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Senior Machine Learning Engineer

Job in McLean, Fairfax County, Virginia, USA
Listing for: TheIncLab
Full Time position
Listed on 2025-12-29
Job specializations:
  • Engineering
    AI Engineer
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below

The Mission Starts Here

The Inc Lab  engineers and delivers intelligent digital applications and platforms that revolutionize how our customers and mission-critical teams achieve success.

We are where innovation meets purpose; and where your career can meet purpose as well. We are looking for a Senior Machine Learning Engineer to that will focus on researching, designing, training, and evaluating machine learning models to solve complex, real-world problems. We encourage you to apply and take the first step in joining our dynamic and impactful company.

Your Mission, Should You Choose to Accept

As a Machine Learning Engineer, you will research, evaluate, and select appropriate machine Learning approaches and architectures based on the problem definition.

What will you do?
  • Research, evaluate, and select appropriate machine learning approaches and architectures based on the problem definition
  • Supervised, unsupervised, and reinforcement learning
  • Neural networks, decision trees, ensemble methods
  • Transformer-based models, adversarial networks, genetic algorithms
  • Retrieval-Augmented Generation (RAG) where appropriate
  • Design and implement machine learning models using frameworks such as PyTorch, Tensor Flow, or equivalent
  • Formulate and solve optimization problems using ML techniques
  • Pathfinding and routing
  • Combinatorial and constraint-based optimization Heuristic and learning-based optimization approaches
  • Own data pipelines for ML systems
  • Data validation and quality checks
  • Feature engineering and preprocessing
  • Data augmentation strategies for training robustness
  • Train, tune, and debug models, addressing issues such as overfitting, instability, bias, and performance degradation
  • Define and apply appropriate evaluation metrics, analyze results and iteratively improve model performance
  • For transformer-based systems
  • Optimize context window usage Manage token budgets, chunking strategies, and retrieval mechanisms
  • Balance performance, accuracy, and computational cost
  • Integrate ML models and data pipelines into production systems
  • Make technical decisions and provide architectural guidance for ML systems
  • Document experiments, results, and design decisions using tools such as Git, Jira, and Confluence
  • Mentor junior engineers and guide best practices in ML development Stay current with emerging ML research, tools, and techniques
  • Ability to travel up to 20%
Capabilities that will enable your success
  • Bachelor’s degree in Computer Science, Engineering, Applied Mathematics, or a related field
  • 7+ years of professional experience, including significant hands‑on machine learning development
  • Strong understanding of machine learning theory and fundamentals
  • Model selection and evaluation
  • Bias/variance tradeoffs
  • Optimization and loss functions
  • Demonstrated experience training and evaluating models using frameworks such as PyTorch or Tensor Flow
  • Experience building and maintaining end‑to‑end ML pipelines
  • Strong programming skills in Python (additional languages are a plus)
  • Experience working with real‑world, imperfect datasets
  • Ability to explain model behavior, tradeoffs, and limitations to both technical and non‑technical stakeholders
  • Strong grasp of software engineering best practices and system design
Preferred Qualifications
  • Experience with deep learning architectures (CNNs, RNNs, Transformers)
  • Experience applying ML to optimization, planning, or decision‑making problems
  • Familiarity with distributed training or large‑scale data processing
  • Experience with experiment tracking tools (e.g., MLflow, Weights & Biases)
  • Experience deploying ML models into production (batch or real‑time inference) Background in research‑driven or R&D‑focused engineering environments
Clearance Requirements

Applicants must be a U.S. Citizen and willing and eligible to obtain a U.S. Security Clearance at the Secret or Top‑Secret level. Existing clearance is preferred.

Benefits
  • Hybrid and flexible work schedules
  • Professional development programs
  • Training and certification reimbursement e options for Me
  • Extended and floating holiday schedule
  • Paid time off and Paid volunteer time
  • Health and Wellness Benefits includdical, Dental, and Vision insurance along with access to Wellness, Mental Health, and…
Position Requirements
10+ Years work experience
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