Machine Learning and Python SME
At a glance
Mid-level Machine Learning Engineering role at Avalore, LLC. Chantilly · full-time · no salary stated · we estimate $154,463–$174,413.
Avalore, LLC has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Build and assess Python models for text classification and topic modeling, then improve their performance
- Choose NLP methods and preprocessing steps, evaluate model results, and explain those choices to senior leaders
- Analyze personnel, intelligence and performance data with statistical methods to develop research findings
- Help define performance measures, gather and analyze supporting data, and present the results to senior leadership
What you bring
- You hold an active security clearance with the appropriate polygraph
- You have hands-on or academic NLP experience using Python libraries, deep learning frameworks and HuggingFace Transformers
- You have built Python text classification and topic modeling models using Scikit-learn or deep learning approaches
- You can use SQL for queries involving common table expressions, aggregations and nested subqueries
Who this fits
This mid-level, onsite role suits someone who can turn technical model results and statistical analysis into clear findings for customers and senior leaders. The work involves extended time at a computer and occasional travel of up to ten percent.
From the employer
Avalore, LLC is seeking a Machine Learning and Python Subject Matter Expert (SME) to support advanced data analytics, natural language processing (NLP), and machine learning initiatives for US Government customers. The ideal candidate will have demonstrated experience developing, evaluating, and optimizing machine learning models using Python, deep learning frameworks, and modern NLP techniques. This role will leverage advanced statistical analysis, data engineering, and performance measurement methodologies to transform complex datasets into actionable insights, support data-driven decision-making, and communicate technical findings and recommendations to senior leadership.
Requirements
- Active Security Clearance with appropriate Polygraph
- Demonstrated professional or academic experience performing NLP tasks, including selecting the best Python libraries for a given task, choosing appropriate pre-processing actions, performing analysis, and assessing model performance.
- Demonstrated professional or academic experience using Python NLP packages such as Spacy, Gensim, or NLTK to analyze or process collections of documents.
- Demonstrated professional or academic experience with deep learning frameworks such as PyTorch, Tensorflow, or Keras
- Demonstrated professional or academic experience with the HuggingFace Transformers library and hub.
- Demonstrated experience creating machine learning models that conduct text classification and topic modeling in Python using standard machine learning (Scikit-learn) or deep learning models.
- Demonstrated academic or professional experience using encoder-decoder and generative language models to perform NLP tasks.
- Demonstrated academic or professional experience communicating methodological choices and model results.
- Demonstrated professional or academic experience and proficiency with SQL to include using common table expressions, set operations, aggregated functions and nested subqueries.
- Demonstrated professional or academic experience with version control systems such as Github and Jenkins.
- Demonstrated experience leveraging GPUs for accelerated computing.
- Develop practical approaches for measuring performance.
- Assist in developing types of measure, the collection of data, analyzing the data, and presenting that data to senior leadership.
- Conduct advanced statistical analysis on personnel, intelligence, and performance metrics.
- Assist in selection or development of appropriate methodology to conduct research.
- Analyze information and provide research findings in a manner that is easily grasped by the customer and consumers.
Desired:
- Demonstrated experience writing Python scripts that pull data from web-based APIs and relational databases.
- Demonstrated experience with cloud computing development and architecture
- Demonstrated experience with front-end web development frameworks such as Flask.
- Demonstrated experience developing applications for semantic search.
- Demonstrated experience tuning LLMs on custom data sets and applying results to specific use cases.
- Demonstrated professional or academic experience and proficiency with Tableau to produce visualizations and dashboards.
Work Environment:
- Moderate noise (i.e. business office with computers, phone and printers) and /or occasional Loud noise (airfield, large equipment).
- Ability to sit at a computer terminal for an extended period of time.
Physical Demands:
- While performing the responsibilities of the job, the employee is required to sit, stand, talk, and hear.
- Employee is often required to sit and use their hands and fingers to operate a computer.
- Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Travel:
- Up to 10%/ Occasional travel.
Avalore will provide reasonable accommodations to applicants who are unable to utilize our online application system due to a disability. Please send your request to hr@avalore.ai.
Avalore is an Equal Opportunity Employer - We not discriminate based on age, race, national or ethnic origin, gender, veterans status, disability, sexual orientation, gender identity or any other legally protected class. Applicants have rights under Federal Employment Laws.
Benefits
Eligibility requirements apply.
- Employer Contributions to Health Care Plan (Medical, Dental & Vision)
- Retirement Plan (401k, IRA) with a generous matching program
- Life Insurance (Basic, Voluntary & AD&D)
- Paid Time Off (Vacation, Sick & Public Holidays)
- Short Term & Long Term Disability
- Training & Development
- Employee Assistance Program
- Salary at Avalore is determined by various factors, including but not limited to location, the individual's particular combinaition of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements.