Top Senior Machine Learning Jobs in Pensacola, FL

Build and maintain data and model layers for an AI decision‑support system: data ingestion, probabilistic record matching, calibrated scoring, provenance‑tracked retrieval and grounded generation, and secure production pipelines. Ensure explainability, auditability, and accredited deployment in a controlled government cloud environment.

Design and build data and model layers for an accredited AI decision-support system: record matching, calibrated scoring, provenance-tracked retrieval and generation, secure ingestion pipelines, model packaging/serving, and instrumentation for audit and accreditation.

Lead product vision and roadmap for Tekion's Automotive CRM, translate dealer and partner needs into product requirements, define AI/LLM-enabled CRM capabilities, collaborate cross-functionally to deliver SaaS CRM features, create product artifacts, measure success metrics, and prioritize initiatives to drive adoption and strategic account success.

Lead and develop a team of five East Coast Enterprise Sales Leaders to drive new logo acquisition and account expansion. Build sales plans, manage pipeline from lead generation through close, recruit and coach leaders, and contribute to GTM strategy while reporting to the VP of Enterprise Sales. Remote-first role with occasional off-hours work.

Drive technical wins for enterprise financial institutions by scoping solutions, leading discovery (MEDDPICC), tailoring demos, building business cases, owning RFI/RFPs and POCs, and coordinating product/engineering to validate feasibility for fraud and financial crime prevention.

Build and operate model validation, quantization, and safety systems for production ML. Develop pipelines for security scanning, optimization (quantization/pruning), routing, prompt management, and evaluation frameworks measuring accuracy, performance, and safety across model lifecycles.

Design, build, and operate core AI capabilities and reusable model integrations for an enterprise platform. Integrate foundation models into production, optimize performance and reliability, prototype new techniques, and support scalable backend services and distributed AI systems in collaboration with cross-functional teams.

Lead and manage actuarial projects for healthcare clients, provide technical and strategic actuarial advice, build financial models, mentor junior actuaries, and support practice development and client relationships to drive financial decision-making.

Lead product ownership for Advisor Experience, owning roadmap from discovery to delivery. Build integrations and AI features (Aspen AI, client portal), deliver advisor capacity and transition tools, work with engineering/design/data and external partners, and drive Client Excellence KPIs (Net Revenue Retention, NPS, advisor retention, transition success).

Lead design, development, and production deployment of ML models and GenAI/LLM solutions to optimize clinical trial workflows. Build scalable pipelines, monitoring, and CI/CD for robust production use. Collaborate cross-functionally, mentor junior engineers, and communicate technical results to technical and non-technical stakeholders.

Lead and mentor engineering teams while owning platform architecture (React, Node/Express, Postgres, AWS). Drive TypeScript migration, design ETL and AI/LLM integration frameworks, ensure reliability and observability, manage delivery, incidents, and hiring, and define technical strategy for production ML/AI systems.

Lead development and refinement of machine learning pricing models (especially reinforcement learning) for Airbnb hosts. Collaborate with data scientists, product, and engineers to design, test, integrate, and monitor models, analyze performance, and prioritize projects to improve host outcomes.

Lead a 4-6 engineer team owning the internal data warehouse and end-to-end ML Ops lifecycle: experimentation, training pipelines, deployment, and monitoring. Provide technical leadership, collaborate with cross-functional partners, define platform standards, and coach engineers to deliver reliable, scalable data and ML infrastructure that powers product analytics and identification features.

Build and prototype supervised ML models to predict ad campaign delivery outcomes (reach, frequency, contention). Own feature engineering, evaluation frameworks, interpretability, and partner with ML engineers to deploy and monitor models at scale. Collaborate across product, engineering, and sales to drive adoption and measure lift versus simulation baselines.

Contractor role to design, harden and productionize ML and LLM systems for enterprise clients: build data/training pipelines, MLOps (deployment, CI/CD, monitoring, versioning), RAG and retrieval systems, benchmarking and cost control, short audits, and client-facing advisory work. Work as part of Janea teams on time-bound engagements.

Lead the design and delivery of a production-grade localization ML stack for autonomous vehicles: architect models for landmark-based localization across sensors, own data and evaluation pipelines, drive feature development to deployment, define failure modes and safety coverage, and mentor engineers while integrating cutting-edge multimodal and foundation-model techniques into robust, real-time localization systems.

Design and deliver enterprise-grade Generative AI solutions on AWS using Bedrock and AgentCore. Architect LLM-based applications, RAG pipelines, agentic workflows, vector DB integrations, and APIs. Optimize models for performance, cost, and quality, ensure security and governance, lead teams, and troubleshoot production GenAI systems.

Architect and implement enterprise-grade MLOps/LLMOps platforms on AWS and Kubernetes. Design ML/LLM pipelines for training, validation, deployment, monitoring, governance, CI/CD, and observability. Serve as technical authority, conduct architecture reviews, ensure security and compliance, and mentor engineering teams across projects.

Design, build, and operate production agentic AI systems on AWS Bedrock AgentCore using Strands/LangGraph. Implement tool integrations (MCP/Gateway), evaluation pipelines and LLM-as-judge CI gates, observability, cost/latency controls, and guardrails for agents operating on live dealer data.

Design, develop, implement, and monitor statistical and machine learning models to support credit risk, collections, servicing, marketing, and forecasting. Build data pipelines, translate business needs into analytical solutions, support model governance, testing, deployment, and ongoing performance monitoring, and communicate results to stakeholders.

Lead development and deployment of predictive and ML models for credit risk, collections, and operations. Mentor data scientists, promote MLOps and modern tools, present insights to stakeholders, and drive experimentation with techniques such as causal inference and GenAI.

Partner with customers to design and deliver production-ready AI/ML solutions, drive POC-to-production success, troubleshoot technical issues, inform product roadmap with customer feedback, and communicate outcomes to stakeholders.

The Senior Machine Learning Engineer will build and optimize ML systems for CRM marketing, collaborating with cross-functional teams to impact customer engagement and product functionality.

The Senior Data Engineer will own the data strategy, managing sourcing, structuring, and optimizing multimodal data to enhance AI models and products.

As a Senior Software Engineer, you'll build and operate the ML platform, optimizing data operations, managing the feature store, and supporting ML initiatives while driving architectural roadmap decisions.