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Freelance Machine Learning Compiler Engineer Jobs in Virginia

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly Salary: Competitive We are seeking a highly skilled and motivated Machine Learning Engineer to join ...

GCP/AWS Machine Learning Engineer Freddie Mac iLab is currently looking for Machine Learning Engineers in its Innovation Labs - Tech Strategy team. In this position, you will be responsible for ...

The Machine Learning Engineer will leverage their strong technical background and knowledge to support highly scalable machine learning-based applications, including both pipelines and services ...

Machine Learning Engineer II The Machine Learning Engineer II will be a member of the Learning and Active Perception (LEAP) group in AV's MacCready Works division and support the development of a ...

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

SW Engineer Schedule: Full-Time Shift: Day Job Travel: Yes - 10% of the time Minimum Clearance ... The Machine Learning Developer will collaborate with software engineers to create innovative ML/AI ...

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative ...

Machine Learning Engineer LOCATIONTysons, VA 22182 CLEARANCETS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARYWe are seeking a talented and innovative Machine ...

Machine Learning Engineer LOCATIONChantilly, VA 20151 CLEARANCETS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARYWe are seeking a talented and innovative Machine ...

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

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Freelance Machine Learning Compiler Engineer information

What is the difference between Freelance Machine Learning Compiler Engineer vs Freelance Software Developer?

AspectFreelance Machine Learning Compiler EngineerFreelance Software Developer
Required SkillsMachine learning frameworks, compiler optimization, programming (C++, Python)General programming, software design, various languages
Work EnvironmentProject-based, remote, often technical teams in AI/ML industryVaried industries, remote or on-site, broad application areas
Industry UsageAI/ML companies, research labs, tech firmsTech, finance, healthcare, startups, enterprise

Freelance Machine Learning Compiler Engineers focus on optimizing ML models for deployment, requiring specialized knowledge in ML frameworks and compiler technology. Freelance Software Developers have broader roles across various industries, working on diverse software projects. Both roles are in high demand but differ in technical focus and industry application.

What are the most commonly searched types of Machine Learning Compiler Engineer jobs in Virginia? The most popular types of Machine Learning Compiler Engineer jobs in Virginia are:
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What cities in Virginia are hiring for Freelance Machine Learning Compiler Engineer jobs? Cities in Virginia with the most Freelance Machine Learning Compiler Engineer job openings:

Machine Learning Engineer

Full Scope

Reston, VA

Other

Posted 3 days ago


Job description

Job Title:Machine Learning Engineer
Location:Fort Meade, MD
Required Clearance: TS/SCI w/ Full-Scope Poly
Salary:Competitive
We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team. The ideal candidate will have a strong background in machine learning, data science, and software engineering. You will work closely with data scientists, engineers, and product managers to design, develop, and deploy machine learning models and solutions that drive business value.
Key Responsibilities:
  • Design, develop, and implement machine learning models and algorithms to solve real-world problems.
  • Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
  • Conduct data analysis and preprocessing to ensure high-quality data for model training.
  • Optimize and fine-tune models for performance, accuracy, and scalability.
  • Deploy machine learning models into production and monitor their performance.
  • Develop and maintain machine learning pipelines and infrastructure.
  • Stay current with the latest research and advancements in machine learning and AI.
  • Participate in code reviews, team meetings, and contribute to a collaborative development environment.
  • Document processes, models, and findings comprehensively.
Qualifications:
  • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field. Ph.D. is a plus.
  • Proven experience as a Machine Learning Engineer or in a similar role.
  • Strong proficiency in programming languages such as Python, R, or Java.
  • Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
  • Solid understanding of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and deep learning.
  • Experience with data processing tools like Pandas, NumPy, and data visualization tools such as Matplotlib or Seaborn.
  • Familiarity with cloud platforms like AWS, Google Cloud, or Azure for model deployment and scaling.
  • Strong problem-solving skills and the ability to think critically and analytically.
  • Excellent communication and teamwork skills.
Preferred Qualifications:
  • Experience with natural language processing (NLP) and computer vision.
  • Familiarity with big data technologies such as Hadoop, Spark, or Kafka.
  • Knowledge of software development best practices and version control systems like Git.
  • Experience with containerization tools like Docker and orchestration tools like Kubernetes.
  • Previous experience in a fast-paced, startup environment.