Develop and productionize deep learning models for computer vision and NLP on medical imaging products. Design and run experiments, document results, collaborate on data labeling, write deployment/docker code, optimize inference speed, and conduct DL methodology research.
Company Description
Qualifications
Founded in 2016, VoxelCloud is a Los Angeles-based leader worldwide in artificial intelligence (AI) analysis of medical images. Backed by Sequoia and Tencent. We help healthcare providers make better/earlier diagnoses and other clinical decisions. http://www.voxelcloud.ai
Job DescriptionThe R&D team (located in Los Angeles, CA) is involved with creating innovative solutions using deep learning tailored to the needs of the product lines (Thorax/Retina/Cardio/Skin). We are currently hiring a full-time engineer to join our model team.
Responsibilities:
- Develop deep learning models for prototyping and production purposes according to product feature request
- Design, implement and test model experiments using major deep learning frameworks
- Document experiments findings and results with supporting summary statistics for peer discussion and review (Confluence)
- Provide insights to data collection and annotation and collaborate with the data team for in-house data management and labelling
- Write production and deployment code (dockerization), iterate deployed models for optimal performance and inference speed
- Conduct methodology research in deep learning to drive scalable, real-time implementation
Qualifications
Basic Qualifications
- MS degree in computer science, engineering, or mathematics
- 1+ years of relevant experience in building deep learning solutions for computer vision problems
- 1+ years of relevant experience in building deep learning solutions for NLP problems
- Proficient with at least one major deep learning framework, preferably TensorFlow/Pytorch
- Proficient in Python
- Good CS fundamentals in data structures and algorithm
- Detail-oriented, well organized and self-motivated with a continuous drive to learn, explore and be challenged
- Work well in teams and communicate ideas clearly
Preferred Qualifications
- PhD degree in computer science, engineering, or mathematics
- 3+ years of relevant experience in building deep learning solutions for computer vision problems
- 2+ years of relevant experience in building deep learning solutions for NLP problems
- Hands-on experience with Transformers, Bert, and other advanced NLP models
- Hands-on experience with state-of-the-art object detection, semantic segmentation, and image classification models
- Track record of publications in CV and NLP is a plus
- Hands-on experience with model optimization (e.g., network quantization and half-precision training) is a plus
- Prior experience with medial images is a plus
- Prior experience with medial report mining is a BIG plus
We Offer…
- An outstanding start-up culture;
- Transparent, collaborative work environment;
- Competitive compensation
- Excellent Medical, Dental, and Vision coverage
- 401k, paid Vacation and Holiday
All your information will be kept confidential according to EEO guidelines.
Similar Jobs
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Develop and productionize GenAI, LLM, machine learning, and analytics solutions for ASIC semiconductor engineering. Build agentic systems, RAG workflows, predictive models, and failure-analysis tools; deploy and monitor AI solutions in cloud and enterprise environments; collaborate with architecture, design, data science, and IT teams; and communicate technical findings while identifying opportunities to improve engineering productivity, quality, cost, and cycle time.
Top Skills:
AWSAzureClaude CodeCSSCursorDeep LearningGCPGemini CliGraph-RagHTMLJavaScriptLlmsMachine LearningMatplotlibPandasPlotlyPythonRagScikit-Learn
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Develops and executes enterprise SSD firmware validation across development, qualification, and sustaining phases. Designs tests for firmware features, NVMe protocols, security capabilities, and system behaviors; analyzes regressions, customer issues, and field-return failures to identify root causes. Builds Python automation, regression frameworks, and coverage reporting while collaborating with firmware engineers, data scientists, and global teams on debugging, design reviews, and AI-enabled testing improvements.
Top Skills:
AesCi/CdDice/CmaEccEnterprise SscNvmePciePost-Quantum CryptographyPythonRsaSecure BootSha-2Sha-3SpdmSsd FirmwareTcg Opal
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Develop GenAI, machine learning, deep learning, and analytics solutions for ASIC semiconductor engineering workflows. Build LLM and agentic systems using prompting, RAG, Graph-RAG, benchmarking, and evaluation. Deploy and monitor production AI/ML solutions in cloud and enterprise environments, collaborate with architecture, design, data science, and IT teams, and communicate technical insights to diverse stakeholders.
Top Skills:
AWSAzureClaude CodeCSSCursorGCPGemini CliGraph-RagHTMLJavaScriptLlmsMatplotlibPandasPlotlyPythonRagScikit-Learn
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering

.jpeg)