Senior Computer Vision, Machine Learning Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of and deliver comprehensive computer vision projects aimed at detecting equipment defects, identifying thermal anomalies, monitoring vegetation encroachment, and overseeing closed areas for human and animal intrusion.

• Define, plan, and execute projects from the initial problem identification to production deployment and ongoing monitoring.

• Translate client needs and raw data into functional computer vision solutions to successfully deliver projects.

• Collaborate on shared team projects and work with other engineers to achieve common goals.

• Keep up with the latest ML/CV research, pinpoint promising techniques, and assess their relevance to the field.

• Modify and implement algorithms based on research findings, validating against benchmarks for production readiness.

• Leverage advancements in deep learning and generative AI to enhance model training, accuracy, and reliability.

• Design and carry out experiments involving hyperparameter tuning, ablation studies, and suitable baselines.

• Conduct structured error analysis across different failure modes and data segments.

• Choose and justify model architectures based on task requirements, considering latency and accuracy trade-offs.

• Create production-grade Python libraries that encompass the entire ML lifecycle.

• Develop and implement data pipelines for data ingestion, preprocessing, annotation workflows, and quality assurance.

• Manage experiment tracking and model versioning processes.

• Build model serving pipelines that meet latency and throughput expectations.

• Perform code reviews and write integration tests for ML pipelines.

• Share insights and contribute to best practices regarding model development, evaluation, deployment, and monitoring.

• Maintain software quality standards within the ML team.

• Effectively communicate research findings, technical decisions, and model limitations to stakeholders and clients.

⛳️ Requirements

• 5–10 years of experience in the fields of computer vision and machine learning.

• Profound knowledge of modern computer vision and deep neural networks, including object detection, semantic segmentation, image classification, vision transformers, foundation models, vision language models, and similarity search.

• Demonstrated success in deploying and maintaining ML models in a production environment.

• Experience in selecting, fine-tuning, and adapting CNN, transformer, and foundation model architectures for specific applications.

• Proven ability to comprehend ML research papers, extract vital concepts, and implement them effectively.

• Skill in troubleshooting training instabilities and performing systematic error analysis.

• Proficient in Python and the essential ML stack: PyTorch and Lightning, OpenCV, NumPy and pandas, Scikit-Learn, FastAPI, and Pydantic.

• Strong commitment to software engineering best practices, including Git, unit and integration testing using Pytest, CI/CD pipelines with GitHub Actions, Docker, reproducible environments, experiment tracking, model versioning, ML DevOps, and Python type hinting.

• Proven capability to independently manage technical projects from problem framing to production deployment.

• Authorization to work in the United States; this position does not offer sponsorship.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Generous paid time off and holidays.

• Opportunities for professional development and continuous learning.