Machine Learning Engineer

Lyntris offers a remote, contract opportunity for a Machine Learning Engineer focused on NLP and LLM powered document understanding. The role aims to transform engineering documentation into structured, machine-actionable knowledge through robust NLP pipelines and transformer based applications. This position supports flexible remote work, collaboration with cross functional teams, and hands on work with cutting edge AI tooling.

Benefits

• Paid Time Off
• Paid Company Holidays
• Medical, Dental & Vision Insurance
• Optional Health Savings Account and Flexible Spending Account
• Base and Voluntary Life Insurance
• Short Term and Long Term Disability Insurance
• 401k Matching
• Employee Assistance Program

Responsibilities

• Design, build, and maintain NLP pipelines for technical and structured document understanding, covering information extraction, summarization, semantic search, and question answering.
• Develop and optimize LLM driven applications using transformer models, including fine-tuning, prompt design, and retrieval augmented generation (RAG) architectures.
• Analyze complex technical corpora such as engineering manuals, specifications, technical reports, drawings, tables, and figures.
• Create methods to convert unstructured and semi-structured documents into structured, machine-actionable knowledge for downstream use.
• Deploy scalable machine learning solutions with Python and modern frameworks like PyTorch and Hugging Face.
• Assess model performance, drive accuracy improvements, and optimize inference pipelines for production environments.
• Collaborate with software engineers, data scientists, and subject matter experts to define requirements and deliver AI enabled document intelligence solutions.
• Perform other duties as assigned.

Requirements

• Bachelor's degree in Computer Science, Data Science, AI/Machine Learning, or a related technical field, or equivalent practical experience.
• 2 to 4 years of experience building NLP pipelines for technical or structured document understanding, including extraction, summarization, semantic search, and question answering.
• Hands-on experience with large language models and transformer architectures (including BERT and successors), covering fine-tuning, prompt engineering, pipeline orchestration, and retrieval augmented generation.
• Experience processing complex technical documentation such as engineering manuals, specifications, technical artifacts, tables, and figures.
• Strong proficiency in Python and modern ML frameworks, including PyTorch and Hugging Face Transformers.
• Proven ability to convert unstructured text into structured, machine-actionable knowledge.
• Currently holds an active U.S. national security clearance or the ability to obtain and maintain one.

Technologies

• Python
• PyTorch
• Hugging Face Transformers
• BERT

Physical Requirements

• Prolonged periods sitting at a desk and working on a computer
• Must be able to lift up to 15 pounds at times

Clearance Requirements

Some positions require access to U.S. National Security information. Roles requiring this access will necessitate receiving and maintaining a U.S. government personnel security clearance. In order to qualify, candidates must be U.S. citizens with current eligibility or the ability to complete the investigation process and maintain eligibility throughout employment.

EEOC and Know Your Rights

Lyntris is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, or any other status protected by applicable federal, state, and local law. Employment decisions are based on merit, qualifications, and business needs. For more information, please consult our policies.

Preferred Qualifications (Not Required)

• Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related field
• Experience deploying and maintaining production scale NLP or LLM applications
• Familiarity with vector databases, embedding models, and semantic retrieval systems
• Experience with document parsing, OCR, layout-aware models, or multimodal document understanding
• Experience working with engineering, manufacturing, aerospace, defense, or other highly technical datasets
• Knowledge of MLOps practices, model monitoring, CI/CD pipelines, and cloud-based AI infrastructure
• Active duty military experience