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Computer Vision, Machine Learning Engineer
Buzz Solutions. Stay current with ML/CV research, identify promising methods, and evaluate their applicability to our domain .
Tech Stack
Tools & technologiesPython
About the role
Key responsibilities & impact- Stay current with ML/CV research, identify promising methods, and evaluate their applicability to our domain
- Adapt and implement algorithms from papers, validating against baselines and benchmarking for production viability
- Own and deliver end-to-end computer vision projects focused on:
- Design and execute experiments with systematic hyperparameter tuning, ablation studies, and appropriate baselines
- Perform structured error analysis: categorize failure modes (false positives, missed detections, localization errors, misclassifications) and break down performance by data slices (object size, occlusion, image quality)
- Select and justify model architectures based on task requirements, latency, and accuracy tradeoffs
- Design and implement data pipelines including ingestion, preprocessing, annotation workflows, and quality monitoring
- Experiment tracking and model versioning (configurations, random seeds, dataset versions, environment specs, and model checkpoints)
- Build model serving pipelines that meet latency and throughput requirements
- Conduct thorough code reviews and write integration tests for ML pipelines
- Communicate research findings, technical decisions, and model limitations clearly to stakeholders
Requirements
What you’ll need- 2-4 years of industry experience in computer vision and machine learning
- Solid understanding of modern computer vision and deep neural networks including:
- Demonstrated ability to read ML research papers, extract key ideas, and implement them
- Experience adapting published methods to specific use cases and validating against baselines
- Experience selecting, fine-tuning, and adapting model architectures (CNNs, transformers, foundation models) for specific use cases
- Ability to debug training instabilities and conduct systematic error analysis
- Proficiency in Python and core ML libraries:
- Strong software engineering practices:
Benefits
Comp & perks- * Buzz Solutions does not provide Visa sponsorship for work authorizations in the United States at this time *
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningcomputer visiondeep neural networkshyperparameter tuningerror analysismodel architecturesdata pipelinesmodel servingPythonML libraries
Soft Skills
communicationproblem-solvinganalytical thinkingattention to detailcollaboration