Senior AI/ML Engineer
$65 - $70 per hourPeopleNTech
Role : Senior AI/ML Engineer Location : Dayton, Ohio (Hybrid) Rate: $65/hr to $70/hr Contract to hire Design advanced ML models across NLP, optimization, predictive modeling, and statistical learning.
Own end to end MLOps pipelines: data ingestion, training, deployment, monitoring, CI/CD.
Collaborate with engineering, product, and domain teams to deliver production ready AI solutions.
Build and scale Knowledge Graph-driven AI systems (ontology design, graph embeddings, reasoning).
Develop and fine tune LLMs for classification, summarization, RAG, and agentic workflows.
What We're Looking For:
PhD (preferred) or Master's in CS, AI, ML, Data Science, or related fields. Strong hands on experience with:
Core ML & Stats (optimization, supervised/unsupervised learning)
NLP (semantic search, embeddings, text modeling)
MLOps (MLflow, Kubeflow, Airflow, Docker, CI/CD)
Proficiency in Python, PyTorch/TensorFlow, HuggingFace, LangChain, and cloud platforms.
Ability to translate complex ideas into scalable, real world systems.
Knowledge Graphs (RDF/OWL, Neo4j, graph ML)
LLMs & Transformers (fine tuning, RAG, prompt engineering)
Preferred
Healthcare insurance / Managed Care (MCO) experience - familiarity with claims, clinical workflows, risk models, or regulatory frameworks is a strong plus.
Experience with vector databases, hybrid semantic neural architectures, or agentic AI systems.
Background in explainable or responsible AI.
Own end to end MLOps pipelines: data ingestion, training, deployment, monitoring, CI/CD.
Collaborate with engineering, product, and domain teams to deliver production ready AI solutions.
Build and scale Knowledge Graph-driven AI systems (ontology design, graph embeddings, reasoning).
Develop and fine tune LLMs for classification, summarization, RAG, and agentic workflows.
What We're Looking For:
PhD (preferred) or Master's in CS, AI, ML, Data Science, or related fields. Strong hands on experience with:
Core ML & Stats (optimization, supervised/unsupervised learning)
NLP (semantic search, embeddings, text modeling)
MLOps (MLflow, Kubeflow, Airflow, Docker, CI/CD)
Proficiency in Python, PyTorch/TensorFlow, HuggingFace, LangChain, and cloud platforms.
Ability to translate complex ideas into scalable, real world systems.
Knowledge Graphs (RDF/OWL, Neo4j, graph ML)
LLMs & Transformers (fine tuning, RAG, prompt engineering)
Preferred
Healthcare insurance / Managed Care (MCO) experience - familiarity with claims, clinical workflows, risk models, or regulatory frameworks is a strong plus.
Experience with vector databases, hybrid semantic neural architectures, or agentic AI systems.
Background in explainable or responsible AI.
Vacancy posted 1 day ago
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