Machine Learning Engineer (AI) - (Remote - US)
Description • Architect, build, and integrate AI-powered data pipelines that plug directly into existing client infrastructure, ensuring zero-downtime deployments and backward compatibility with legacy systems. • Translate complex business problems into production-grade ML solutions using TensorFlow, PyTorch, scikit-learn, and Hugging Face, delivering measurable ROI within weeks rather than months. • Lead rapid-prototyping sprints (1–2 weeks) that showcase Generative AI, LLMs, and agentic capabilities to non-technical stakeholders, turning abstract ideas into clickable demos that secure follow-on funding. • Embed MLOps best practices—model versioning, automated testing, CI/CD, and real-time monitoring—into every engagement, guaranteeing reliability, reproducibility, and seamless rollback when needed. • Collaborate daily with software engineers, data scientists, product owners, and federal program managers to align AI roadmaps with mission-critical objectives, ensuring every model serves a clear operational purpose. • Fine-tune and optimize pre-trained models when off-the-shelf solutions fall short, leveraging transfer learning, quantization, and distributed training to hit latency and accuracy targets on resource-constrained environments. • Present technical findings and strategic recommendations in client workshops, sprint reviews, and executive briefings, translating metrics like F1-score and latency into cost savings, risk reduction, and citizen impact. • Evaluate emerging AI services from AWS, Azure, and GCP—such as Bedrock, OpenAI Service, and Vertex AI—then select and integrate the best-fit components to accelerate delivery without sacrificing governance. • Design scalable, secure, and cost-efficient cloud architectures that satisfy federal compliance standards (FISMA, FedRAMP, NIST), while remaining flexible enough to pivot as requirements evolve. • Champion a “builder’s mindset” across the team, running internal hackathons, brown-bag sessions, and code reviews that raise the bar for code quality, documentation, and knowledge sharing. • Maintain rigorous documentation—from architecture decision records to API specs—so that every solution can be handed off to client DevOps teams with minimal friction. • Contribute to ICF’s broader AI thought leadership by publishing white papers, speaking at conferences, and mentoring junior engineers, amplifying the impact of your work beyond any single project. Requirements • Bachelor’s degree in Computer Science, Engineering, Data Science, or related technical field • 5–8 years of overall professional experience, including 3–5 years of applied AI/ML and 3–5 years of production-grade Python development • Hands-on experience with modern ML frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face) and at least one major cloud platform (AWS, Azure, or GCP) • Proven track record designing, prototyping, and deploying LLM-based or agentic AI solutions that solve real client problems • US Citizenship or Permanent Residency (Green Card) and ability to obtain Public Trust clearance; must reside and perform work within the United States ️ Benefits • Generous vacation and retirement plans plus comprehensive health, dental, and vision coverage • 100% remote flexibility anywhere in the United States with core collaboration in Eastern Time Zone • Ongoing training, certification reimbursement, and development opportunities including conference attendance and internal hackathons • Friendly, mission-driven community with regular social events, charity initiatives, and employee support programs Apply tot his job