DatologyAI

Developer Relations

• Turn DatologyAI research and product work into narratives, threads, videos, live demos, and launches
• Build and run DatologyAI's recognizable voice on X day to day
• Reply, quote-post, and participate in live conversations in real time
• Help leadership and researchers communicate in their own voices
• Own research launches end to end across X, the technical blog, and video
• Build relationships with researchers, open-source developers, AI creators, and technical founders
• Bring community feedback back to product and research teams
• Run experiments across X, technical writing, video, launches, and events
• Track what earns attention and trust and use results to improve future work

Explore AI Developer Experience – Media Lead at DatologyAI. Review requirements and application details.

AI Developer Experience – Media Lead

Research Scientist

• Lead research on post-training data curation for foundation models
• Design and implement algorithms to generate and improve instruction, preference, and other post-training datasets
• Explore jointly optimizing data across pre-training and post-training stages
• Curate preference, instruction-following, capability-specific, and domain-specific data
• Research end-to-end data curation to improve model post-trainability and final post-trained model performance
• Source, vet, implement, and improve promising ideas from research literature and original research
• Conduct research guided by customer needs and product improvements
• Work autonomously with the context and resources needed to succeed
• Collaborate closely with engineers and product teams
• Talk to customers and shape product vision

Explore Research Scientist – Post-Training at DatologyAI. Review requirements and application details.

Research Scientist – Post-Training

Data Engineer

• Design, build, and maintain highly scalable data processing solutions while ensuring scalability, reliability, and security
• Architect, build, and deploy back-end systems and services powering the data curation platform
• Partner with researchers and engineers to bring new features and research capabilities to customers
• Ensure systems are reliable, secure, and worthy of customers' trust
• Partner closely with founders on product direction and business-critical technical decisions
• Lead development of the core product and data platform
• Help shape the company's technology, product, and culture

Explore Software Engineer, Data Infrastructure at DatologyAI. Review requirements and application details.

Software Engineer, Data Infrastructure

Research Engineer

• Build and scale data processing and curation pipelines over massive language, vision, and multimodal datasets
• Make data pipelines fast, reliable, and inexpensive to run
• Design experimentation infrastructure that enables scientists to iterate quickly at scale
• Translate research results into production-grade systems that customers depend on
• Profile and optimize large-scale training and data workloads
• Collaborate closely with technical staff and researchers to develop and improve state-of-the-art data curation strategies

Explore Research Engineer at DatologyAI. Review requirements and application details.

Cloud Engineer

• Architect and maintain multi-cloud infrastructure, primarily AWS and potentially Azure/GCP
• Define and implement infrastructure-as-code best practices using Terraform, CloudFormation, Pulumi, and similar technologies
• Design and manage Kubernetes-based systems for model training, inference, and data processing workloads
• Optimize CI/CD pipelines and streamline service deployments across environments
• Build monitoring, alerting, and logging systems for high availability and observability
• Collaborate with research and engineering teams to support training large-scale ML models
• Ensure infrastructure supports cloud, on-prem, and hybrid deployment models for enterprise use cases
• Drive cost-efficiency strategies across compute and storage resources
• Respond to and resolve infrastructure-related incidents
• Work with engineering, research, and product teams to define deployment and compute-resource management across AWS and other cloud providers

Explore Software Engineer, Cloud Infrastructure at DatologyAI. Review requirements and application details.

Software Engineer, Cloud Infrastructure

Frontend Engineer

• Build software from the ground up to solve critical bottlenecks for DatologyAI customers and internal teams
• Partner closely with founders on product direction and business-critical technical decisions
• Develop the core product for customer dataset curation and related visualizations
• Develop internal tooling interfaces used by the team daily
• Own the full front-end development lifecycle from design through implementation
• Talk to customers and internal stakeholders to understand problems and design solutions
• Collaborate with engineers, researchers, designers, and other cross-functional partners
• Ensure products and systems are reliable, secure, and worthy of customer trust

Explore Software Engineer – Front-end at DatologyAI. Review requirements and application details.

