LabsDAO
Overview
LabsDAO is a decentralized autonomous organization at the forefront of integrating AI, blockchain, and emerging technologies. We tackle the most challenging problems with radical transparency, accountability, and efficiency. LabsDAO is dedicated to making the impossible possible through innovative solutions. This is a full-time hybrid role for an AI/ML Engineer located in Ashburn, VA, with some work from home permissible. The AI/ML Engineer will be responsible for developing and implementing machine learning models, performing data analysis, and collaborating with cross-functional teams. Daily tasks include designing algorithms, working with neural networks, and improving pattern recognition systems. Core Technical Requirements
Strong in Python (FastAPI, Django, Flask). Experience with PostgreSQL, SQL optimization, and ORMs (SQLAlchemy, Prisma, TypeORM). Experience deploying scalable backends on AWS (ECS/EKS, Lambda, RDS, S3). Experience with infrastructure-as-code (Terraform, CloudFormation). Familiarity with containerization (Docker, Kubernetes). MLOps expertise: Model deployment (ONNX, TorchServe, SageMaker, BentoML). Experiment tracking (MLflow, Weights & Biases). Monitoring and evaluation of LLMs (latency, drift detection, hallucinations). CI/CD for ML workflows (GitHub Actions, Airflow, Argo). AWS Solutions Architect Certification AI/Agent Systems
Experience with LangGraph, LangChain, LiveKit, or similar frameworks. Familiarity with vector databases (Pinecone, Weaviate, pgvector). Strong grasp of retrieval-augmented generation (RAG) and evaluation pipelines. Soft Skills
Problem solver who thrives in debugging complex systems. Able to communicate clearly with both technical and non-technical stakeholders. Ownership mindset — accountable for backend stability and ML pipeline performance. Comfort working autonomously with little oversight. Bonus Skills
Experience with event-driven architectures (Kafka, RabbitMQ). Exposure to contract generation, document parsing, or real estate APIs. Understanding of privacy-preserving ML (federated learning, differential privacy). Experience with cost optimization for LLM deployments. Experience
5+ years in backend or MLOps roles. Proven record of deploying production AI/ML applications. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Software Development Get notified about new Machine Learning Engineer jobs in Ashburn, VA.
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LabsDAO is a decentralized autonomous organization at the forefront of integrating AI, blockchain, and emerging technologies. We tackle the most challenging problems with radical transparency, accountability, and efficiency. LabsDAO is dedicated to making the impossible possible through innovative solutions. This is a full-time hybrid role for an AI/ML Engineer located in Ashburn, VA, with some work from home permissible. The AI/ML Engineer will be responsible for developing and implementing machine learning models, performing data analysis, and collaborating with cross-functional teams. Daily tasks include designing algorithms, working with neural networks, and improving pattern recognition systems. Core Technical Requirements
Strong in Python (FastAPI, Django, Flask). Experience with PostgreSQL, SQL optimization, and ORMs (SQLAlchemy, Prisma, TypeORM). Experience deploying scalable backends on AWS (ECS/EKS, Lambda, RDS, S3). Experience with infrastructure-as-code (Terraform, CloudFormation). Familiarity with containerization (Docker, Kubernetes). MLOps expertise: Model deployment (ONNX, TorchServe, SageMaker, BentoML). Experiment tracking (MLflow, Weights & Biases). Monitoring and evaluation of LLMs (latency, drift detection, hallucinations). CI/CD for ML workflows (GitHub Actions, Airflow, Argo). AWS Solutions Architect Certification AI/Agent Systems
Experience with LangGraph, LangChain, LiveKit, or similar frameworks. Familiarity with vector databases (Pinecone, Weaviate, pgvector). Strong grasp of retrieval-augmented generation (RAG) and evaluation pipelines. Soft Skills
Problem solver who thrives in debugging complex systems. Able to communicate clearly with both technical and non-technical stakeholders. Ownership mindset — accountable for backend stability and ML pipeline performance. Comfort working autonomously with little oversight. Bonus Skills
Experience with event-driven architectures (Kafka, RabbitMQ). Exposure to contract generation, document parsing, or real estate APIs. Understanding of privacy-preserving ML (federated learning, differential privacy). Experience with cost optimization for LLM deployments. Experience
5+ years in backend or MLOps roles. Proven record of deploying production AI/ML applications. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Software Development Get notified about new Machine Learning Engineer jobs in Ashburn, VA.
#J-18808-Ljbffr