FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing scalable AI/ML architectures and integrating LLM APIs into enterprise workflows. Proficient in developing and validating machine learning models while ensuring adherence to AI safety and ethical standards.
Highest-signal resume keywords
Python ProgrammingDeep Learning FrameworksMLOps ImplementationAI Model ProductionStatistical Model Development
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningStatistical ModelingOptimization AlgorithmsData Pipeline DefinitionPrompt EngineeringModel Fine-TuningAnalytical ReasoningStructured Problem-Solving
Soft Skills
Exceptional Communication SkillsMentoringAutonomous Work
Tools & Technologies
PyTorchTensorFlowLangChainAWS SageMakerGCP Vertex AIDockerKubernetesMLflow
Certifications & Qualifications
Bachelor's DegreeMaster's DegreePh.D. in Computer Science
Industry Keywords
AI SafetyEthical AIData GovernanceGenerative AIMulti-Agent Frameworks
Tech Stack
Tools & technologiesAWSAzureDockerGoogle Cloud PlatformGRPCKubernetesPythonPyTorchSQLTensorflowC++
About the role
Key responsibilities & impact- Design scalable, enterprise-grade architecture for AI/ML systems, Generative AI models, and autonomous multi-agent frameworks
- Define standards for Model Context Protocol, RAG architectures, prompt engineering, and LLM fine-tuning and evaluation
- Assess technical feasibility, select model architectures, and define data pipelines for structured and unstructured datasets
- Integrate LLM APIs including OpenAI, Anthropic Claude, and Google Gemini into enterprise workflows
- Develop, train, and validate statistical models, optimization algorithms, and machine learning pipelines using Python, R, or C++
- Implement MLOps, AI observability, and tracing tools to monitor model drift, token usage efficiency, latency, and production performance
- Advise cross-functional leaders, product managers, and external clients on AI solutions
- Translate unstructured business problems into mathematical and computational models
- Communicate technical concepts, model outputs, and risk assessments to technical and non-technical audiences
- Champion AI safety, ethical AI, data governance, and secure coding practices
- Mentor junior AI engineers and data scientists on modern development workflows and AI coding assistants
Requirements
What you’ll need- Fluent in Python, SQL, and deep learning frameworks such as PyTorch and TensorFlow
- Hands-on experience with LangChain, LlamaIndex, LangGraph, vector databases such as Pinecone, Qdrant, and Milvus, and agentic workflows
- Experience with AWS Bedrock/SageMaker, GCP Vertex AI, or Azure OpenAI/AI Foundry
- Experience with Docker, Kubernetes, CI/CD for AI models, MLflow, REST, and gRPC
- Bachelor's, Master's, or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Applied Mathematics, or a related quantitative field
- 6+ years of relevant experience in software engineering, data science, or AI consulting
- Proven track record of shipping AI models into production environments
- Strong analytical reasoning and structured problem-solving abilities
- Exceptional written and verbal communication skills for technical and business audiences
- Ability to work autonomously in ambiguity and manage multiple project streams simultaneously
Benefits
Comp & perks- Work from home and assigned office days in a hybrid arrangement
- 40 scheduled weekly hours