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Senior, Software Engineer - ML Data Delivery
Builds and maintains ML data pipelines for autonomous truck perception models, curating high-quality sensor annotations and delivering data for on-demand model training.
Senior, ML Engineer - 3D Reconstruction
Build and deploy ML models for 3D scene reconstruction, lane detection, and HD map creation using LiDAR/camera data to auto-generate high-quality annotations for autonomous trucks.
Senior, ML Engineer - 3D Reconstruction
Build and deploy ML systems that reconstruct 3D lane lines and maps from noisy sensor data (cameras, LiDAR, radar, GPS/IMU) to power autonomous truck perception and HD mapping.
AI Engineer
Build and deploy production-grade AI systems for edge environments like offshore platforms, mines, and autonomous vehicles, optimizing models for latency, robustness, and security across disconnected settings.
Data & AI Strategy Lead | GenAI & MLOps Champion
Leads data strategy, GenAI, and MLOps for an edtech company, building scalable AI platforms and guiding analytics teams to drive data-driven decisions.
Conversational Agent AI Platform Engineer
Build and maintain a cloud-native Conversational AI Platform using Python, RAG, Airflow, and Elasticsearch to deploy and scale AI bots for customer service across 30+ countries.
Applied AI & ML Lead - Markets Operations
Lead a team to design, build, and deploy AI/ML models that transform J.P. Morgan’s market operations, using Python, PyTorch/TensorFlow, and cloud platforms.
DevOps AI Platform Architecture - London, UK - London
Design and build scalable AI platforms using cloud services, MLOps pipelines, and Kubernetes to automate AI/ML deployment and monitoring for enterprise solutions.
Member of the Technical Staff — AI/ML
Build and deploy AI/ML systems for B2B financial operations, focusing on invoice matching, payment reconciliation, and agentic workflows using LLMs and RAG in a fintech SaaS platform.
Platform Engineer - AI & Data Platform 50-60k
Build and maintain enterprise-scale AI and data platforms, automating operations with cloud and MLOps tools like Kubernetes, Terraform, and Jenkins.
Platform Engineer (AI / Data Platform, 30-40K)
Build and maintain the AI platform and data lakehouse, automating operations and deploying services using Python, Kubernetes, and MLOps tools.
GenAI AI/ML Engineer — Remote & Production AI
Design and deploy production-grade AI/ML systems, owning the full lifecycle from data prep to deployment in a multidisciplinary team.
Data Manager - Senior (KP) Job#818
Data Manager - Senior (KP) Location: Springfield, VA TS/SCI REQUIRED Current CI polygraph is required immediately after starting (or already within scope) Position Responsibilities : 3+ years of experience with people…
Data Scientist - Expert (KP) Job#821
Build and maintain data pipelines, query databases, and create visualizations for a government IT program using Python/JavaScript/Java and cloud architectures.
Data Manager - Senior - #826
Data Manager - Senior - #826 Location: Springfield, VA - 100% onsite TS/SCI REQUIRED Required Experience/Skills: 3+ years of experience with people management experience and excellent communication and keen…
ML Engineer | Hybrid
Build and deploy AI/ML models and data pipelines for an insurance group, focusing on Snowflake data assets, MLOps, and production-grade ML systems.
Senior Specialist Machine Learning Engineer
Design and deploy scalable ML systems in production, owning MLOps pipelines, real-time inference, and model monitoring across Vodafone’s markets.
Senior Data/AI Technical Architect
Designs and governs enterprise AI, data, and cloud architectures on Azure, AWS, and GCP, guiding clients through modernization and AI adoption while ensuring security, cost efficiency, and compliance.
Lead AI Engineer
Lead the architecture and delivery of enterprise AI systems using LLMs, RAG, and AI agents, setting engineering standards and mentoring teams to build secure, scalable, and responsible AI solutions.
Manager, Data Governance
Lead Benevity’s Data Governance program: set standards, classify assets, enforce quality SLAs, and maintain the DataHub catalog so teams can trust their data.