Applied AI Research Engineer

Netic is an AI revenue engine for essential services, backed by $43M in funding. As an Applied AI Research Engineer, you will track frontier ML research, identify high-ROI projects, build and productionize models, and own the full cycle from data to deployment.

• Study the frontier: Track frontier work in traditional ML, LLMs, multimodal models, retrieval, and agentic systems.
• Identify high-ROI projects: Partner with GTM and ops teams to spot bottlenecks and define ML projects.
• Build targeted models: Own data curation, training, evaluation, and deployment.
• Productionize solutions: Integrate models via robust APIs and streaming pipelines.
• Self-direct & ship: Set technical roadmap, validate quickly, iterate based on real-world results.

• Deep ML experience: 4+ years with cutting-edge ML techniques; fluent in PyTorch or JAX.
• Research-to-revenue record: Proven ability to take novel ML concepts from paper to production.
• Full-stack pragmatism: Comfortable with ETL, feature stores, cloud-native infrastructure, and A/B experimentation.
• Data engineering skills: Experience with complex, real-world data streams and building reliable training pipelines.
• Product intuition: Ability to understand customer workflows and translate business needs into technical solutions.