Research Assistant Deep Learning Jobs in Atlanta, GA

We are seeking a Senior Computer Vision / Deep Learning Scientist to design, develop, and deploy advanced computer vision and deep learning solutions for unique, high-impact applications. The successful candidate will combine strong theoretical knowledge with hands‑on industry experience to develop novel algorithms, custom deep learning architectures, and production‑ready machine learning solutions. This role will be a key contributor to a Digital Train Inspection project, applying computer vision and deep learning techniques to analyze visual data and support automated inspection capabilities.

The Senior Scientist will own the model development lifecycle from requirements gathering and data evaluation through model development, validation, production integration, and post‑production support. The role requires close collaboration with application development teams, business stakeholders, and senior leadership, as well as the ability to provide technical guidance to junior team members and lead targeted research initiatives.

• Hybrid schedule: Two days onsite each week for candidates located in the Atlanta area.
• Fully remote option available for candidates located outside the Atlanta area.

• Design, develop, and implement novel computer vision algorithms for specialized and unique use cases.
• Design and build custom deep learning architectures tailored to specific business and technical requirements.
• Develop and apply deep learning models for semantic segmentation, object detection, image classification, and related computer vision applications.
• Evaluate model accuracy, robustness, quality, and performance, as well as the quality and suitability of underlying data sources.
• Develop clean, scalable, maintainable, and production‑ready Python and machine learning code.
• Partner with application development teams to integrate computer vision and deep learning models into existing applications and production environments.
• Own the complete model development lifecycle, including requirements gathering, data assessment, experimentation, model development, validation, deployment, monitoring, and post‑production support.
• Conduct research and experimentation to identify and implement new computer vision and deep learning techniques.
• Communicate technical findings, model performance, research results, and recommendations clearly to colleagues, business partners, and senior management.
• Provide technical guidance and mentorship to junior team members and oversee targeted research and team projects.
• Contribute to hiring initiatives, including technical candidate evaluation, interviews, and assessment of prospective team members.
• Collaborate across technical and business functions to translate complex computer vision challenges into practical, scalable solutions.

• Bachelor’s, Master’s, or Ph.D. in Computer Science, Electrical Engineering, Machine Learning, Statistics, or a related technical field.
• 1–3 years of relevant industry experience in a role such as Computer Vision Scientist, Data Scientist, Research Scientist, Machine Learning Scientist, or similar; 3+ years of experience is preferred. Candidates with equivalent proven qualifications may also be considered.
• Excellent programming skills in Python, with demonstrated experience developing machine learning or deep learning solutions in an industry environment.
• Hands‑on industry experience with PyTorch or another major deep learning framework.
• Strong practical experience applying deep learning techniques to computer vision problems, including semantic segmentation, object detection, and image classification.
• Ability to evaluate model performance and data quality and translate findings into actionable improvements.
• Experience developing production‑ready machine learning solutions and collaborating with software/application development teams.
• Strong analytical, problem‑solving, communication, and research skills.

• 3+ years of professional experience in computer vision, machine learning, deep learning, or a closely related discipline.
• Experience taking machine learning models from research or experimentation into production.
• Experience working with large‑scale visual datasets and establishing data quality and model evaluation processes.
• Experience mentoring technical professionals or leading research‑oriented projects.
• Experience participating in technical recruiting, interviewing, or candidate evaluation.

The selected candidate will contribute to a Digital Train Inspection initiative, developing computer vision and deep learning capabilities that support automated analysis of train and rail‑related visual inspection data. The work will involve applying advanced image analysis and machine learning techniques to identify, classify, segment, and evaluate visual conditions relevant to inspection and maintenance workflows.

• Python
• PyTorch or comparable deep learning frameworks
• Computer Vision
• Semantic Segmentation
• Image Classification