Biomedical Engineer

Overview

Credence is seeking a Biomedical AI Engineer to develop artificial intelligence and machine learning (AI/ML) models using multimodal biomedical and healthcare data. You will leverage your experience making data AI-ready and design, develop, and implement AI models and ML algorithms to support biomedical research. This onsite role is in McLean, VA.

Credence supports clients’ mission-critical needs with technology, including AI/ML and advanced intelligence capabilities, for the largest federal health and defense organizations. Credence is privately held, recognized as a top place to work, and has appeared on the Inc. 5000 Fastest Growing Private Companies list for 12 consecutive years. We practice servant leadership to focus on the success of clients, team members, and partners.

Responsibilities

• Build AI models and pipelines for biomedical and healthcare applications
• Develop multimodal AI algorithms using data types such as medical imaging data, electronic health records (EHR) data, multiomics data, and wearable device data
• Conduct data preparation, feature engineering, model selection, training, and optimization to ensure optimal AI model performance
• Design and implement AI solutions using Generative AI technologies and foundation models / large-language models (LLMs)
• Collaborate with cross-functional teams of data scientists, software engineers, program managers, and client stakeholders to understand, evaluate, and deliver AI solutions that meet project requirements
• Stay updated on AI/ML trends and write clean, maintainable, and well-documented code following industry standards
• Contribute to the technical writing of AI/ML-related proposals and white papers

Education, Requirements and Qualifications

• Ph.D. (preferred) or M.S. in an engineering, scientific, or health-related field
• Minimum 3 years relevant work experience (Ph.D.) or 7 years relevant work experience (M.S.)
• Experience implementing multimodal AI with at least 2 (preferably 3) of the following data types: medical imaging data, EHR data, multiomics data, and wearable device data
• Understanding of data types, standards, and data models used for medical imaging, EHR, multiomics, and wearable device data
• Successful track record of performing AI/ML research and development in the biomedical/healthcare space, as evidenced through publications and/or other relevant outcomes
• Strong knowledge of AI/ML techniques including natural language processing (NLP), supervised, unsupervised, and reinforcement learning, with expertise in Python, AI/ML libraries, and basic LLM concepts
• Strong problem-solving skills and the ability to work both independently and as part of a team
• Excellent communication skills, with the ability to convey complex technical concepts to non-technical stakeholders

Working Conditions

Onsite or Hybrid options may be available per role requirements.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Consulting
• Information Technology
• Engineering

Industries

• IT Services and IT Consulting
• Software Development
• Biotechnology Research

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Incentives and benefits commonly inferred include medical insurance, vision insurance, 401(k), pension plan, paid parental leave, student loan assistance, tuition assistance, disability insurance, and paid maternity leave.

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