Senior Research Data Scientist

Aicadium

Senior Research Data Scientist developing AI-powered computer vision products at Aicadium. Drive applied R&D while collaborating with engineering and product teams in a hybrid role.

Posted 7/14/2026full-timeSan Diego • California • 🇺🇸 United StatesSenior💰 $150,000 - $180,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Expertise in developing and optimizing computer vision and deep learning models, with a strong foundation in image classification, object detection, and segmentation. Proficient in managing the full data lifecycle for visual tasks and effectively communicating complex methodologies to diverse stakeholders.

Highest-signal resume keywords

Computer VisionDeep LearningPython ProgrammingPyTorch FrameworkData Lifecycle Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Image ClassificationObject DetectionSegmentationTrackingSupervised LearningSelf-Supervised LearningRepresentation LearningModel TrainingModel EvaluationApplied Mathematics

Soft Skills

CollaborationCommunication

Certifications & Qualifications

Master’s or PhD in Computer ScienceElectrical EngineeringRoboticsMachine Learning

Industry Keywords

Dataset CurationAnnotation StrategySynthetic Data GenerationQuality AnalysisVision-Language Tasks

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

Research, prototype, and develop state-of-the-art computer vision and deep learning models spanning detection, segmentation, tracking, and vision-language tasks.
Translate recent research into working implementations, reproducing baselines, running ablations, and quantifying practical tradeoffs.
Own the full data lifecycle for visual tasks: dataset curation, annotation strategy, augmentation, synthetic data generation, and quality analysis.
Collaborate closely with engineering and product teams to move models from prototype to production, including optimization for edge or latency-constrained environments.
Communicate methods, results, and tradeoffs clearly to both technical and non-technical stakeholders.

Requirements

What you’ll need

Master’s or PhD in Computer Science, Electrical Engineering, Robotics, Machine Learning, or a related field, or a Bachelor’s with equivalent research or industry experience.
Strong foundation in modern computer vision and deep learning: image classification, object detection, segmentation, and tracking across CNNs, Vision Transformers, vision-language models, and foundation models.
Solid grasp of deep learning fundamentals: supervised and self-supervised learning, representation learning, optimization, loss design, and rigorous model training and evaluation.
Demonstrated ability to read, implement, and build on recent research papers, turning literature into working prototypes.
Hands-on experience with real-world visual data: dataset curation, annotation, augmentation, synthetic data, data-quality analysis, and low-data or noisy-data settings.
Strong applied mathematics (linear algebra, probability, statistics, optimization) and proficiency in Python with PyTorch or equivalent deep learning framework.
Strong collaboration and communication skills — able to work across research, engineering, and product, and present technical work clearly to mixed audiences.

Benefits

Comp & perks

PTO
Heath insurance
Vision and Dental Insurance
Life and AD&D
401k with matching
and more!