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Machine Learning Training Placement Jobs (NOW HIRING)

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 ...

Work with Subject Matter Experts to design appropriate machine learning model types and ... training or for any other fees • Use recruiting or placement agencies that charge candidates an ...

$28 - $45/hr

Key Responsibilities * Assist in building and training machine learning and deep learning models * Perform data preprocessing, feature engineering, and exploratory data analysis (EDA) * Implement ...

Develop efficient workflows for training, validation, and testing, incorporating distributed ... Strong understanding of fundamental machine learning algorithms and neural network techniques.

... training, optimization, and deployment Consistent track record of researching, inventing and/or shipping advanced machine learning models Outstanding communication and interpersonal skills with ...

Machine Learning Engineer 100% Remote We are seeking a highly skilled Machine Learning Engineer to ... Build and optimize end-to-end ML pipelines for data ingestion, feature engineering, model training ...

$28 - $45/hr

Key Responsibilities * Assist in building and training machine learning and deep learning models * Perform data preprocessing, feature engineering, and exploratory data analysis (EDA) * Implement ...

$28 - $45/hr

Key Responsibilities * Assist in building and training machine learning and deep learning models * Perform data preprocessing, feature engineering, and exploratory data analysis (EDA) * Implement ...

Machine Learning Engineer 100% Remote We are seeking a highly skilled Machine Learning Engineer to ... Build and optimize end-to-end ML pipelines for data ingestion, feature engineering, model training ...

Build and maintain end-to-end machine learning pipelines, including data ingestion, preprocessing, model training, deployment, and monitoring. * Evaluate and benchmark machine learning models using ...

Work with Subject Matter Expertsto design appropriate machine learning model types and ... training or for any other fees Use recruiting or placement agencies that charge candidates an ...

Health insurance Machine Learning Engineer 100% Remote We are seeking a highly skilled Machine ... Build and optimize end-to-end ML pipelines for data ingestion, feature engineering, model training ...

Health insurance Machine Learning Engineer 100% Remote We are seeking a highly skilled Machine ... Build and optimize end-to-end ML pipelines for data ingestion, feature engineering, model training ...

Design and implement Machine Learning algorithms and models into software solutions for our enterprise customers by using common machine learning frameworks, including establishing and training ...

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Machine Learning Training Placement information

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$25.5K

$42.6K

$88K

How much do machine learning training placement jobs pay per year?

As of Jun 12, 2026, the average yearly pay for machine learning training placement in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is a Machine Learning Training Placement?

A Machine Learning Training Placement is a program or opportunity designed to provide hands-on experience and practical training in machine learning concepts and techniques. These placements are often offered by companies, universities, or training institutes to help participants apply theoretical knowledge to real-world data problems. Participants may work on projects involving data preprocessing, model building, and evaluation under the guidance of experienced professionals. The goal is to prepare individuals for careers in machine learning by bridging the gap between academic study and professional work environments.

What is the difference between Machine Learning Training Placement vs Data Scientist?

AspectMachine Learning Training PlacementData Scientist
Required CredentialsBootcamps, certifications, or degree in computer science or related fieldsAdvanced degree (Master's or PhD) often preferred, with strong statistical and programming skills
Work EnvironmentInternship or entry-level training programs in tech companies or startupsFull-time roles in data analysis, modeling, and decision-making teams
Industry UsageTraining programs designed to prepare candidates for machine learning rolesApplying data analysis and modeling to solve business problems

Machine Learning Training Placement focuses on providing hands-on training and internships to prepare individuals for machine learning roles, while Data Scientist positions involve applying statistical and analytical skills to interpret data and develop models in a full-time capacity.

What are the key skills and qualifications needed to thrive in a Machine Learning Training Placement, and why are they important?

To thrive in a Machine Learning Training Placement, you need a strong background in mathematics, statistics, and programming, often supported by coursework or a degree in computer science or a related field. Familiarity with tools like Python, TensorFlow, scikit-learn, and version control systems, as well as foundational knowledge of machine learning algorithms, is typically expected. Analytical thinking, problem-solving, and effective communication are crucial soft skills for interpreting results and collaborating on projects. These competencies enable you to develop robust models, communicate findings, and contribute to data-driven solutions in real-world environments.

What types of projects or assignments can I expect during a machine learning training placement?

During a machine learning training placement, you can expect to work on a variety of hands-on projects such as data preprocessing, building and evaluating machine learning models, and participating in real-world problem-solving tasks like image or text classification. You may also contribute to collaborative group projects, attend code reviews, and present your findings to mentors or team members. This practical experience is designed to help you build a strong portfolio and develop teamwork and communication skills, which are valuable for future machine learning roles.

Machine Learning Engineer

Full Scope

Reston, VA

Other

Posted 26 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.