Deep Learning Engineer
Quick Summary
NeuroVector Systems is seeking a Deep Learning Engineer to design, implement, and optimize advanced neural network architectures for large-scale applications. This role is perfect for candidates who enjoy experimenting with deep learning models and applying them to real-world challenges across industries.
Project Category or Industry
Artificial intelligence, software development, and applied research.
Type
Full-time employment.
Experience Level
Entry to mid level, with opportunities for fresh graduates who have completed impactful projects in deep learning, while also welcoming experienced engineers ready to contribute to high-impact AI systems.
Duration
Ongoing, long-term position.
Location
Remote with flexible scheduling. Team members are expected to have at least four hours of overlap with US Eastern or Central European time zones.
Salary
USD 95,000–130,000 annually, with performance-based bonuses and professional development support.
Payment Mode
Monthly salary with additional performance incentives.
Hiring Company Name
NeuroVector Systems.
Required Skills or Tools
Applicants should be proficient in Python, with strong experience using PyTorch or TensorFlow for deep learning tasks. Familiarity with CUDA, distributed training, and cloud platforms such as AWS or GCP is highly desirable. A solid understanding of mathematics, particularly linear algebra and optimization, is essential.
Project Description
The Deep Learning Engineer will focus on building, training, and deploying neural networks that address complex problems in areas such as natural language processing, computer vision, and recommendation systems. The role emphasizes experimentation, scalability, and innovation.
Core Responsibilities and Expected Deliverables
Key responsibilities include designing novel neural architectures, optimizing model training, evaluating model performance, and deploying models into production environments. Deliverables will include reproducible codebases, performance benchmarks, and production-ready AI systems.
Required Experience and Preferred Qualifications
A bachelor’s or master’s degree in computer science, artificial intelligence, or a related field is required. Candidates with experience in publishing applied research or participating in AI competitions will be given preference. Industry certifications in deep learning frameworks are considered an asset.
Tools or Platforms to Be Used
PyTorch, TensorFlow, Python, CUDA, GitHub, and cloud-based GPU training environments on AWS or GCP.
Language Requirement
English fluency is mandatory for collaboration and documentation. Additional languages are welcomed but not required.
Communication Style
The team collaborates via Slack and Zoom for daily check-ins, Jira for project management, and email for formal communications and reporting.
Time Commitment or Working Window
Forty hours per week with flexibility. Engineers must align with project timelines and attend scheduled sprint reviews and research discussions.
Payment Terms
Fixed monthly salary with annual performance-based bonuses. Additional support is provided for attending technical conferences or workshops.
Evaluation Criteria
Candidates will be evaluated based on technical proficiency, problem-solving skills, and their ability to deliver scalable AI solutions. Code quality, reproducibility, and creative model experimentation will be key factors in selection.
Other Requirements
Successful candidates will be required to sign an NDA. Time-tracking for resource allocation and progress monitoring may be necessary depending on project requirements.
About the Company
NeuroVector Systems is an AI-focused technology company that specializes in creating advanced deep learning solutions for industries including healthcare, finance, and autonomous systems. Founded in 2016 and headquartered in San Francisco, the company has grown into a global, fully remote team with research hubs across North America and Europe. Its mission is to deliver scalable, ethical, and high-performance AI systems that drive innovation. More information is available at https://neurovectorsystems.com or via email at careers@neurovectorsystems.com.