ZipRecruiter

Log In

1

Machine Language Jobs in Virginia (NOW HIRING)

BMS Direct, Inc

Flex Machine Operator

Lynchburg, VA · On-site

$16.50 - $19.75/hr

Flex Machine Operator- Production Supervisor: Production Supervisor Job Summary: Set up and operate ... Language / Communication skills * Ability to read and comprehend instructions, correspondence, and ...

BMS Direct, Inc

Flex Machine Operator

Lynchburg, VA · On-site

$16.50 - $19.75/hr

Flex Machine Operator- Production Supervisor: Production Supervisor Job Summary: Set up and operate ... Language / Communication skills * Ability to read and comprehend instructions, correspondence, and ...

BMS Direct, Inc

Flex Machine Operator

Lynchburg, VA

$16.50 - $19.75/hr

Flex Machine Operator- Production Supervisor: Production Supervisor Job Summary: Set up and operate ... Language / Communication skills * Ability to read and comprehend instructions, correspondence, and ...

Cymertek

Machine Learning Engineer

Chantilly, VA

Machine Learning Engineer LOCATIONChantilly, VA 20151 CLEARANCETS/SCI Full Poly (Please note this ... Experience with natural language processing (NLP) * Knowledge of deep learning techniques (e.g ...

Cymertek

Machine Learning Engineer

Tysons, VA

Machine Learning Engineer LOCATIONTysons, VA 22182 CLEARANCETS/SCI Full Poly (Please note this ... Experience with natural language processing (NLP) * Knowledge of deep learning techniques (e.g ...

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this ... Experience with natural language processing (NLP) * Knowledge of deep learning techniques (e.g ...

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this ... Experience with natural language processing (NLP) * Knowledge of deep learning techniques (e.g ...

Cymertek

Machine Learning Engineer

Reston, VA

Machine Learning Engineer LOCATIONReston, VA 20190 CLEARANCETS/SCI Full Poly (Please note this ... Experience with natural language processing (NLP) * Knowledge of deep learning techniques (e.g ...

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this ... Experience with natural language processing (NLP) * Knowledge of deep learning techniques (e.g ...

next page

Showing results 1-20

People also search for

All JobsMachine Language JobsMachine Language Jobs in Virginia

Machine Language information

See Virginia salary details

$9

$40

$76

How much do machine language jobs pay per hour?

As of Jun 5, 2026, the average hourly pay for machine language in Virginia is $40.59, according to ZipRecruiter salary data. Most workers in this role earn between $17.53 and $56.81 per hour, depending on experience, location, and employer.

What is the difference between Machine Language vs Data Scientist?

AspectMachine LanguageData Scientist
Required CredentialsNone specific; basic programming knowledgeBachelor's or higher in CS, statistics, or related fields
Work EnvironmentLow-level programming, embedded systems, hardware interactionData analysis, modeling, visualization in offices or labs
Industry UsageSoftware development, embedded systems, hardware programmingTech, finance, healthcare, marketing

Machine Language involves low-level programming directly with binary instructions, primarily used for hardware interaction. Data Scientists analyze data to extract insights, often using high-level languages like Python or R. While both roles require programming skills, Machine Language focuses on hardware-level coding, whereas Data Scientists work with data analysis and modeling.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (especially Python), and a relevant degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms, and data processing tools, as well as certifications in data science or machine learning, are highly valuable. Problem-solving skills, curiosity, and effective collaboration are crucial soft skills for innovating and working in multidisciplinary teams. These abilities are essential to design, implement, and optimize models that drive data-driven decision-making and business success.

What are some common challenges faced by professionals working with machine learning models, and how can they be addressed?

Professionals in machine learning often encounter challenges such as managing large and complex datasets, addressing data quality issues, and preventing model overfitting. Collaborating effectively with data engineers and domain experts can help ensure data relevance and accuracy. Additionally, staying updated with the latest research and best practices is important for optimizing model performance and adapting to evolving business needs. Regular code reviews and model validation are key practices that help maintain high-quality, reliable machine learning solutions.

What is machine language and what does a machine language programmer do?

