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 States️ 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