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Freelance Google Machine Learning Engineer Jobs in Virginia

Full Scope

Machine Learning Engineer

Reston, VA

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly ... Familiarity with cloud platforms like AWS, Google Cloud, or Azure for model deployment and scaling.

Cymertek

Machine Learning Engineer

Reston, VA

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Cymertek

Machine Learning Engineer

Chantilly, VA

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Cymertek

Machine Learning Engineer

Tysons, VA

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Booz Allen Hamilton

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

R0242766 Machine Learning Engineer The Opportunity: As an experienced AI and ML engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to ...

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Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Booz Allen Hamilton

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

R0242757 Machine Learning Engineer The Opportunity: As an experienced AI and ML engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to ...

New

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Freelance Google Machine Learning Engineer information

What are the key skills and qualifications needed to thrive as a Freelance Google Machine Learning Engineer, and why are they important?

To thrive as a Freelance Google Machine Learning Engineer, you need a solid background in computer science, statistics, and machine learning, typically supported by a relevant degree and experience with real-world data projects. Familiarity with Google Cloud Platform (GCP), TensorFlow, and certifications like Google Professional Machine Learning Engineer are commonly required. Strong problem-solving abilities, self-motivation, and effective client communication distinguish top freelancers in this field. These skills and qualifications are crucial for delivering robust machine learning solutions tailored to client needs and efficiently navigating remote, project-based work.

What does a Freelance Google Machine Learning Engineer do?

A Freelance Google Machine Learning Engineer is a technical specialist who designs, develops, and deploys machine learning models using Google’s tools and platforms, such as TensorFlow and Google Cloud AI services. They work independently or with clients to solve data-driven problems, build predictive models, and automate processes using machine learning techniques. Their responsibilities may include data preprocessing, feature engineering, model training and evaluation, and integrating models into production systems. Freelancers often manage multiple projects and must stay updated on the latest ML advancements and Google technologies.

What are some common challenges freelance Google Machine Learning Engineers face when working with clients remotely?

Freelance Google Machine Learning Engineers often encounter challenges such as clearly defining project scopes, aligning on deliverables, and managing expectations, especially when working remotely. Communication can be more complex due to time zone differences and varying levels of technical understanding among clients. Staying updated with Google’s latest ML tools and ensuring secure, efficient data sharing are also important. Building strong documentation and regular progress updates can help foster trust and smooth collaboration.

What is the difference between Freelance Google Machine Learning Engineer vs Freelance Data Scientist?

AspectFreelance Google Machine Learning EngineerFreelance Data Scientist
CredentialsKnowledge of Google Cloud ML tools, programming skills in Python, TensorFlowStatistical expertise, programming in Python/R, data analysis skills
Work EnvironmentCloud platforms, AI/ML projects, collaboration with developersData analysis, reporting, model development, client communication
Industry UsageTech companies, AI startups, cloud service providersFinance, healthcare, marketing, research organizations

While both roles involve working with data and models, a Freelance Google Machine Learning Engineer specializes in deploying ML solutions on Google Cloud, focusing on AI/ML engineering tasks. A Freelance Data Scientist primarily analyzes data, builds statistical models, and provides insights. The roles overlap in skills but differ in focus and tools used.

What are the most commonly searched types of Google Machine Learning Engineer jobs in Virginia? The most popular types of Google Machine Learning Engineer jobs in Virginia are:
What are popular job titles related to Freelance Google Machine Learning Engineer jobs in Virginia? For Freelance Google Machine Learning Engineer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Freelance Google Machine Learning Engineer jobs in Virginia look for? The top searched job categories for Freelance Google Machine Learning Engineer jobs in Virginia are:
What cities in Virginia are hiring for Freelance Google Machine Learning Engineer jobs? Cities in Virginia with the most Freelance Google Machine Learning Engineer job openings:
Freelance Google Machine Learning Engineer jobs near you

Machine Learning Engineer

Full Scope

Reston, VA

Other

Posted 10 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.

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