Senior Research Data Scientist

Jobtailor; San Diego (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Jobtailor in San Diego, CA is seeking an experienced machine learning researcher to advance computer vision and vision-language models from prototype to production. You will handle data curation, augmentation, and synthetic data generation while collaborating with engineering and product teams.

Candidates should have a strong foundation in modern CV and DL, including CNNs and vision transformers, plus hands-on Python and PyTorch experience.

Qualifications

• Master’s or PhD in CS/EE/Robotics/ML, or related industry experience.
• Strong CV and DL fundamentals across detection, segmentation and tracking.
• Experience with real-world visual data, data quality analysis and augmentation.
• Ability to read, implement and build on recent research papers.

Responsibilities

• Research, prototype, and develop state-of-the-art CV and DL models for detection, segmentation, tracking, and vision-language tasks.
• Translate research into working implementations, reproduce baselines, run ablations, and quantify tradeoffs.
• Own the data lifecycle for visual tasks: dataset curation, annotation strategy, augmentation, synthetic data generation, and quality analysis.
• Collaborate with engineering and product teams to move models from prototype to production, including edge/latency optimization.
• Communicate methods, results, and tradeoffs clearly to technical and non-technical stakeholders.

Skills

Python

PyTorch

Computer Vision

Deep Learning

Mathematics

Edge Deployment

Research Reading

Education

Master’s or PhD in CS/EE/Robotics/ML

Tools

PyTorch

Job description

Responsibilities

• 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

• 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.