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4d ago

Senior Staff / Senior Machine Learning Engineer

SciTec Boulder, CO

Boulder, CO

4d ago

$127k - $193k/yr Full time Python Senior Artificial Intelligence

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Job Description

SciTec in Boulder, CO offers onsite work with a robust benefits package and a salary range of USD 127,000 to 193,000 per year. This Senior Staff / Senior Machine Learning Engineer role focuses on designing, training, and optimizing high-performance ML models for remote sensor data, integrating into production Linux software within an Agile team.

Benefits

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

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

Technologies

Python
PyTorch
TensorFlow
scikit-learn
Linux
CUDA
cuDNN
TensorRT
ROCm
C++17/20/23

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

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2mo ago

Machine Learning Engineer

Amazon.com Services LLC Boston, MA

Boston, MA

2mo ago Closed

$144k - $194k/yr Full time Artificial Intelligence Engineer Jax

This position is no longer accepting applications (closed Jun 6, 2026).

Job Description

As an on-site Machine Learning Engineer in Boston, MA, on the Alexa AI team at Amazon, you will contribute to LLM training, production deployment, and optimization, collaborating with Applied Scientists and fellow MLEs to advance generative AI capabilities.