Senior Staff / Senior Machine Learning Engineer

SciTec Incorporated

Boulder (CO)

Hybrid

USD 127,000 - 193,000

Full time

14 days+

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Benefits offered by this job

4% Safe Harbor 401(k) match
Company paid HSA Medical insurance
Dental insurance
Vision insurance
Life insurance
Long-term Disability insurance
Hospital Indemnity insurance
Voluntary Accident and Critical Illn.
Paid Parental Leave
Generous Paid Time Off

Job summary

SciTec seeks a Staff/Senior Staff Machine Learning & AI Engineer in Boulder, CO to design, train, and optimize high‑performing ML models for OPIR sensor data and related national defense applications.

The role emphasizes hands‑on algorithm development, model optimization, and production integration on Linux, within an Agile team. In‑person work at the Boulder office is required.

Qualifications

  • Bachelor's degree in a physical sciences, mathematics, engineering, computer science, or related field.
  • 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 (Mutual Information, Shapley Analysis).
  • Detail oriented with strong problem‑solving skills; good communication.
  • Ability to work full‑time in‑person at the Boulder, CO office; ability to obtain DoD clearance.

Responsibilities

  • Develop and implement ML, DL, and AI algorithms for remote sensor data exploitation.
  • Design, train, and optimize models for image analysis, detection, tracking, and multi‑modal sensor fusion.
  • Deploy high‑performance inference pipelines for large‑volume data processing.
  • Collaborate with C++ and systems engineers to integrate ML/AI into existing software.
  • Apply software engineering practices for reproducibility, performance, and maintainability.
  • Work on an Agile team and contribute to shared tools, workflows, and documentation.
  • Other duties as assigned.

Skills

Python
PyTorch
TensorFlow
scikit-learn
Linux
C++
GPU programming
CUDA
MLOps
Agile
DoD clearance
Data structures

Education

Bachelor's degree in physical sciences, mathematics, engineering, computer science, or related field
MS or PhD (preferred)

Tools

CUDA
cuDNN
TensorRT
ROCm

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
  • 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
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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