Gardner Resources Consulting, LLC
Senior Machine Learning Engineer, Perception R&D
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Machine Learning Engineer, Perception R&D, offering a hybrid work location. Contract length and pay rate are unspecified. Key skills include 5+ years in computer vision, deep learning, Python, PyTorch, and experience with modern architectures and real-world perception challenges.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
January 30, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Hybrid
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Boston, MA
-
🧠 - Skills detailed
#GCP (Google Cloud Platform) #ML (Machine Learning) #Supervised Learning #Cloud #AWS (Amazon Web Services) #Deep Learning #"ETL (Extract #Transform #Load)" #AI (Artificial Intelligence) #Python #PyTorch #R #Docker #Transformers
Role description
Senior Machine Learning Engineer, Perception R&D (Hybrid)
• 5+ years in computer vision and deep learning, focused on applied research or advanced R&D
• Hands-on with modern architectures (ViT/Transformers, self-supervised learning, vision-language models, zero-shot detection)
• Strong Python and PyTorch expertise
• Experience tackling real-world perception challenges (occlusion, lighting, reflective surfaces); sound judgment on model vs. heuristic tradeoffs
• Experience with model distillation and quantization
• Able to clearly communicate AI concepts and performance tradeoffs to engineering and product partners
• Familiar with Docker, cloud platforms (AWS/GCP), and experiment tracking tools
Senior Machine Learning Engineer, Perception R&D (Hybrid)
• 5+ years in computer vision and deep learning, focused on applied research or advanced R&D
• Hands-on with modern architectures (ViT/Transformers, self-supervised learning, vision-language models, zero-shot detection)
• Strong Python and PyTorch expertise
• Experience tackling real-world perception challenges (occlusion, lighting, reflective surfaces); sound judgment on model vs. heuristic tradeoffs
• Experience with model distillation and quantization
• Able to clearly communicate AI concepts and performance tradeoffs to engineering and product partners
• Familiar with Docker, cloud platforms (AWS/GCP), and experiment tracking tools
