Experienced Machine Learning Customer Solutions Engineer – AI Foundation Model Integration and Technical Client Support Specialist

Introduction to blithequark blithequark is at the forefront of innovation in medical imaging, developing the first multimodal AI foundation model. Our deep learning platform, unique for its proprietary privacy-compliant trust architecture, integrates diverse data sources with cutting-edge AI/ML development. blithequark is co-founded by a visionary leader with a prolific background including founding various successful ventures and former roles at renowned companies. As a pioneer in the field of medical imaging and AI, blithequark is committed to revolutionizing the healthcare industry through its groundbreaking technologies. Job Overview The Machine Learning Customer Solutions Engineer will play a crucial role in supporting healthcare organizations in integrating machine learning foundation models into their radiological clinical software. This involves assisting with model fine-tuning, prompt engineering, and pre-sales activities such as delivering demos. The ideal candidate will possess a blend of technical expertise, client engagement, and strong collaboration and communication skills to ensure successful implementation and optimal clinical outcomes. Key Responsibilities Fine-Tuning: Collaborate with clients to fine-tune foundation models for specific radiology tasks (e.g., anomaly detection, image segmentation) using various fine-tuning methodologies such as prompt engineering, parameter-efficient fine-tuning, etc. Pre-Sales Support and Demos: Partner with client experience to deliver demos and facilitate technical discussions, highlighting the foundation model’s capabilities to potential clients. Client Support and Integration: Serve as the primary technical contact for our clients, working closely with application developers and serving as a trusted advisor to implement solutions using our foundation models. Workflow Optimization: Ensure AI models fit seamlessly into radiological workflows, optimizing outputs for clinical decision-making. Cross-Functional Collaboration: Work closely with product, engineering, and client engagement teams to address client needs and feedback. Assist in translating complex technical findings into actionable insights and recommendations for non-technical stakeholders, contributing to impactful business decisions. Documentation: Assist with development of technical materials, including integration guides, training documents, and best practices for model fine-tuning. Solicit, summarize and document platform and tooling requirements and feature requests for the product development team. Preparation of model details to be used for client regulatory documentation as it relates to specific fine-tuning use cases. Essential Qualifications Experience: 7-10 years’ total experience, including 3-5 years in a technical client-facing role with previous experience working on machine learning projects and industry knowledge of standard technologies in the machine learning space. Technical Skills: Proficiency in Python, machine learning frameworks (e.g., TensorFlow, PyTorch), and understanding of radiological software (PACS, DICOM). Communication: Strong ability to explain and present complex technical concepts to both technical and non-technical stakeholders. Education: B.S. degree in a quantitative field such as Computer Science, Engineering, or comparable degree/experience. Preferred Qualifications Experience with generative LLM fine-tuning and prompt engineering. Experience with cloud native architecture, including machine learning model development and deployment, in a client-facing or support role. Experience with RESTful APIs, radiology workflow orchestration tools, and medical interoperability standards is a plus. Familiarity with pre-sales processes, including delivering demos, gathering requirements, and customizing solutions for clinical environments. Previous experience within a team that underwent a high growth stage. Career Growth Opportunities and Learning Benefits At blithequark, we are committed to providing our employees with opportunities for growth and development. As a Machine Learning Customer Solutions Engineer, you will have the chance to work on cutting-edge technologies, collaborate with a talented team of professionals, and contribute to the development of innovative solutions that transform the healthcare industry. You will also have access to training and development programs, mentorship, and opportunities to expand your skill set and expertise. Work Environment and Company Culture blithequark is dedicated to creating a diverse, inclusive, and supportive work environment that fosters collaboration, creativity, and innovation. Our company culture values openness, transparency, and respect, and we strive to create a workplace where everyone feels valued, empowered, and motivated to contribute their best work. We believe in maintaining a healthy work-life balance and offer flexible working arrangements, recognition and reward programs, and a comprehensive benefits package to support the well-being of our employees. Compensation, Perks, and Benefits blithequark offers a competitive salary and benefits package, including a range of perks and benefits designed to support the well-being and success of our employees. These may include health insurance, retirement plans, paid time off, and opportunities for professional development and growth. Conclusion If you are a motivated and talented professional with a passion for machine learning, client support, and technical collaboration, we encourage you to apply for the Machine Learning Customer Solutions Engineer role at blithequark. This is an exciting opportunity to join a fast-growing startup with immense potential, work on cutting-edge technologies, and contribute to the development of innovative solutions that transform the healthcare industry. Apply now to take the first step in your journey with blithequark and discover a career that is both challenging and rewarding.