Robots and Pencils
AIEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“AI Engineer at Robots and Pencils. Skills: AI Engineering, Machine Learning, MLOps, Cloud infrastructure. Implement machine learning models. Implement inference services”
What You'll Achieve.
Deliver measurable business value; Deliver independently on features; Maintain high standards for reliability; Maintain high standards for performance; Maintain high standards for maintainability
Industry & Context.
Problem-solving; Debugging; Troubleshooting
What They're Looking For.
Must Have
3–5 years of experience in AI/ML engineering, Experience building and deploying ML models in production, Software engineering background (Python or similar), Familiarity with distributed systems, Familiarity with scalable data processing, Experience contributing to ML pipelines, Experience with automated deployment workflows, Working knowledge of MLOps concepts, Ability to debug issues across model, application, and infrastructure layers
Nice to Have
Exposure to generative AI, Exposure to LLM-based systems, Familiarity with RAG architectures, Experience with cloud-based AI platforms, Exposure to infrastructure-as-code, Exposure to DevOps practices, Experience in consulting, Experience in delivery-focused environments, Hands-on AWS experience, AWS certifications, Equivalent practical AWS expertise
What You'll Do.
Implement machine learning models
Implement inference services
Implement supporting APIs
Develop training workflows
Develop evaluation workflows
Develop deployment workflows
Build data ingestion components
Build feature engineering components
Ensure reliability of AI services
Ensure performance of AI services
Ensure stability of AI services
Develop agentic workflows
Support LLMOps processes
Implement observability
Debug issues across LLM layers
Debug issues across data ingestion
Debug issues across cloud infrastructure
Operationalize research prototypes
Implement evaluation metrics
Implement validation processes
Support rollout of AI features
Support iteration of AI features
Implement AI-driven features
Participate in sprint planning
Participate in estimation
Participate in technical discussions
Contribute to documentation
Contribute to shared engineering standards
How You'll Work.
Team & Collaboration
Senior engineers; Product managers; Cross-functional teams; Product teams; Engineering teams
Communication Scope
Communicate progress; Communicate blockers; Communicate risks
Process & Methodology
Sprint planning, Estimation
Full Job Description
Robots & Pencils is seeking an AI Engineer to design, build, and deploy production-grade AI systems that deliver measurable business value. This is a hands-on engineering role focused on implementation and delivery. You will contribute to scalable AI systems and ML pipelines, working within established architectural direction while collaborating closely with senior engineers, product managers, and cross-functional teams. You will be expected to deliver independently on well-defined features, contribute to system design discussions, and maintain high standards for reliability, performance, and maintainability. Key Responsibilities AI System Implementation Implement machine learning models, inference services, and supporting APIs Contribute to the development of training, evaluation, and deployment workflows Build data ingestion and feature engineering components aligned to defined architecture Ensure reliability, performance, and stability of AI services in production environments AI Pipelines & Infrastructure Contribute to the development and orchestration of AI pipelines and agentic workflows. Support LLMOps processes for automated model deployment, versioning, and prompt management. Implement monitoring and observability to track token usage, model drift, and hallucinations. Debug and resolve complex issues across LLM layers, data ingestion, and cloud infrastructure. Research-to-Production Support Collaborate with senior engineers to operationalize research prototypes Implement evaluation metrics and validation processes Support rollout and iteration of AI features based on performance data Collaboration & Delivery Work closely with product and engineering teams to implement AI-driven features Participate in sprint planning, estimation, and technical discussions Contribute to documentation and shared engineering standards Communicate progress, blockers, and risks clearly Required Skills & Qualifications 3–5 years of experience in AI/ML engineering or applied machi
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