Sr. Machine Learning Engineer (Computer Vision)PeopleConnect Staffing • San Francisco, CA, United States
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Sr. Machine Learning Engineer (Computer Vision)
PeopleConnect Staffing • San Francisco, CA, United States
[job_card.variable_days_ago]
[job_preview.job_type]
- [job_card.full_time]
[job_card.job_description]5+ years of experience designing, building, and maintaining production machine learning models and pipelines in the cloud. 3+ years of experience in computer vision in real‑world applications. 2+ years of industry experience with Python. Deep understanding of best practices in machine learning and MLOps around data quality (including annotations), monitoring, scalability, and maintainability. Strong grasp of computer vision fundamentals. Proficiency in relevant deep learning frameworks (e.g., TensorFlow, PyTorch). Strong software engineering fundamentals, with the ability to write clean, reliable code. Track record of independent problem‑solving and the ability to proactively drive projects to completion. Demonstrated ability and willingness to quickly acquire new technical skills to meet project demands. Strong communication, collaboration, and organizational skills. Interest in building impactful products in the health sector. Familiarity with a startup environment. Experience working with sensitive health data or datasets governed by HIPAA, GDPR, or other regulatory frameworks. Proficiency with AWS systems. Experience in the healthcare spaces such as medical devices or clinical data. Data engineering experience, including annotation workflows and managing large‑scale labelled datasets. Competitive salary and equity participation. Healthcare and 401(k) benefits. Flexible work environment with hybrid office structure. Mission‑driven, collaborative team. Work on modern technology that integrates hardware, software, and data science to improve lives. Opportunity to contribute to regulatory‑grade validation of AI / ML models in healthcare. Benefit from a high degree of ownership and direct impact on the product's success. Contribute as a foundational member of an early‑stage startup poised for significant growth in the wellness IoT and healthtech market.
Job Title : Senior Machine Learning Engineer (Computer Vision)
Office Location : San Francisco, US
Employment Type : Full-time, Hybrid (3 days / week in office)
Compensation : $125,000- $150,000 / year
Our client is a pioneering health technology company based in San Francisco, dedicated to enhancing wellness through innovative in‑home health monitoring solutions. Their flagship product is an AI‑powered smart toilet seat designed to seamlessly integrate into daily routines while providing continuous health insights. Recognized by TIME as one of the Best Inventions of 2024, our client continues to lead in transforming everyday habits into opportunities for better health.
They are seeking a Machine Learning Engineer (Computer Vision) to join their lean and agile team. This role involves ownership of their computer vision and other machine learning algorithms from design, development, testing, and deployment. You will be instrumental in building new product features, working independently within a collaborative startup environment.
Responsibilities
- Lead the design, development, testing, and deployment of their computer vision and other machine learning systems, including model training, MLOps pipelines, and inference.
- Build, optimize, and maintain robust machine learning pipelines leveraging cloud infrastructure (AWS preferred).
- Train, validate, and deploy computer vision models on real‑world clinical trial datasets.
- Implement monitoring systems to ensure model performance, accuracy, and reliability in production healthcare environments.
- Work cross‑functionally within infrastructure, software, and product teams on system‑wide architecture and feature development.
- Contribute to regulatory documentation and validation efforts in support of clinical trials.
Qualifications
Preferred Qualifications
Benefits and Perks
If interested, please send your resume to adam@peopleconnectstaffing.com.
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