ZipRecruiter

Log In

1

Ml Inference Jobs in Washington, DC (NOW HIRING)

Synergy ECP

AI/ML Engineer

Annapolis Junction, MD · On-site

They are seeking AI/ML Engineers to build, deploy, and maintain machine learning models and data ... inference • Collaborate with software and DevOps teams for integration • Monitor model ...

540

Senior AI/ML Engineer

Arlington, VA · On-site

$120K - $165K/yr

Experience designing model-serving capabilities for batch and real-time inference * Experience ... Experience architecting AI/ML solutions within AWS, Azure, or Google Cloud * Experience with data ...

Adtech

AI/ML Engineer With DevOps

Ashburn, VA · On-site

$54 - $74/hr

Develop and optimize model training & inference pipelines for real-time execution, and efficiently handle large-scale data processing * Work with data science teams to structure automated ML model ...

Doist

Senior AI/ML Engineer

Arlington, VA · On-site

$140 - $210/hr

Experience designing model-serving capabilities for batch and real-time inference * Experience ... Experience architecting AI/ML solutions within AWS, Azure, or Google Cloud * Experience with data ...

540

Senior AI/ML Engineer

Arlington, VA · On-site

$120K - $165K/yr

Experience designing model-serving capabilities for batch and real-time inference * Experience ... Experience architecting AI/ML solutions within AWS, Azure, or Google Cloud * Experience with data ...

540

Senior AI/ML Engineer

Arlington, VA

$120K - $165K/yr

Experience designing model-serving capabilities for batch and real-time inference * Experience ... Experience architecting AI/ML solutions within AWS, Azure, or Google Cloud * Experience with data ...

GRVTY

AI/ML Engineer

Mclean, VA

What You'll be Owning GRVTY is seeking an experienced AI/ML Engineer with a TS/SCI + Poly clearance ... Familiarity with model evaluation frameworks, fine-tuning workflows, inference optimization, and AI ...

Closure Technologies

AI/ML Engineer

Mclean, VA · On-site

Closure Technologies is seeking a AI/ML Engineer who will Implement and maintain Retrieval ... Familiarity with model evaluation frameworks, fine-tuning workflows, inference optimization, and AI ...

Dev Technology

iOS Mobile Developer (Swift)

Reston, VA · On-site +1

$100K - $160K/yr

Integration of on-device ML inference frameworks (Core ML, ONNX Runtime, WhisperKit) -- loading, lifecycle, error recovery -- not training the models * Real-time audio pipeline: AVAudioEngine, voice ...

Doist

AI/ML Engineer

Arlington, VA · On-site

$120 - $180/hr

... inference * Implement MLOps practices using CI/CD, infrastructure as code, automated testing, and ... Optimize AI/ML services and infrastructure for performance, scalability, reliability, and cost ...

New

previous page

Showing results 41-60

All JobsMl Inference JobsMl Inference Jobs in Washington, DC

Ml Inference information

See Washington, DC salary details

$42.5K

$139K

$222.6K

How much do ml inference jobs pay per year?

As of Aug 21, 2026, the average yearly pay for ml inference in Washington, DC is $139,013.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,600.00 and $154,000.00 per year, depending on experience, location, and employer.

What is ML inference?

ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.

What are the key skills and qualifications needed to thrive in ML inference?

To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.

What are some common challenges faced by ML inference engineers when deploying models to production?

ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.

What is the difference between Ml Inference vs Data Scientist?

AspectML InferenceData Scientist
Required CredentialsKnowledge of machine learning models, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentDeploying models in production, real-time data processingData analysis, model development, research
Industry UsageAI product deployment, software companiesResearch institutions, tech firms, consulting

ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.

What are popular job titles related to Ml Inference jobs in Washington, DC?

For Ml Inference jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Ml Inference jobs in Washington, DC look for?

The top searched job categories for Ml Inference jobs in Washington, DC are:

Ml Inference jobs near you

AI/ML Engineer

Synergy ECP

Annapolis Junction, MD • On-site

Full-time

Re-posted 27 days ago

Job description

Job Summary:
Synergy ECP is a leading provider of cybersecurity, software and systems engineering and IT services to the U.S. intelligence and defense communities. They are seeking AI/ML Engineers to build, deploy, and maintain machine learning models and data-driven systems at scale, collaborating with software and DevOps teams for integration and monitoring model performance.
Responsibilities:
• Develop and train machine learning models
• Deploy models into production environments
• Build data pipelines and workflows for model training and inference
• Collaborate with software and DevOps teams for integration
• Monitor model performance and optimize over time
• Support the full ML lifecycle (data → training → deployment → monitoring)
Qualifications:
Required:
• B.S. degree in a technical field and 3+ years of experience
• Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• Experience with data processing and feature engineering
• Understanding of model evaluation and performance tuning
• Experience deploying ML in production environments
• U.S. Citizenship
• TS/SCI w/ Polygraph
Preferred:
• MLOps / model lifecycle tools
• Cloud ML services (AWS SageMaker, Azure ML)
• Experience with large-scale or real-time systems
Company:
Synergy ECP deals with cybersecurity, information technology, procurement support, project management and financial analysis. Founded in 2007, the company is headquartered in Columbia, USA, with a team of 201-500 employees. The company is currently Growth Stage.

Apply