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Machine Learning Engineer Apprenticeship Jobs in Washington

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 ...

Machine Learning Engineer Role Summary: The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main ...

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 ...

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

Machine Learning Engineer Our client, a financial company, is looking for a Machine Learning Engineer for their McLean, VA location. Requirements: * Python, AWS, Kubernetes, Kubeflow, MLOps, ML ...

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

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Machine Learning Engineer Apprenticeship information

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

To thrive as a Machine Learning Engineer Apprentice, a solid understanding of mathematics, programming (especially Python), and foundational machine learning concepts is essential, often supported by coursework or a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is typically required. Strong analytical thinking, attention to detail, and the ability to collaborate and communicate complex ideas clearly are valuable soft skills. These abilities are crucial for efficiently developing, testing, and deploying machine learning models while contributing effectively to team projects.

What types of projects can I expect to work on during a Machine Learning Engineer Apprenticeship?

As a Machine Learning Engineer Apprentice, you can expect to participate in hands-on projects that involve data preprocessing, building and evaluating machine learning models, and collaborating with cross-functional teams such as data scientists and software engineers. Common projects may include developing recommendation systems, automating data analysis tasks, or implementing natural language processing solutions. These experiences provide valuable exposure to real-world datasets and industry-standard tools, helping you build foundational skills for a long-term career in machine learning.

What is a Machine Learning Engineer Apprenticeship?

A Machine Learning Engineer Apprenticeship is a structured training program that combines hands-on work experience with classroom or online learning in the field of machine learning. Apprentices work under the guidance of experienced professionals to develop skills in data analysis, building machine learning models, and deploying algorithms in real-world applications. This apprenticeship is ideal for individuals seeking to enter the field of artificial intelligence without prior extensive experience, as it provides practical training and mentorship. Typically, apprenticeships last from several months to a couple of years and may lead to full-time employment upon successful completion.
What are popular job titles related to Machine Learning Engineer Apprenticeship jobs in Washington? For Machine Learning Engineer Apprenticeship jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Apprenticeship jobs in Washington look for? The top searched job categories for Machine Learning Engineer Apprenticeship jobs in Washington are:
What cities in Washington are hiring for Machine Learning Engineer Apprenticeship jobs? Cities in Washington with the most Machine Learning Engineer Apprenticeship job openings:

Machine Learning Engineer

Full Scope

Reston, VA

Other

Posted 12 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.