Senior Computer Vision Engineer

Aptly Automation is a forward-thinking technology company dedicated to addressing complex real-world challenges through advanced computer vision and data science. Our multidisciplinary team collaborates to develop scalable, production-ready systems that power intelligent products and services. We foster a culture of curiosity, rigorous engineering, and continuous improvement in both research and development. Our fully remote team structure promotes flexibility, inclusivity, and access to diverse talent, offering an environment where you can work with cutting-edge tools, contribute to impactful solutions, and grow professionally.

Key Responsibilities
- Design, develop, and train computer vision models for image and video analysis, including classification, object detection, tracking, and recognition.
- Optimize image processing, pattern recognition, and video-AI pipelines for performance and scalability.
- Build reproducible training pipelines with configuration management, hyperparameter tuning, and experiment tracking.
- Conduct rigorous model evaluation and improve accuracy through iterative data refinement and retraining cycles.
- Export, validate, and optimize models for production deployment, balancing accuracy, latency, throughput, and infrastructure costs.
- Develop and maintain production computer vision services and APIs deployed on cloud and edge platforms.
- Own solutions end to end, from prototyping through production deployment across multiple business workflows.
- Research and prototype innovative approaches to solve complex problems.
- Curate, annotate, and manage image and video datasets.
- Collaborate with cross-functional teams to define requirements and translate them into technical solutions.
- Review and improve existing codebases, contribute to architectural decisions, and promote engineering best practices.
- Mentor team members, conduct code reviews, and maintain clear technical documentation.
- Contribute to the company’s long-term technology strategy.

Required Qualifications
- Bachelor’s degree in Artificial Intelligence, Computer Science, Electrical Engineering, Data Science, or related fields; Master’s degree is a plus.
- Over 5 years of professional experience in computer vision and machine learning, including designing, training, and deploying models in production environments.
- Strong proficiency in Python with solid software engineering fundamentals; C++ experience is advantageous.
- Hands-on experience with PyTorch and related tools such as torchvision and PyTorch Lightning; TensorFlow/Keras knowledge is a plus.
- Practical expertise in image classification (CNNs, transfer learning), object detection (YOLOv8, Ultralytics framework), and familiarity with architectures like Faster R-CNN, Mask R-CNN, RT-DETR, and U-Net. Experience with Detectron2, MMDetection, or Segment Anything (SAM) is beneficial.
- Experience in building video-AI pipelines and multi-object tracking methods such as ByteTrack and DeepSORT.
- Proficiency in computer vision libraries including OpenCV, scikit-image, and Pillow, with knowledge of classical image processing techniques.
- Strong understanding of machine learning and deep learning concepts, including Vision Transformers, loss functions, optimization, and regularization.
- Experience managing and augmenting image/video datasets using tools like Albumentations and Kornia, alongside rigorous model evaluation metrics and experimental design.
- Familiarity with MLOps practices, reproducible training pipelines, and experiment tracking tools such as Hydra, Optuna, MLflow, or Weights & Biases.
- Experience exporting models to ONNX and serving them via production APIs (e.g., FastAPI) with inference optimization.
- Proficiency in data science tools including NumPy, Pandas, scikit-learn, Matplotlib/Seaborn, and Jupyter notebooks.
- Excellent written and spoken English communication skills.
- Ability to work independently and effectively in a remote environment with strong self-management.
- Strong analytical and problem-solving skills with ownership of projects from start to finish.

Preferred Qualifications and Benefits
- Experience with model deployment and optimization tools such as ONNX Runtime, TensorRT, OpenVINO, TensorFlow Lite, NVIDIA Triton, model quantization, pruning, CUDA fundamentals, and edge deployment.
- Familiarity with serving frameworks and API design including FastAPI (async), Flask, and Pydantic.
- Knowledge of MLOps tools and workflows including Docker, Kubernetes, CI/CD pipelines, GitHub Actions, and data version control (DVC).
- Experience with cloud platforms like AWS SageMaker, GCP Vertex AI, or Azure ML, including GPU-based and distributed training.
- Proficiency with annotation tools such as CVAT, Roboflow, Label Studio, or LabelImg.
- Exposure to advanced vision tasks like instance segmentation, anomaly detection, OCR, document understanding, and generative models including diffusion models and vision-language models.
- Strong collaboration skills with experience in version control and multidisciplinary teams.
- Prior leadership experience mentoring engineers or leading technical projects.

What We Offer
- Fully remote, full-time position with flexible work arrangements.
- Opportunities to work with state-of-the-art technologies and contribute to impactful, real-world solutions.
- A supportive and inclusive environment that values curiosity, rigorous engineering, and continuous learning.
- Opportunities to influence technical strategy and mentor a growing team of engineers.

This role is ideal for a seasoned computer vision engineer passionate about building end-to-end solutions and advancing the state of the art in AI-driven visual intelligence.