Senior Machine Learning Engineer

• We are seeking a Senior Machine Learning Engineer to support our Public Sector initiatives focused on building and optimizing production ready AI systems for secure and distributed environments




• You will be responsible for transforming prototype models into scalable, efficient, and reliable production systems that operate seamlessly across a spectrum of hardware from government cloud infrastructure to edge devices in restricted or disconnected environments




• Design, develop, and deploy agentic workflows to orchestrate multi-step reasoning, tool use, and decision-making across production systems




• Productionize AI models from research prototypes into scalable, deployable systems used in real world applications




• Engineer adaptive ML systems using LoRA, PEFT, and on-device inference strategies, leveraging PyTorch, TensorFlow, and Hugging Face Transformers for model development, fine-tuning, and optimization




• Implement model optimization techniques such as quantization, pruning, distillation, and hardware specific acceleration




• Build and maintain Retrieval Augmented Generation (RAG) pipelines, including vector database integration for contextual retrieval




• Work with multi-modal AI systems across computer vision, audio, and natural language domains




• Optimize model execution for distributed and resource constrained environments, ensuring reliability under variable connectivity conditions

Benefits

• Grow with us: Equity options so you share in our growth. Build your future as we build ours.




• Family first: Parental leave and fertility support for every stage of life. Your family matters here.




• Plan your future: A 401(k) to help you save and invest. Secure what’s ahead with confidence.




• Stay well: Comprehensive health coverage for body and mind. Because balance fuels great work.




• Keep learning: A stipend to explore, study, and sharpen your skills. Growth never stops.




• Work anywhere: Remote-first with flexible time off to recharge. Find balance wherever you are.

Requirements

• Familiarity with multi-modal models and synthetic data generation methods




• Deep proficiency in PyTorch, TensorFlow, or Hugging Face Transformers




• Active US Security clearance




• Strong algorithmic and problem solving skills, especially in distributed or constrained compute environments




• Proven experience deploying AI models across cloud, edge, and mobile hardware environments




• 4+ years of experience in applied AI, ML engineering, or production AI systems




• Expertise in model compression and optimization (quantization, pruning, distillation)




• Experience building RAG pipelines and integrating vector databases (e.g., Quadrant, ChromaDB, FAISS, Milvus, Pinecone)




• Ownership – Taking full responsibility for one’s actions and decisions, demonstrating commitment to the success of our clients




• Truth – Emphasizing transparency and honesty in every interaction and decision




• Humility – Maintaining a respectful and learning-oriented mindset, acknowledging the strengths and contributions of others




• Tenacity – Persisting in the face of challenges and setbacks, continually striving for excellence and improvement




• We seek individuals who exemplify the following:




• Strong understanding of GPU computing, CUDA, and performance profiling




• Excellent communication and technical documentation skills for collaboration across multi disciplinary teams




• Understanding of AI governance and compliance frameworks relevant to public sector deployments




• Experience with edge AI, federated learning, or offline inference systems




• Experience integrating models into large scale distributed systems or microservice architectures

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