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In Place Machining Jobs in Washington (NOW HIRING)

AI Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... in place. Key Responsibilities: * Design, implement, and maintain ML deployment pipelines for ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... in place. Key Responsibilities: * Design, implement, and maintain ML deployment pipelines for ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... in place. Key Responsibilities: * Design, implement, and maintain ML deployment pipelines for ...

Lockheed Martin

Technician

Severn, MD · On-site

We are seeking a Junior Technician in Severn, MD. Role & Responsibilities Performs a variety of electronic assembly duties, to include MYDATA and Panasonic NPM-WX Pick and place machines, and ...

Lockheed Martin Corporation

Technician

Severn, MD · On-site

We are seeking a Junior Technician in Severn, MD. Role & Responsibilities Performs a variety of electronic assembly duties, to include MYDATA and Panasonic NPM-WX Pick and place machines, and ...

WM T Burnett Foam LLC

Slitter Operator

Jessup, MD · On-site

$17 - $19.38/hr

The machine and conveyors function properly * Have in place the proper size cores, tape, and shrink-wrap according to the Customer Product Master. * Complete all information at the top of the Slitter ...

WM T BURNETT Holding LLC

Slitter Operator

Jessup, MD

$17 - $19.38/hr

The machine and conveyors function properly * Have in place the proper size cores, tape, and shrink-wrap according to the Customer Product Master. * Complete all information at the top of the Slitter ...

Annapolis Micro Systems

Be Seen First

SMT Operator - 2nd Shift

Annapolis, MD · On-site

$36.04 - $46.31/hr

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Hands on experience with a Pick and Place machine * Ability to lift 20 lbs Desired Technical Background * Experience in handling SMT components, boards, and tools for assembly * Experience with SMT ...

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In Place Machining information

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How much do in place machining jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for in place machining in Washington is $25.17, according to ZipRecruiter salary data. Most workers in this role earn between $21.78 and $28.03 per hour, depending on experience, location, and employer.

What is in place machining?

In place machining, also known as on-site or field machining, refers to performing precision machining operations directly at the equipment’s location rather than moving it to a machine shop. This service is commonly used for large, heavy, or immovable equipment found in industries like power generation, marine, and manufacturing. It helps minimize downtime, reduces transportation costs, and ensures that repairs or modifications are completed efficiently and accurately without dismantling entire assemblies.

What are the key skills and qualifications needed to thrive as an in place machining technician?

To thrive as an In Place Machining Technician, you need strong mechanical aptitude, precision measurement skills, and experience with industrial machining processes, often supported by a technical diploma or apprenticeship. Familiarity with portable machining tools, alignment systems, and CNC equipment is commonly required, and certifications like OSHA or ASNT can be beneficial. Attention to detail, problem-solving abilities, and effective communication are crucial soft skills for this role. These skills ensure accurate on-site repairs, minimize downtime, and maintain safety and quality in demanding industrial environments.

What are some common challenges faced by in place machining professionals, and how can they be addressed?

In Place Machining professionals often work in environments where precision is critical and downtime must be minimized, such as power plants or manufacturing facilities. Common challenges include working in confined spaces, adapting to irregular or worn components, and maintaining safety standards while operating heavy equipment on-site. These challenges can be addressed through thorough job planning, use of specialized portable machining tools, continuous safety training, and strong communication with both clients and team members to ensure all requirements are clearly understood and met.

What is the difference between In Place Machining vs Pipe Fitting?

AspectIn Place MachiningPipe Fitting
CredentialsTechnical certifications, machining experienceTrade certifications, plumbing or pipefitting licenses
Work EnvironmentIndustrial sites, manufacturing plants, power plantsConstruction sites, industrial facilities, maintenance environments
Industry UsageMachining equipment, repairing machinery, restoring surfacesInstalling, repairing, and maintaining piping systems

In Place Machining focuses on restoring or repairing equipment surfaces and components through precision machining, often in industrial settings. Pipe Fitting involves installing and maintaining piping systems. While both roles require technical skills and work in industrial environments, In Place Machining emphasizes machining processes, whereas Pipe Fitting centers on pipe installation and repair.

What are popular job titles related to In Place Machining jobs in Washington?

For In Place Machining jobs in Washington, the most frequently searched job titles are:

What job categories do people searching In Place Machining jobs in Washington look for?

The top searched job categories for In Place Machining jobs in Washington are:

What cities in Washington are hiring for In Place Machining jobs?

Cities in Washington with the most In Place Machining job openings:

In Place Machining jobs near you
Infographic showing various In Place Machining job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 18% Part Time, 2% Temporary, and 7% Contract. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $52,362 per year, or $25.2 per hour.

Machine Learning Engineer

AI Squared

Washington, DC

Full-time

Re-posted 28 days ago

Job description

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, maintaining, and monitoring the AI/ML systems that power our platform. You will work closely with data scientists, data engineers, and product teams to ensure scalable, reliable, and production-grade AI solutions. You'll play a critical role in operationalizing large language models (LLMs) and other ML systems, ensuring they run efficiently, securely, and with robust monitoring in place.

Key Responsibilities:
  • Design, implement, and maintain ML deployment pipelines for scalable production systems.
  • Operationalize large language models (LLMs) and other AI/ML models, ensuring high availability and reliability.
  • Build robust model monitoring, logging, and alerting systems to track performance and detect drift.
  • Partner with data scientists to transition models from research/prototype into production-ready deployments.
  • Develop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.
  • Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed systems.
  • Apply containerization and orchestration (Docker, Kubernetes) to enable reproducible, scalable systems.
  • Collaborate with cross-functional teams to ensure ML systems align with platform goals and business requirements.
Qualifications:
  • 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role.
  • Proven experience deploying and maintaining machine learning models in production at scale.
  • Hands-on experience with ML lifecycle tooling (MLflow, Kubeflow, SageMaker, Vertex AI, or similar).
  • Strong proficiency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
  • Deep knowledge of containerization (Docker) and orchestration (Kubernetes) for production ML systems.
  • Expertise with cloud platforms (AWS, GCP, Azure) for ML deployment and scaling.
  • Strong understanding of MLOps best practices, monitoring, and automation.
  • Excellent problem-solving skills, with an emphasis on building reliable, scalable systems.
  • Strong communication and collaboration skills across technical and non-technical teams.

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