ZipRecruiter

Log In

2

Mlops Engineer Remote Jobs in New Port Richey, FL

Worth AI

Senior Agentic (AI) Engineer

Tampa, FL · On-site +1

$98K - $135K/yr

Drive production MLOps: deployment, versioning, traffic shaping, cost/latency budgets, tracing, and ... All Remote Hires will be required to travel to Orlando, Florida at least twice per year for Town ...

Worth AI

Senior Agentic (AI) Engineer

Tampa, FL · Remote

$107K - $146K/yr

Drive production MLOps: deployment, versioning, traffic shaping, cost/latency budgets, tracing, and ... All Remote Hires will be required to travel to Orlando, Florida at least twice per year for Town ...

Booz Allen Hamilton, Inc.

Data Manager, Senior

Tampa, FL · On-site +1

$86K - $198K/yr

Remote Work: No Job Number: R0247173 Location: Tampa,FL,US Share job via: Share Data Manager ... Experience with enterprise technology systems, such as CORE and MLOps * Experience working with AI ...

All JobsMlops Engineer JobsMlops Engineer Remote JobsMlops Engineer Remote Jobs in New Port Richey, FL

Mlops Engineer Remote information

See New Port Richey, FL salary details

$33.8K

$103.2K

$170.6K

How much do mlops engineer remote jobs pay per year?

As of Aug 24, 2026, the average yearly pay for mlops engineer remote in New Port Richey, FL is $103,199.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,900.00 and $134,900.00 per year, depending on experience, location, and employer.

What does an MLOps engineer do in a remote role?

An MLOps Engineer is responsible for streamlining and automating the deployment, monitoring, and management of machine learning models in production environments. Working remotely, they collaborate with data scientists, software engineers, and IT teams using cloud-based tools to ensure that ML models are scalable, reliable, and maintainable. Their tasks often include setting up CI/CD pipelines for ML workflows, managing model versioning, and monitoring model performance over time. Remote MLOps Engineers leverage communication and project management tools to stay aligned with distributed teams and ensure seamless operations.

What are common challenges faced by remote MLOps engineers, and how can they be addressed?

Remote MLOps Engineers often encounter challenges related to communication and collaboration, especially when coordinating with data scientists, developers, and operations teams across different time zones. To overcome these challenges, it's essential to establish clear documentation practices, utilize collaborative platforms for workflow management, and schedule regular virtual meetings to ensure alignment. Additionally, maintaining strong version control and automated CI/CD pipelines helps streamline model deployment and monitoring, reducing friction caused by remote coordination. Building proactive communication habits and leveraging cloud-based tools can significantly improve efficiency and team cohesion.

What are the key skills and qualifications needed to thrive as a remote MLOps engineer?

To thrive as an MLOps Engineer, you need a solid background in machine learning, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, and cloud platforms such as AWS or Azure, as well as certifications in cloud services or DevOps, are highly valuable. Strong problem-solving, collaboration, and communication skills help you bridge the gap between data science and operations teams in a remote setting. These competencies are crucial for building scalable, reliable machine learning systems that deliver real-world value efficiently.

What is the difference between Mlops Engineer Remote vs Data Engineer?

AspectMlops Engineer RemoteData Engineer
Required CredentialsBachelor's in CS, Data Science, or related; experience with cloud platforms and ML toolsBachelor's in CS, Data Engineering, or related; strong SQL and ETL skills
Work EnvironmentRemote, collaborative teams, cloud-based infrastructureRemote or on-site, data pipelines, cloud or on-premises systems
Industry UsageTech, AI, ML-focused companiesFinance, healthcare, tech, and other data-driven industries

While both roles involve working with data and cloud platforms, Mlops Engineers focus on deploying and maintaining machine learning models in production, often working remotely with ML-specific tools. Data Engineers primarily build and manage data pipelines and infrastructure. The roles overlap in cloud experience and data handling but differ in their core focus areas.

What are the most commonly searched types of Mlops Engineer jobs in New Port Richey, FL?

The most popular types of Mlops Engineer jobs in New Port Richey, FL are:

What are popular job titles related to Mlops Engineer Remote jobs in New Port Richey, FL?

For Mlops Engineer Remote jobs in New Port Richey, FL, the most frequently searched job titles are:

What job categories do people searching Mlops Engineer Remote jobs in New Port Richey, FL look for?

The top searched job categories for Mlops Engineer Remote jobs in New Port Richey, FL are:

What cities near New Port Richey, FL are hiring for Mlops Engineer Remote jobs?