Machine language is the lowest-level programming language, consisting of binary code that computers can directly execute. A machine language programmer writes instructions in this binary code to control computer hardware at the most fundamental level. This job often involves optimizing code for performance and working closely with computer architecture. Machine language programming is rare today, as higher-level languages are more commonly used, but it remains crucial for certain applications like embedded systems and hardware drivers.
What are popular job titles related to Machine Language jobs in Virginia? For Machine Language jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Machine Language jobs in Virginia look for? The top searched job categories for Machine Language jobs in Virginia are:
Machine Language jobs near you
Infographic showing various Machine Language job openings in Virginia as of May 2026, with employment types broken down into 78% Full Time, 11% Part Time, 8% Contract, and 3% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $84,418 per year, or $40.6 per hour.
Machine Learning Engineer - Geospatial (TS/SCI) with Security Clearance

Machine Learning Engineer - Geospatial (TS/SCI) with Security Clearance

LaunchCode

Springfield, VA

$175K - $250K/yr

Other

Posted 3 days ago

Job description

Description Title: AI/Machine Learning Engineer - Vision Language Models / Multimodal AI (NGA)
Location: Springfield or Herndon, VA (onsite)
Clearance: TS/SCI (CI Poly preferred) Position Type: Full-Time, Direct Hire Pay: $175,000 to $250,000 for an SME Company: The name of our partner organization will be disclosed during the interview process. This is not a direct role with LaunchCode; it is a position through LaunchCode, working with one of our partner companies. Disclaimer: We are unable to provide work sponsorship for this role Overview: We're hiring a AI/Machine Learning Engineer with strong experience in multimodal AI and large-scale model training to support advanced vision-language initiatives in a secure government environment. This role will focus on fine-tuning Vision Language Models (VLMs) on domain-specific geospatial imagery, building scalable AWS training infrastructure, and developing evaluation frameworks for image understanding and spatial reasoning. Ideal candidates will have deep experience with PyTorch, HuggingFace, distributed training, and computer vision, along with the ability to optimize and deploy multimodal models in mission-critical environments. Huge plus for candidates who have hands-on experience taking multimodal models such as CLIP, LLaVA, Qwen-VL, or similar Vision Language Models and fine-tuning them on classified or mission-specific imagery datasets. The ideal candidate can build the AWS infrastructure needed to train and scale these models, evaluate performance improvements across real-world use cases, and deploy solutions into secure government or air-gapped environments. Key Responsibilities: * Design and execute fine-tuning pipelines for Vision Language Models (VLMs) using domain-specific imagery datasets
  • Handle data preprocessing, training orchestration, and hyperparameter optimization for multimodal models
  • Build evaluation frameworks for image understanding, visual question answering, and spatial reasoning tasks
  • Develop scalable AWS-based ML infrastructure using SageMaker and GPU-enabled EC2 for distributed training
  • Create data pipelines for curating, annotating, and transforming geospatial imagery into model-ready datasets
Partner with applied scientists and architects on model architecture improvements, LoRA/QLoRA strategies, and inference optimization Required Qualifications: Active TS/SCI with CI Poly
  • 5+ years of machine learning engineering experience focused on deep learning
  • 1+ year of hands-on experience fine-tuning foundation models (LLMs or VLMs)
  • Experience with LoRA, QLoRA, adapters, supervised fine-tuning, instruction tuning, and RLHF/DPO
  • 4+ years of advanced Python development for ML workloads
  • Strong PyTorch and HuggingFace experience (Transformers, PEFT, Datasets, Accelerate)
  • Experience with distributed training frameworks such as DeepSpeed, FSDP, or Megatron
  • 3+ years working with computer vision or multimodal models
  • Familiarity with vision transformer architectures (ViT, CLIP, LLaVA, etc.)
  • Experience processing and augmenting image datasets at scale
  • 3+ years with AWS ML infrastructure including SageMaker, EC2 GPU environments, and S3
  • Experience with ML evaluation pipelines, benchmarking, metrics, and result analysis
Strong software engineering fundamentals including version control, testing, and CI/CD Preferred Qualifications: 2+ years working with geospatial or remote sensing imagery
  • Experience with EO or SAR satellite imagery
  • Understanding of geospatial metadata, coordinate systems, and imagery preprocessing
  • Experience with model quantization / inference optimization (vLLM, TensorRT, ONNX)
  • MLOps tooling experience (MLflow, Weights & Biases, SageMaker Experiments)
  • Familiarity with annotation tools and active learning workflows
  • Containerized ML experience with Docker / ECR / ECS / EKS
  • Experience supporting ATO processes and NIST 800-53 compliance
  • Experience deploying in air-gapped/disconnected environments
  • Familiarity with multimodal evaluation benchmarks (MMMU, MMBench, GQA)
  • Publications or contributions in computer vision, multimodal AI, or VLMs
  • Synthetic data generation experience for training augmentation

Apply