MLOps/Data Scientist -- LLM - REMOTE WORK -- 66966

Remote, USA Full-time
MLOps/Data Scientist - LLM - REMOTE WORK - 66966 Pay Range - $65 - $70/hr One of our clients is looking for a MLOps/Data Scientist - LLM to join their team remotely. TECH STACK Python, LangChain, LlamaIndex, MLflow, Svelte/SvelteKit/TypeScript, MongoDB, Qdrant, FastAPI, Kubernetes, Terraform, AWS (EKS, Lambda, S3, Bedrock, etc.), Azure Cognitive Services, REST, GraphQL, OpenAI and HuggingFace APIs, Anthropic Claude API, scikit-learn, pandas, numpy, prompt engineering frameworks, evaluation libraries, A/B testing tools, statistical analysis tools. RESPONSIBILITIES Design evaluation strategies and roadmaps aligned with development priorities Create rigorous experiments to test prompt variations, hyperparameters, and agentic tooling configurations Define success criteria and quality gates for AI features before development begins Interpret evaluation results and identify systematic patterns in failures and successes Make data-driven go/no-go decisions on feature readiness Drive prompt engineering improvements based on systematic testing and iteration Recommend specific changes to cognitive functions: prompt adjustments, parameter tuning, tool selection Provide statistical rigor to experiment design (sample sizes, significance testing, holdout sets) Transform metrics into actionable insights with clear next steps for developers Lead weekly evaluation standups and present findings to stakeholders Mentor team members on evaluation best practices and ML principles Document evaluation frameworks and build institutional knowledge QUALIFICATIONS Advanced degree in Computer Science, Machine Learning, Statistics, or related field (MS/PhD preferred) 3+ years of hands-on experience with large language models and prompt engineering Strong background in applied machine learning, particularly NLP or generative AI Deep understanding of evaluation methodologies: metrics selection, dataset design, statistical testing Experience with experiment design: A/B testing, hyperparameter optimization, systematic variation testing Proficiency with LLM APIs and prompt engineering frameworks Strong programming skills in Python and ML libraries Practical experience optimizing AI systems for production use cases Understanding of agentic AI architectures: tool use, function calling, multi-step reasoning Proven ability to translate technical findings into clear, actionable recommendations Strong decision-making skills: comfortable making go/no-go calls based on data Excellent communication and cross-functional collaboration abilities Self-directed and proactive problem solver Experience building evaluation infrastructure or MLOps tooling desirable Background in RLHF or constitutional AI desirable Published research or blog posts on LLM evaluation or prompt engineering desirable For immediate consideration: Neetu PRIMUS Global Services Direct Desk: Ext. 419 Email: Apply tot his job
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