AI/ML Engineer Skill Level 2 - FFPP-8841

Nyla Technology Solutions

• $188K — $223K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Active security clearance at the TS/SCI polygraph level required.
  • Bachelor's degree in a technical discipline with 10+ years of software engineering experience, or a Master's with 5+ years, or a high school diploma/GED plus 15+ years of technical experience.
  • Demonstrated experience in applied machine learning using frameworks like PyTorch or TensorFlow.
  • Hands-on experience with model lifecycle management and MLOps practices.
  • Strong skills in statistical analysis and data engineering.
  • Proven ability to transition prototypes to production-ready systems.
  • Excellent communication skills with a focus on team leadership.

Responsibilities

  • Design, build, test, and deploy advanced AI/ML models to tackle high-stakes challenges.
  • Oversee the entire lifecycle, including data pipeline architecture and statistical analysis.
  • Guide cross-functional teams as the primary subject matter expert in AI initiatives.
  • Evaluate and ensure the accuracy of AI systems through iterative feedback loops.
  • Transform scalable solutions from experimental proofs to production systems.
  • Monitor data distribution changes to inform model adjustments and retraining.
  • Develop and enforce software testing and evaluation protocols for robust system performance.

Benefits

  • Comprehensive benefits package includes health, dental, and vision insurance.
  • Eligibility for discretionary bonus compensation.
  • Opportunities for professional development and training.
  • Flexible work environment to promote work-life balance.
  • Access to cutting-edge tools and technologies in AI/ML.
Full Job Description
Job Description

ACTIVE SECURITY CLEARANCE AT THE TS/SCI POLYGRAPH LEVEL IS REQUIRED

We are seeking a visionary, inventive Artificial Intelligence / Machine Learning (AI/ML) Engineer to design, build, test, and productize advanced models that solve high-stakes challenges. In this role, you won't just train models in isolation-you will transform data science prototypes into production-ready, scalable AI solutions. You will oversee the complete lifecycle: architecting data pipelines, selecting optimal representations, running statistical analyses, and continuously refining models through iterative feedback and retraining loops. As a technical leader and primary subject matter expert, you will guide test and evaluation protocols, evaluate data distribution shifts, and ensure our AI systems deliver accurate, mission-critical predictions at scale.

The annual base salary range for this role is $188,000-$223,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.

Required Skills

Applied Machine Learning: Demonstrated experience selecting, training, evaluating, and productizing AI/ML models using standard frameworks (e.g., PyTorch, TensorFlow) and ML libraries.

Model Lifecycle & MLOps: Hands-on experience in pipeline interaction, data modeling, feature selection, model verification/validation, monitoring, and iterative retraining based on feedback loops.

Data Engineering & Statistical Analysis: Strong capabilities in statistical analysis, detecting data distribution shifts, and converting raw datasets into effective data representations for ML algorithms.

Prototype-to-Production Engineering: Proven ability to transform experimental data science prototypes into scalable, performant production systems with proper system integration oversight.

Software Foundations & Test Protocols: Sound understanding of application development concepts, data structures, software architecture, and running standard test/evaluation protocols.

Communication & Technical Leadership: Excellent analytical, problem-solving, and presentation skills to serve as a primary POC for AI initiatives and guide cross-functional teams.

Education: Bachelor's Degree in Computer Science, Computer Engineering, Software Engineering, or a related technical discipline, PLUS 10+ years of professional software engineering experience OR Master's Degree PLUS 5+ years of professional software engineering experience OR High School Diploma / GED, PLUS 15+ years of hands-on technical software development experience in lieu of a degree.

Desired Skills

Multi-Language Mastery: Advanced proficiency in multiple programming languages, such as Python, Java, C, C++, or R.

Advanced MLOps & Infrastructure: Deep familiarity with cloud-based AI deployments, automated model scheduling, data governance, and automated CI/CD pipelines for ML models.

Distributed Team Leadership: Direct experience leading geographically dispersed engineering teams and driving collaborative AI research initiatives.

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