term incentive program. Benefits offered included a qualified retirement program [401(k) plan]; paid vacation and holidays; paid leaves; and, health benefits including medical, prescription drug, dental, and vision coverage in accordance with the terms and conditions of the applicable plans.
Additional details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, employee will be in an "at-will position" and the Company reserves the right to modify base pay (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.
Date Posted
20-Jul-2026
Closing Date
06-Aug-2026
Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.

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