Cities near New Port Richey, FL with the most Mlops Engineer Remote job openings:

Mlops Engineer Remote jobs near you
Infographic showing various Mlops Engineer Remote job openings in New Port Richey, FL as of August 2026, with employment types broken down into 93% Full Time, 2% Part Time, and 5% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $103,199 per year, or $49.6 per hour.

Senior Agentic (AI) Engineer

Worth AI

Tampa, FL • On-site, Remote

$98K - $135K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 10 days ago

Job description

Worth AI is hiring a Senior Agentic AI Engineer to design and ship production agent systems that automate KYB, underwriting, and risk decisions on regulated financial data. You'll own agents end-to-end architecture, retrieval, tools, evals, and production deployment and partner closely with our Chief AI Officer, applied scientists, and platform teams.

Responsibilities
  • Design and ship multi-step agentic systems (planner/executor, tool-using, multi-agent, human-in-the-loop) for onboarding, underwriting, case review, and continuous monitoring.
  • Architect agent graphs in LangGraph (or comparable - CrewAI, AutoGen, Claude Agent SDK) with explicit state, durable execution, retries, and safe fallbacks.
  • Build the retrieval layer powering our agents - chunking, hybrid search, reranking, and grounded citation.
  • Own the eval stack: golden sets, offline regression suites, LLM-as-judge, online A/B and shadow evals, and red-teaming for jailbreaks, prompt injection, and PII leakage.
  • Expose agents to production systems via well-typed tools and MCP servers. Treat tool surface area as a product.
  • Drive production MLOps: deployment, versioning, traffic shaping, cost/latency budgets, tracing, and on-call playbooks for agent incidents.
  • Partner with security and compliance to keep agents inside SOC 2, GDPR, CCPA, and fair-lending posture - auditability and explainability built in, not bolted on.
  • Mentor engineers on agent patterns, prompt hygiene, eval discipline, and LLM failure modes.
  • Technology Stack
    • Languages: Python, Node.js, TypeScript
    • Agent / LLM frameworks: LangGraph, LangChain, Claude Agent SDK, MCP, OpenAI SDK
    • Models: Anthropic Claude, OpenAI, open-weight where appropriate
    • Retrieval & Data: PostgreSQL, pgvector, OpenSearch, Kafka, Redshift, Redis
    • Infra: AWS, Kubernetes (EKS), ArgoCD, Terraform
    • Evals & Observability: LangSmith / Langfuse / Braintrust-style tooling, DataDog

Requirements

  • 5+ years of software engineering experience, with 2+ years building production LLM or agentic systems (not just notebooks or demos).
  • Hands-on experience with a modern agent framework (LangGraph strongly preferred) and a track record of shipping agents that run, fail gracefully, and recover.
  • Strong RAG fundamentals chunking, embeddings, hybrid retrieval, reranking, grounding - and judgment about when RAG isn't the right answer.
  • Real eval experience golden sets, offline and online evaluations, used to make ship/no-ship calls.
  • Production MLOps fluency: deployed LLM workloads under real latency, cost, and reliability constraints.
  • Strong Python; comfortable in TypeScript / Node.js.
  • Solid systems engineering instincts APIs, async patterns, queues, databases, distributed system failure modes.
  • Calibrated communicator; thrives in ambiguous, fast-moving environments.
  • Prior experience in fintech, lending, payments, KYB/KYC, fraud, or AML.
  • Experience building MCP servers or other structured tool interfaces for LLMs.
  • Background in classical ML (ranking, scoring, calibration).
  • Experience designing explainable / auditable AI workflows for regulated environments.
  • Open-source contributions to agent frameworks, eval tooling, or retrieval libraries.
  • AWS depth (EKS, MSK, RDS, S3, Lambda) and IaC with Terraform.
Success Metrics
  • Agent Quality: Measurable improvements in task success rate, grounding accuracy, and hallucination rate on our eval suites.
  • Production Reliability: Agents you own meet defined SLOs for latency (P90/P99), tool-call success, and cost per task.
  • Velocity: New agent capabilities go from prototype to production in weeks, without skipping evals or guardrails.
  • Risk Posture: Zero material incidents tied to prompt injection, PII leakage, or unsafe tool use on agents you own.
  • Force Multiplier: Patterns, tools, and eval scaffolding you build get adopted across engineering.

All Remote Hires will be required to travel to Orlando, Florida at least twice per year for Town Halls and team collaboration, in addition to orientation in Orlando.

Benefits

  • Health Care Plan (Medical, Dental & Vision)
  • Retirement Plan (401k, IRA)
  • Life Insurance
  • Flexible Paid Time Off
  • 9 paid Holidays
  • Family Leave
  • Remote
  • Hybrid work (for Orlando Associates)
  • Free Food & Snacks (Orlando)
  • Wellness Resources

Apply