AI/ML Engineer I

Reflexive Concepts, LLC; Maryland; On-site; USD 90,000 - 130,000; Full time

Job summary

Reflexive Concepts, LLC seeks an AI/ML I with hands-on NLP and full-stack development experience. You will work across model development lifecycles, from training to deployment, collaborating with cross-functional teams to deliver impactful AI solutions.

The ideal candidate has 2 years of applied ML experience, a B.S. in a STEM field, and familiarity with language models, Marian, and multilingual NLP. Proficiency in Java/C/C++ and AWS tools is highly valued.

Qualifications

• 2 years of applied ML experience in programs and contracts of similar scope, type, and complexity is required.
• B.S. degree in advanced math (e.g., calculus, linear algebra or Bayesian statistics), computer science or related STEM discipline from an accredited college or university is required.
• 3 years of additional machine learning experience on projects with similar machine learning processes may be substituted for a bachelor’s degree.
• Knowledge and experience of Language models is required.
• Specific experience with Marian and multi-lingual model development is required.
• Knowledge of Computation Linguistics is a plus.
• Experience with Open-Source model libraries, Deep Learning Containers (DLC), GPU technologies and optimization / tuning is required.
• Strong Java, C, C++ programming experience is required.
• Willingness to support occasional on-call duties is a plus.
• Model Development & Training: Build, train, and fine-tune machine learning models, particularly language models; Apply best practices in model training, tuning, and optimization; Design and implement solutions for model performance improvement.
• Evaluation & Testing: Conduct rigorous model evaluation, including performance analysis and benchmarking; Perform error analysis, debugging, and model diagnostics to ensure quality and reliability.
• Model Deployment & Integration: Work with cloud-based AI platforms (especially AWS Sagemaker) to deploy and scale models; Integrate machine learning models into production environments, ensuring seamless integration with other systems.
• Full-Stack Engineering: Contribute to the development and maintenance of the full stack for AI model-based applications (front-end and back-end); Collaborate with software engineers to build scalable and efficient deployment pipelines.
• Collaboration & Reporting: Work closely with data scientists, product teams, and engineers to translate business requirements into technical solutions; Document workflows, model design processes, and technical specifications

Responsibilities

• Knowledge and experience of Language models is required
• Specific experience with Marian and multi-lingual model development
• Knowledge of Computation Linguistics is a plus
• Experience with Open-Source model libraries, Deep Learning Containers (DLC), GPU technologies and optimization / tuning
• Strong Java, C, C++ programming experience
• Willingness to support occasional on-call duties is a plus
• Model Development & Training: Build, train, and fine-tune machine learning models, particularly language models
• Apply best practices in model training, tuning, and optimization.
• Design and implement solutions for model performance improvement.
• Evaluation & Testing: Conduct rigorous model evaluation, including performance analysis and benchmarking.
• Perform error analysis, debugging, and model diagnostics to ensure quality and reliability.
• Model Deployment & Integration: Work with cloud-based AI platforms (especially AWS Sagemaker) to deploy and scale models.
• Integrate machine learning models into production environments, ensuring seamless integration with other systems.
• Full-Stack Engineering: Contribute to the development and maintenance of the full stack for AI model-based applications (front-end and back-end).
• Collaborate with software engineers to build scalable and efficient deployment pipelines.
• Collaboration & Reporting: Work closely with data scientists, product teams, and engineers to translate business requirements into technical solutions.
• Document workflows, model design processes, and technical specifications

Skills

NLP expertise

Language models

Full-stack development

Java, C, C++ programming

AWS tools (SageMaker, Lambda, EC2, S3)

Git / MLFlow

Containerization (Kubernetes)

Problem solving

Education

B.S. in advanced math / CS or related STEM

3 years ML experience substitution for degree

Tools

TensorFlow

PyTorch

Hugging Face

MLFlow

Kubernetes

AWS (SageMaker)

Docker

Job description

Reflexive Concepts is seeking a skilled Artificial Intelligence/Machine Learning I to join our team!

The ideal candidate will have hands-on experience with state-of-the-art machine learning techniques, specifically for natural language processing (NLP), and will also have strong understanding of full-stack development. This person will work across the model development lifecycle and collaborate with cross-functional teams to deliver high-impact solutions.

Qualifications:

• 2 years of experience in applied machine learning in programs and contracts of similar scope, type, and complexity is required.
• B.S. degree in advanced math (e.g., calculus, linear algebra or Bayesian statistics), computer science or related STEM discipline from an accredited college or university is required.
  • 3 years of additional machine learning experience on projects with similar machine learning processes may be substituted for a bachelor’s degree.

Key Responsibilities:

• Knowledge and experience of Language models is required
• Specific experience with Marian and multi-lingual model development
• Knowledge of Computation Linguistics is a plus
• Experience with Open-Source model libraries, Deep Learning Containers (DLC), GPU technologies and optimization / tuning
• Strong Java, C, C++ programming experience
• Willingness to support occasional on-call duties is a plus
• Model Development & Training:
  • Build, train, and fine-tune machine learning models, particularly language models
  • Apply best practices in model training, tuning, and optimization.
  • Design and implement solutions for model performance improvement.
• Evaluation & Testing:
  • Conduct rigorous model evaluation, including performance analysis and benchmarking.
  • Perform error analysis, debugging, and model diagnostics to ensure quality and reliability.
• Model Deployment & Integration:
  • Work with cloud-based AI platforms (especially AWS Sagemaker) to deploy and scale models.
  • Integrate machine learning models into production environments, ensuring seamless integration with other systems.
• Full-Stack Engineering:
  • Contribute to the development and maintenance of the full stack for AI model-based applications (front-end and back-end).
  • Collaborate with software engineers to build scalable and efficient deployment pipelines.
• Collaboration & Reporting:
  • Work closely with data scientists, product teams, and engineers to translate business requirements into technical solutions.
  • Document workflows, model design processes, and technical specifications

Required Skills:

• Strong proficiency in AI/ML frameworks such as TensorFlow, PyTorch, or Hugging Face.
• Expertise in model training, evaluation, and deployment.
• Hands-on experience with AWS tools like SageMaker, Lambda, EC2, and S3.
• Experience in developing full-stack software applications (JavaScript, Python, Java, etc.).
• Solid understanding of data structures, algorithms, and system design.
• Experience & Background:
  • Extensive experience in machine learning model development, including natural language processing (NLP).
  • Experience with model evaluation, optimization, and performance monitoring.
  • Proven experience in software engineering with strong coding skills.
  • Experience working in a government or defense-related environment is highly preferred.
• Additional Skills:
  • Experience with model versioning and management using tools such as MLFlow or Git.
  • Familiarity with containerization tools (i.e. Kubernetes).
  • Strong problem-solving and analytical skills.
  • Excellent communication and collaboration abilities.

Nice to Have:

• Experience with secure data handling and compliance requirements
• Experience working with Large Language Models (LLMs)