Senior Machine Learning Engineer

Responsibilities

• check_circle Build, train, evaluate, and deploy computer vision and multimodal models, taking them from early prototype through to production
• check_circle Design systems that infer structured attributes and spatial context from imagery, combining learned models with geometric and heuristic reasoning
• check_circle Train and fine-tune models on large, diverse real-world image datasets, and build the pipelines to curate and label that data at scale
• check_circle Work with vision-language models (VLMs) and build rigorous evaluation frameworks to measure their accuracy on our tasks
• check_circle Develop and benchmark high-performance image retrieval capabilities with embedding models and vector indexing strategies
• check_circle Optimize models for inference latency and throughput using techniques like distillation, quantization, and GPU acceleration
• check_circle Read current research, prototype novel algorithms from academic literature, and turn promising ideas into reliable production code
• check_circle Implement efficient, scalable data pipelines and inference infrastructure
• check_circle Develop high-performance tooling in ML and data engineering
• check_circle Additional duties and responsibilities as reasonably required by the employee’s supervisor or CEO
• check_circle Experience building, training, evaluating, and deploying ML models in production
• check_circle Strong experience using PyTorch, JAX, or other deep learning frameworks to develop and optimize models
• check_circle Strong software engineering ability to build and maintain complex systems and work with large-scale datasets
• check_circle Ability to solve open-ended problems and quickly learn new domains
• check_circle Comfort operating with significant ownership and autonomy, making pragmatic trade-offs between model sophistication, velocity, inference and business constraints
• check_circle BS, MS, or PhD in Computer Science or a related technical field, or equivalent practical experience

Preferred qualifications

• Experience inferring structured, real-world attributes from images
• Experience training models on large-scale, real-world image datasets
• Familiarity with vision-language models (VLMs)
• Ability to digest academic literature, prototype novel algorithms, and bridge the gap between research and production code
• Experience building LLM or VLM pipelines and the evaluation frameworks to measure their performance
• Experience in an ML role at a growth-stage startup
• Publications in major ML or computer vision conferences (e.g., CVPR, ICML, ICCV, WACV)

Benefits

• check_circle Medical, Dental, Vision, STD and LTD Plans
• check_circle FSA - Medical and Dependent Care
• check_circle EAP and wellness programs
• check_circle 13 Paid Holidays
• check_circle Unlimited PTO
• check_circle Flexible work environment - 100% remote
• check_circle 401(k) plan

About the company