Associate Data Engineer Jobs in Maryland (NOW HIRING)

Job Summary:
Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications. They are seeking a visionary Associate Director of Artificial Intelligence, Modeling, and Data to lead the development and deployment of AI-driven solutions for federal health agencies, overseeing complex modeling and high-dimensional data pipelines.
Responsibilities:
• Architect and execute a comprehensive AI/ML strategy that aligns Axle’s technical capabilities with the NIH Strategic Plan for Data Science (2025–2030).
• Spearhead the evolution of the Polus platform, transitioning it from a robust image analysis tool into a fully integrated, multi-modal research ecosystem.
• Establish and enforce rigorous AI Governance frameworks.
• Direct the design and implementation of high-throughput data pipelines capable of ingesting and analyzing petabyte-scale datasets.
• Oversee the development of predictive models for translational science, focusing on "de-risking" drug discovery and clinical trial design.
• Optimize MLOps and DevSecOps processes to ensure the rapid, secure deployment of models from prototype to production.
• Partner with the Growth and Capture teams to drive new business acquisition.
• Serve as the Lead Solution Architect for major proposal efforts ($50M+).
• Personally write key sections of technical proposals, including the "Technical Approach," "Staffing Plan," and "Risk Mitigation" volumes.
• Galvanize relationships with key federal stakeholders (Project Officers, CIOs, Lab Chiefs).
• Cultivate a high-performance, interdisciplinary team culture.
• Drive continuous learning and upskilling initiatives.
• Democratize access to AI tools within the client environment.
Qualifications:
Required:
• Ph.D. in Computer Science, Bioinformatics, Computational Biology, Data Science, or a related quantitative discipline is highly preferred to ensure peer-level credibility with NIH scientists.
• Alternatively, a Master’s degree in one of the above fields with exceptional, demonstrated leadership experience in a federal or research-intensive setting will be considered.
• 8–10+ years of progressive experience in data science, AI/ML engineering, or computational biology, with a focus on high-dimensional data.
• 3–5+ years of leadership experience managing cross-functional teams (e.g., managing both PhD researchers and software developers) in a matrixed organization.
• Demonstrated experience with Federal Business Development, including writing technical proposals and supporting capture activities for contracts valued at $15M+.
• Proven track record of delivering complex AI/ML solutions in a regulated environment, with specific familiarity with HIPAA, FedRAMP, or NIST AI RMF compliance.
• Expert-level understanding of Deep Learning frameworks (PyTorch, TensorFlow), Classical Machine Learning (Scikit-Learn), and Generative AI architectures (Transformers, LLMs, RAG).
• Proficiency in Python (primary) and R (secondary); familiarity with Java or C++ (for Polus backend optimization) is a strong plus.
• Extensive experience with Cloud-Native AI pipelines on AWS (SageMaker, HealthLake), GCP (Vertex AI, BigQuery), or Azure. Knowledge of the NIH STRIDES initiative and cloud economics is essential.
• Mastery of big data technologies (Spark, Databricks) and workflow orchestration tools (Airflow, Nextflow, Cromwell).
• Strong knowledge of containerization (Docker, Kubernetes), CI/CD pipelines (GitHub Actions, Jenkins), and model monitoring/governance tools.
• Experience with advanced visualization tools (DeepZoom, WebGL) and platform development (building APIs, microservices).
Preferred:
• NIH Ecosystem Experience: Direct experience working with NIH, NCATS, NIAID, or similar federal health agencies. Understanding of the specific data challenges within the federal health sector is highly valued.
• Open Source Leadership: Contributions to or leadership of open-source scientific software projects. Specific familiarity with the Polus platform or the National COVID Cohort Collaborative (N3C) data enclave is a distinct advantage.
• NIST AI RMF Practitioner: Demonstrated experience implementing the NIST AI Risk Management Framework (Map, Measure, Manage, Govern) in a real-world setting.
• Domain Expertise: Specialized knowledge in High-Content Imaging, Cheminformatics, Genomics, or Real-World Data (RWD) analytics.
Company:
At Axle, we are driven by the mission to accelerate discovery and enhance organizational outcomes by revolutionizing operations with our innovative solutions. Founded in 2002, the company is headquartered in Rockville, USA, with a team of 501-1000 employees. The company is currently Late Stage.