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Temporary Machine Learning Trainer Jobs in Washington

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

About the Role We are seeking a Machine Learning Engineer to design, build, and evaluate advanced ... Hands-on experience training, fine-tuning, or evaluating modern ML models. * Strong understanding ...

Build and maintain ML pipelines for training, evaluation, and inference * Integrate machine learning models into real-time and batch processing systems * Optimize model performance for accuracy ...

Machine Learning Engineer

Mclean, VA · On-site

$105K - $115K/yr

As a Machine Learning Engineer at Somatus, you will work collaboratively with our data and ... Build pipelines for training, evaluating, and deploying models. * Perform exploratory data analysis ...

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

Machine learning experience using visual data * Understanding of a variety of machine learning ... Experience curating quality, real-world datasets for training deep learning models * Proficiency in ...

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

Machine learning experience using visual data * Understanding of a variety of machine learning ... Experience curating quality, real-world datasets for training deep learning models * Proficiency in ...

Machine Learning Engineer

Arlington, VA · On-site

$110K - $160K/yr

Machine learning experience using visual data * Understanding of a variety of machine learning ... Experience curating quality, real-world datasets for training deep learning models * Proficiency in ...

Comfortable designing training and inference pipelines * Understanding of full-stack software ... Machine Learning Engineering Leadership * Production Deployment Experience * Python Proficiency

Most of the machine learning work that reaches production is not modelling. It is knowing which ... Build reproducible training and fine-tuning pipelines against regulated data * Turn ambiguous ...

Most of the machine learning work that reaches production is not modelling. It is knowing which ... Build reproducible training and fine-tuning pipelines against regulated data * Turn ambiguous ...

Most of the machine learning work that reaches production is not modelling. It is knowing which ... Build reproducible training and fine-tuning pipelines against regulated data * Turn ambiguous ...

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Temporary Machine Learning Trainer information

What is a temporary machine learning trainer?

Temporary Machine Learning Trainers are professionals hired on a short-term or contract basis to develop, implement, and refine machine learning models or to train teams in machine learning techniques. Their responsibilities often include preparing training data, selecting appropriate algorithms, and ensuring models are accurate and efficient. They may also provide guidance to organizations on best practices and help upskill employees in machine learning concepts. These roles are typically project-based and may last from a few weeks to several months, depending on organizational needs.

What are some common challenges faced by temporary machine learning trainers, and how can they be managed effectively?

Temporary Machine Learning Trainers often face the challenge of quickly adapting to new team environments and rapidly understanding existing workflows. Additionally, they may need to balance delivering training sessions with handling updates to curriculum or technology. Effective communication with permanent staff and staying up-to-date with the latest machine learning tools can help manage these challenges. Being proactive in seeking feedback and clarifying expectations early on can also contribute to a smoother transition and more impactful training sessions.

What are the key skills and qualifications needed to thrive as a temporary machine learning trainer, and why are they important?

To thrive as a Temporary Machine Learning Trainer, you need a solid background in machine learning concepts, data analysis, and model evaluation, usually supported by a relevant degree or experience in computer science or a related field. Familiarity with programming languages like Python, machine learning libraries (such as TensorFlow or scikit-learn), and educational tools is typically required. Strong communication, adaptability, and instructional skills help trainers effectively convey complex topics and respond to diverse learner needs. These skills ensure trainees gain practical knowledge and confidence, contributing to successful training outcomes and organizational goals.

What is the difference between Temporary Machine Learning Trainer vs Data Scientist?

AspectTemporary Machine Learning TrainerData Scientist
CredentialsRelevant certifications (e.g., AWS, Google Cloud), technical trainingAdvanced degrees (Master's or PhD) in data science, statistics, or related fields
Work EnvironmentTraining sessions, workshops, corporate training settingsData analysis, modeling, research environments, often in offices or labs
Employer & Industry UsageTech companies, educational institutions, consulting firmsTech, finance, healthcare, research organizations

While both roles involve working with data and machine learning, a Temporary Machine Learning Trainer primarily focuses on educating and training teams or clients on machine learning tools and concepts. In contrast, a Data Scientist develops models, analyzes data, and derives insights for decision-making. The roles differ mainly in their focus—training versus data analysis—though they share foundational technical skills.

What are the most commonly searched types of Machine Learning Trainer jobs in Washington?

The most popular types of Machine Learning Trainer jobs in Washington are:

What cities in Washington are hiring for Temporary Machine Learning Trainer jobs?

Cities in Washington with the most Temporary Machine Learning Trainer job openings:

Engineer, Machine Learning

Venture Global, Inc.

Arlington, VA • On-site

$157K - $185K/yr

Full-time

Posted 16 days ago


Job description

Venture Global LNG ("Venture Global") is a long-term, low-cost provider of American-produced liquefied natural gas. The company's Louisiana-based export projects service the global demand for North American natural gas and support the long-term development of clean and reliable North American energy supplies. Using reliable, proven technology in an innovative plant design configuration, Venture Global's modular, mid-scale plant design will replace traditional designs as it allows for the same efficiency and operational reliability at significantly lower capital cost.
We are seeking qualified applicants for the position:
Engineer, Machine Learning
Located:
Arlington
Summary
The Machine Learning Engineer will design, develop, and maintain the productionization of machine learning, deep learning, generative AI, large language models, simulation, and optimization algorithms. This includes building pipelines for training and deploying deep learning and other machine learning algorithms and enabling models to run efficiently in production. The main data engineering work will be done in Databricks and PySpark.
The ideal candidate will have excellent technical proficiency, excellent communication skills, a self-driven mindset, and the willingness to continuously learn new things.
This position will report to the Director of Business Intelligence and is structured within IT under the Vice President of Applications.
The position will be located in Arlington, VA and will require commuting to the office 5 days a week.
General Description Duties & Responsibilities
  • Work with business stakeholders to define project requirements.
  • Orchestrate, scale, setup and improve model serving pipelines.
  • Improve model accuracy through feature engineering, tuning, and observability.
  • Improve model computational performance through all aspects of the pipeline, including tuning clusters/job compute, partitioning, caching, feature engineering code, tuning setup, etc.
  • Integrate machine learning models into production environments, ensuring reliability and scalability.
  • Evaluate pretrained models and software from vendors and support integration into production environments.
  • Develop comprehensive project plans for implementing machine learning and AI projects including solution architectures, resourcing, and dependencies.
  • Provide ETL requirements to data engineers to effectively curate files for data analytics.
  • Work with data scientists, data engineers, and business analysts to translate business requirements into machine learning solutions.
  • Build software solutions that are maintainable, scalable and provide quantifiable business value.
  • Continuously focus on quality architecture, quality code, and ruthless management of technical debt.
  • Continuously push the practice forward, learning and testing newer and better ways of performing work.

Qualifications
Required experience
  • 5 years of machine learning engineering, software engineering, or data science experience.
  • Bachelors in a quantitative field of study.

Preferred Experience
  • Masters in a quantitative field of study.
  • Experience with the Azure, AWS, or other cloud ecosystems.
  • Experience in building secure data processing pipelines.
  • Proficient in utilizing data lakes, CI/CD pipelines, Databricks, Unity Catalog, and Git.
  • Experience working with streaming.
  • Expertise in building machine learning solutions using cloud data services.
  • Exceptional skills in data processing languages such as SQL, Python, or Scala.
  • Exceptional skills in feature engineering, model optimization, and parameter tuning.

Salary Range
$157,000-$185,000
Venture Global LNG is an Equal Opportunity Employer. We do not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law.