FREE ACCESS
5,000–10,000 jobs/day
See all jobs on JobTailor
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Tech Stack
Tools & technologiesGoGRPCMicroservicesPythonPyTorchScikit-LearnTensorflow
About the role
Key responsibilities & impact- Build and scale AI/ML and GenAI pipelines from experimental workflows to production-ready systems.
- Integrate model training, evaluation, deployment, and monitoring into product workflows.
- Deploy and manage GenAI solutions such as chatbots, RAG applications, and predictive analytics tools.
- Operationalize LLMs and AI agents, including prompt orchestration, chaining, and fine-tuning.
- Benchmark models, develop evaluation frameworks, and improve reliability and auditability.
- Implement observability, monitoring, and rollback mechanisms to ensure secure, scalable deployments.
- Work across the stack—from backend systems to product SDKs—to deliver AI features directly into user-facing applications.
- Prototype rapidly, gather feedback, and iterate while keeping scale and maintainability in mind.
- Own critical product components and take responsibility for delivering robust, production-grade features.
- Collaborate cross-functionally with data scientists, product managers, and engineers to scope specifications and solve real customer problems.
- Debug complex issues and perform root cause analysis across model pipelines, infrastructure, and product layers to ensure reliability and continuous improvement.
Requirements
What you’ll need- BS or MS in Computer Science, Statistics, or Mathematics, or equivalent experience.
- Strong software engineering background with proven experience shipping production systems.
- 3+ years of experience in ML/DL pipelines, deployment, and applied AI solutions.
- Proficiency in Python or Go with frameworks like TensorFlow, PyTorch, Scikit-Learn, FastAPI, or gRPC.
- Experience with LLM and AI frameworks such as Langchain, LlamaIndex, Hugging Face Transformers, and OpenAI API.
- Knowledge of RAG architectures, embeddings, reranking models, and LLM-based dialogue systems.
- Experience building and scaling backend platforms, APIs, and microservices.
- Comfortable working full-stack, from model APIs down to user-facing integrations.
- Have shipped AI features that users actually use; production experience over theoretical knowledge.
- Track record of building reliable products with strong attention to detail and usability.
- Autonomous and excited about taking ownership over major initiatives.
- Frequent user of AI products (Cursor, Claude Code, Copilot, etc.) during the development lifecycle.
Benefits
Comp & perks- Competitive Compensation
- Unlimited PTO
- Hybrid working model (3 days in office)
- AI Assistants for work (Coding, General Purpose, etc.)
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AI/ML Pipeline DevelopmentModel Training and EvaluationDeployment and MonitoringBackend DevelopmentAPI DevelopmentMicroservices ArchitecturePrompt OrchestrationFine-Tuning AI ModelsRoot Cause AnalysisProduction Systems Engineering
Soft Skills
CollaborationAutonomyAttention to DetailProblem-SolvingFeedback Iteration