Software Engineer – Front-end

Infrastructure Engineer

• Design and build development and production platforms powering DatologyAI’s products
• Enable reliability and security at scale
• Architect, build, and deploy core infrastructure supporting multiple cloud providers and deployment models
• Accelerate company productivity through excellent tooling and systems
• Partner with researchers and engineers to bring new features and research capabilities to customers
• Drive business-critical technical decisions and help shape product direction
• Lead development of data infrastructure, including multi-cloud support, deployment models, training infrastructure, and inference infrastructure

Explore Software Engineer, Infrastructure at DatologyAI. Review requirements and application details.

Software Engineer, Infrastructure

Product Manager

• Own the product strategy and roadmap for the enterprise data curation platform
• Own the product roadmap end-to-end, from discovery and prioritization through launch and iteration
• Partner with research and engineering to turn ambiguous, early-stage outputs into concrete, shippable product decisions
• Define and drive the enterprise product experience, including platform UX, API design, deployment flexibility (BYOC, on-prem), and integrations with existing ML workflows
• Engage directly with enterprise ML teams, data scientists, and infrastructure engineers to turn pain points into product strategy
• Build foundational PM infrastructure, including discovery frameworks, roadmap tooling, release processes, and cross-functional rituals
• Work with Sales and Customer Success to enable a repeatable, defensible go-to-market motion
• Track the competitive landscape across AI tooling, MLOps, and data infrastructure
• Connect research output with commercial product decisions, sequencing, and success measurement
• Partner closely with the founders, research, and engineering teams

Explore Product Manager at DatologyAI. Review requirements and application details.

Pre-sales Engineer

• Support customers in a highly technical pre-sales role
• Partner with strategic prospects to understand data curation needs, technical constraints, and business goals
• Design scalable solutions demonstrating the impact of DatologyAI’s data curation platform
• Embed deeply with strategic customers to understand business challenges and technical requirements
• Lead end-to-end customer PoCs connecting data curation, training behavior, and evaluation outcomes
• Analyze datasets, design training plans, and interpret results
• Partner with customer ML teams to map data and curation strategy
• Design and execute evaluation plans for base and post-trained models
• Select appropriate benchmarks and metrics and run model evaluations
• Produce customer-ready evaluation reports covering methodology, metrics, baselines, ablations, conclusions, and productionization recommendations
• Communicate technical results and tradeoffs in compute, latency, and deployment cost to ML experts and executives
• Collaborate with GTM, Engineering, and Research teams on customer experiences, demos, requirements, and product strategies
• Provide technical guidance, training, and documentation to prospects

Explore Solutions Engineer, AI/ML – Pre-Sales at DatologyAI. Review requirements and application details.

Solutions Engineer, AI/ML – Pre-Sales

• Investigate how intervening on training data can improve deep learning model quality and shape model behavior
• Source, vet, implement, and improve promising ideas from research literature and independent thinking
• Conduct research grounded in concrete customer needs and product outcomes
• Collaborate closely with engineers and product teams to turn research findings into tangible impact
• Talk to customers and help shape product vision
• Run large-scale experiments and build production prototypes

Explore Research Scientist at DatologyAI. Review requirements and application details.

AI Engineer

• Lead customers through onboarding, deployment, and production rollout of DatologyAI’s platform
• Serve as technical owner for assigned accounts, driving architecture, execution, long-term adoption, and tailored technical success plans
• Partner with Sales, Engineering, and Research to translate use-case requirements into technical strategies
• Support early trials, relay customer feedback, and help shape roadmap priorities
• Guide customers in designing scalable, secure workflows across compute, storage, networking, and distributed systems
• Provide reporting on deployment progress, workload health, usage metrics, and executive-level updates
• Adapt and optimize the platform across AWS, GCP, Azure, and on-prem Kubernetes environments
• Handle provider-specific APIs, storage systems, networking configurations, and compute orchestration
• Tune performance for network topology, storage tiering, and resource allocation in each environment
• Serve as a trusted technical advisor for strategic customers and bridge platform capabilities with customer requirements

Explore Forward Deployed AI Engineer – Post-Sales at DatologyAI. Review requirements and application details.