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Assistant Llm Developer Jobs in Ohio (NOW HIRING)

Build secure LLM/RAG services and ML pipelines that integrate with SIEM/XDR, EDR, SOAR, IAM, ITSM ... Drive a roadmap of 2-3 flagship capabilities per year (e.g., SOC triage assistant, controls ...

Senior Lead AI Security Engineer

Columbus, OH · On-site

$107K - $147K/yr

Build secure LLM/RAG services and ML pipelines that integrate with SIEM/XDR, EDR, SOAR, IAM, ITSM ... Drive a roadmap of 2-3 flagship capabilities per year (e.g., SOC triage assistant, controls ...

... LLM-powered enterprise applications, such as internal knowledge assistants, document processing ... Collaborate with data engineers, software engineers, product teams, and business stakeholders to ...

Senior Data Scientist

Cleveland, OH · On-site

$150 - $200/hr

Build and deploy LLM-powered applications, such as enterprise knowledge assistants and chatbots ... Optimize prompt engineering workflows and fine-tune models using domain-specific data * Evaluate ...

... LLM-powered enterprise applications, such as internal knowledge assistants, document processing ... Collaborate with data engineers, software engineers, product teams, and business stakeholders to ...

... LLM-powered enterprise applications, such as internal knowledge assistants, document processing ... Collaborate with data engineers, software engineers, product teams, and business stakeholders to ...

Sr. Machine Learning Engineer

Columbus, OH

$100K - $138K/yr

... Assistant (copilot), Flows (AI Agentic workflows) and Performers (autonomous AI Agents). Realm-X ... LLM fluency: Strong grasp of LLM reasoning behavior, tool use, structured output, and reasoning-vs ...

Sr. Machine Learning Engineer

Columbus, OH · On-site

$100K - $138K/yr

... Assistant (copilot), Flows (AI Agentic workflows) and Performers (autonomous AI Agents). Realm-X ... LLM fluency: Strong grasp of LLM reasoning behavior, tool use, structured output, and reasoning-vs ...

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Assistant Llm Developer information

What is the difference between Assistant Llm Developer vs Machine Learning Engineer?

AspectAssistant Llm DeveloperMachine Learning Engineer
Required CredentialsBachelor's in CS, AI, or related; familiarity with NLP and LLMsBachelor's or higher in CS, Data Science, or related; strong ML background
Work EnvironmentTech companies, AI startups, research labsTech firms, AI companies, research institutions
Employer & Industry UsageFocus on developing and fine-tuning language modelsDesigning, building, deploying ML models across domains

Assistant Llm Developers typically focus on developing and fine-tuning language models, often working closely with NLP teams. Machine Learning Engineers have a broader scope, designing and deploying various ML models across industries. Both roles require strong technical skills, but Assistant Llm Developers specialize more in language-specific AI applications.

What are the most commonly searched types of Llm Developer jobs in Ohio?

The most popular types of Llm Developer jobs in Ohio are:

What cities in Ohio are hiring for Assistant Llm Developer jobs?

Cities in Ohio with the most Assistant Llm Developer job openings:

Senior Lead AI Security Engineer

Columbus, OH • On-site

JPMorgan Chase & Co.
Finance and Insurance • 10K+ employees

$150 - $200/hr

Other

Re-posted 16 days ago


JPMorgan Chase & Co. rating

7.9

Company rating: 7.9 out of 10

Based on 500 frontline employees who took The Breakroom Quiz

78th of 176 rated banks


Job description

Job Summary

As a Senior Lead AI Security Engineer in our Cybersecurity team, you will design and deliver secure artificial intelligence solutions that support critical cyber use cases. You will play a key role in shaping platform standards and governance, collaborating with cross-functional teams, and driving innovation in secure AI. Together, we will build foundational capabilities and create lasting impact for our organization and the wider community.

Job responsibilities
  • Lead end-to-end design and delivery of AI solutions for cyber use cases, from problem framing and data integration to model development, evaluation, deployment, and monitoring.
  • Build secure LLM/RAG services and ML pipelines that integrate with SIEM/XDR, EDR, SOAR, IAM, ITSM, CMDB, code repos, and cloud telemetry.
  • Establish engineering standards for secure AI: prompt security, tool/function calling patterns, input/output validation, PII masking, secrets handling, and deterministic fallbacks.
  • Create evaluation harnesses with offline/online metrics, golden datasets, adversarial prompt sets, jailbreak tests, and safety/quality KPIs.
  • Partner with platform teams to stand up reusable AI components: LLM gateways, vector stores, feature stores, evaluation/observability, and governance workflows.
  • Implement drift and quality monitoring; define SLAs/SLOs; build incident response runbooks for AI-enabled services.
  • Collaborate with risk and MRGR-style governance partners to meet documentation, validation, and attestations; maintain model/AT inventories, monitoring plans, and change logs.
  • Deliver measurable impact: reduce MTTR, improve detection precision, automate control evidence collection, and accelerate secure engineering.
  • Mentor engineers and analysts; publish playbooks, templates, and safe prompt libraries; lead brown-bags and office hours for adoption.
  • Drive a roadmap of 2–3 flagship capabilities per year (e.g., SOC triage assistant, controls automation agent, DevSecOps code copilot).
Required qualifications, capabilities and skills
  • Minimum 7 years of software/security engineering, including hands‑on experience in one or more of: detection engineering, SecOps, AppSec/DevSecOps, or cloud security.
  • Minimum 3 years building and operating applied ML/LLM systems in production (RAG pipelines, embeddings, fine‑tuning/specialization, vector databases, model serving).
  • Proficiency in Python and at least one of: Java, Scala, or TypeScript; experience with microservices, APIs, containers, and Kubernetes.
  • Familiarity with SIEM, EDR, SOAR, IAM, and ITSM integrations; streaming/data engineering with Kafka or similar.
  • Experience with LLM orchestration and guardrails (prompt engineering, injection defense, tool calling, safety filters).
  • Hands‑on with ML/LLM ecosystems: PyTorch or TensorFlow; scikit‑learn; LangChain/LlamaIndex; ONNX/Triton/Ray
  • Strong understanding of secure SDLC, privacy, and data protection; ability to partner with governance to meet documentation and monitoring requirements.
  • Demonstrated ability to ship secure, reliable AI features with clear metrics and post‑deployment monitoring.
Preferred qualifications, capabilities and skills
  • Experience building developer copilots for AppSec/DevSecOps (IaC scanning, secrets detection, SAST/DAST triage).
  • Cloud security engineering across one or more major providers; IaC and policy‑as‑code.
  • Experience or exposure to Cyber operations, Adversarial ML and LLM red teaming experience (prompt injection, data exfiltration, model abuse, poisoning defenses).
  • Graph ML for identity/threat detection; anomaly detection over telemetry.
  • GPU optimization, model quantization/distillation, and on‑prem/private model deployment.
  • Familiarity with governance for AI/ML systems in regulated environments.

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