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Senior Staff / Senior Machine Learning Engineer

SciTec -
Boulder, CO

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Job Details

$127,000 - $193,000 a year

Benefits

Profit sharing
Paid parental leave
Health savings account
Paid holidays
Disability insurance
Health insurance
Dental insurance
Paid time off
401(k) 4% Match
Parental leave
Vision insurance
401(k) matching
Flexible schedule
Life insurance
Paid sick time

Qualifications

Hypothesis testing
Data structures
AI platforms (beyond public GPTs)
Computational framework
Linux
Machine learning libraries
Data performance optimization
Machine learning frameworks
Statistical significance testing
Feature engineering

Full Job Description

SciTec, a wholly owned subsidiary of Firefly Aerospace, is a dynamic non-traditional defense contractor that delivers advanced technologies in support of U.S. National Security and Defense. For the past forty-five plus years, we have supported Department of Defense customers by developing innovative remote sensing algorithms, tools, and techniques to deliver world-class data exploitation capabilities supporting missile

Important Notice: SciTec exclusively works on U.S. government contracts that require U.S. citizenship for all employees. SciTec cannot sponsor or assume sponsorship of employee work visas of any type. Further, U.S. citizenship is a requirement to obtain and keep a security clearance. Applicants that do not meet these requirements will not be considered.

SciTec has an immediate opportunity for a talented Machine Learning & AI Engineer to support our programs delivering Next-Generation Missile Warning software. This is a unique opportunity to join a small business delivering core capabilities for national defense. You will work within a fast‑paced team developing end‑to‑end machine learning and analytics pipelines for Overhead Persistent InfraRed (OPIR) sensor data supporting Missile Warning, Missile Defense, Battlespace Awareness, and Technical Intelligence.

We are seeking a Staff/Senior Staff Machine Learning & AI Engineer to design, train, and optimize high‑performance ML models and algorithms that enhance remote sensor data exploitation and analysis. This role focuses on hands‑on algorithm development, model optimization, and integration into production software systems running on Linux.

The ideal candidate is a strong individual contributor with deep experience in machine learning, high‑throughput data processing, and applied algorithmic development. Success in this role requires technical curiosity, rigorous engineering practices, and the ability to collaborate effectively within a highly technical, Agile team.

Responsibilities

Develop and implement machine learning, deep learning, and AI algorithms for remote sensor data exploitation
Design, train, and optimize models supporting image analysis, detection, tracking, and multi‑modal sensor fusion
Deploy high‑performance inference pipelines for large‑volume, real‑time or near‑real‑time data processing
Collaborate closely with C++ and system-level engineers to integrate ML/AI solutions into existing software frameworks
Apply strong software engineering practices to ensure model reproducibility, performance, and maintainability
Work as part of an Agile team and contribute to shared tools, workflows, and documentation
Other duties as assigned

Requirements

A Bachelor’s degree in the physical sciences, mathematics, engineering, computer science, or a related field
(Additional years of education may be substituted for years of professional experience)
At least five years of professional experience in machine learning, AI engineering, or applied algorithm development
At least three years of experience working in Linux environments
Proficiency with Python and common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
Strong understanding of data structures, numerical methods, and algorithm design
Experience optimizing models and pipelines for high‑data‑throughput processing
Feature engineering and statistical tests, such as Mutual Information and Shapley Analysis
Detail oriented with strong problem‑solving skills
Good verbal and written communication skills
Ability to work full‑time in-person at the Boulder, CO office location
Ability to obtain and maintain a DoD security clearance

Preferred Qualifications

Experience with GPU programming and acceleration (CUDA, cuDNN, TensorRT, ROCm, etc.)
Direct experience applying ML/AI techniques to OPIR, E/O, SAR, Spectral, RF, or other remotely sensed data
Strong understanding of modern software engineering principles, including object‑oriented design and SOLID principles
Experience with production deployment of ML models, MLOps pipelines, or real‑time inference systems
Familiarity with C++17/20/23, especially for model integration or high‑performance compute components
Advanced degree (MS or PhD) in the physical sciences, mathematics, engineering, computer science, or a related discipline
Professional fluency in one or more additional languages: Python, Rust, or C++
Prior experience in Agile software development environments
A current active DoD SECRET clearance or higher

Benefits

SciTec offers a highly competitive salary and benefits package, including:

4% Safe Harbor 401(k) match
100% company paid HSA Medical insurance, with a choice of 2 buy-up options
80% company paid Dental insurance
100% company paid Vision insurance
100% company paid Life insurance
100% company paid Long-term Disability insurance
100% company paid Hospital Indemnity insurance
Voluntary Accident and Critical Illness insurance
Short-term Disability insurance
Annual Profit-Sharing Plan
Discretionary Performance Bonus
Paid Parental Leave
Generous Paid Time Off, including Holiday, Vacation, and Sick Pay
Flexible Work Hours

The pay range for this position is $127,000 - $193,000 / year. SciTec considers several factors when extending an offer of employment, including but not limited to the role and associated responsibilities, a candidate's work experience, education/training, and key skills. This is not a guarantee of compensation.

SciTec is proud to be an Equal Opportunity employer. VET/Disabled

#ND123

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