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Mlops Machine Learning Engineer Jobs in Washington

Cymertek

Machine Learning Engineer

Chantilly, VA ยท On-site

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 ...

Cymertek Corporation

Machine Learning Engineer

Reston, VA ยท On-site

$110 - $170/hr

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 ...

Cymertek

Machine Learning Engineer

Tysons, VA ยท On-site

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 ...

Cymertek

Machine Learning Engineer

Reston, VA ยท On-site

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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All JobsMlops Machine Learning Engineer JobsMlops Machine Learning Engineer Jobs in Washington

Mlops Machine Learning Engineer information

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

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

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.

What are popular job titles related to Mlops Machine Learning Engineer jobs in Washington?

For Mlops Machine Learning Engineer jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Mlops Machine Learning Engineer jobs in Washington look for?

The top searched job categories for Mlops Machine Learning Engineer jobs in Washington are:

What cities in Washington are hiring for Mlops Machine Learning Engineer jobs?

Cities in Washington with the most Mlops Machine Learning Engineer job openings:

Mlops Machine Learning Engineer jobs near you

Machine Learning Engineer

Cymertek Corporation

Chantilly, VA โ€ข On-site

Full-time

Re-posted 29 days ago

Job description

Job Summary:
Cymertek Corporation is seeking a talented and innovative Machine Learning Engineer to join their team and help build intelligent systems that drive impactful business solutions. In this role, you will work with cutting-edge technologies to design, develop, and deploy machine learning models that solve complex problems and improve decision-making processes.
Responsibilities:
โ€ข Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning)
โ€ข Ability to design, implement, and optimize machine learning models and workflows
โ€ข Experience working with large, complex datasets
โ€ข Knowledge of data preprocessing and feature engineering
โ€ข Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure)
โ€ข Strong problem-solving skills and analytical thinking
Qualifications:
Required:
โ€ข Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning)
โ€ข Ability to design, implement, and optimize machine learning models and workflows
โ€ข Experience working with large, complex datasets
โ€ข Knowledge of data preprocessing and feature engineering
โ€ข Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure)
โ€ข Strong problem-solving skills and analytical thinking
โ€ข Proficiency in programming languages (e.g., Python, R, Java)
โ€ข Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
โ€ข Expertise in model evaluation techniques and metrics
โ€ข Strong knowledge of version control tools (e.g., Git)
โ€ข Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau)
โ€ข Understanding of database technologies (e.g., SQL, NoSQL)
โ€ข Bachelor's Degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, Statistics, Software Engineering, Electrical Engineering, Robotics, Computational Biology, Physics, etc.
Preferred:
โ€ข Experience with natural language processing (NLP)
โ€ข Knowledge of deep learning techniques (e.g., CNNs, RNNs)
โ€ข Familiarity with deployment tools (e.g., Docker, Kubernetes)
โ€ข Experience with data augmentation and synthetic data generation
โ€ข Ability to collaborate in cross-functional teams (e.g., engineers, product managers)
โ€ข Knowledge of edge computing and model optimization for deployment
Company:
With headquarters in Maryland, Cymertek [/'sฤซ-mer-tek/] Corporation provides superior consulting services for the implementation of high quality information systems. Founded in 2010, the company is headquartered in Laurel, USA, with a team of 11-50 employees. The company is currently Early Stage.

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