Top Senior Machine Learning Jobs in Pensacola, FL

Shape company-wide machine learning strategy across credit, fraud, marketing, and growth. Build and improve consumer credit models, establish model governance and responsible modeling controls, and advance experimentation, causal inference, and business measurement. Provide technical leadership, mentor scientists, evaluate AI-assisted workflows, and partner with Legal, Compliance, Risk, Engineering, Product, and Finance to support reliable, compliant, and impactful financial decision systems.

Lead the design, development, deployment, monitoring, and improvement of interconnected customer lifetime value models covering conversion, retention, premiums, and claim losses. Serve as a hands-on technical leader, guide modeling strategy, evaluate experiments and business impact, partner with engineering and business teams, support production ML systems, establish technical standards, and coach other data scientists.

Develop and validate machine learning models, training pipelines, inference systems, and numerical methods using Python. Debug algorithmic and system-level issues, optimize memory usage and performance, design systematic tests, and build reproducible workflows. Review challenging ML engineering tasks, use coding agents in development, document technical findings, and deliver high-quality work independently within deadlines.

Develop and deploy machine-learned interatomic potentials for PFAS substitution. Responsibilities include generating and curating first-principles training data, building reproducible cloud and HPC workflows, training and validating ML force fields, running molecular dynamics and quantum chemistry campaigns, predicting physical properties, extending models to condensed-phase and process chemistries, and communicating model uncertainty and domain limitations.

Lead design, development, and production deployment of ML and algorithmic solutions. Own end-to-end ML systems, support distributed production reliability, communicate tradeoffs, and apply generative AI, LLM fine-tuning, RAG, and agentic techniques to product problems.

Leads the AI product strategy and roadmap, extending governed Alteryx workflows and business logic into enterprise AI agents and LLM ecosystems. Owns the Faster, Better, Cheaper ROI narrative, benchmarks product performance, quantifies customer value, champions trustworthy AI through the VURA framework, and represents the product vision with customers, analysts, and external audiences.

Leads Dandelion Health’s AI developer business by building pipeline, closing clinical AI data and validation partnerships, recruiting developers into its marketplace, and achieving revenue targets. Develops commercial strategy, manages executive relationships, structures agreements, and collaborates with marketing, product, data, engineering, and clinical informatics teams. Represents the company at industry events and advises on clinical AI validation, regulatory, payer, and competitive dynamics.

Researches, develops, tests, and maintains materials-aware machine learning models and software. Designs scalable ML systems, improves model interpretability and uncertainty quantification, and develops inverse-design capabilities. Collaborates with product, engineering, and external research teams to deliver customer-focused AI solutions, publishes research, reviews code, analyzes model performance, and mentors developers.

Develop and deploy machine learning algorithms that improve real-time device identification and fraud detection. Own data science projects from experimentation through production, including supervised, semi-supervised, and unsupervised learning, real-time inference, training automation, exploratory analysis, and model-to-service integration. Contribute to engineering best practices, collaborate within a global remote team, and participate in a shared on-call rotation.

Improve 1Password’s technical SEO across consumer, PLG, and enterprise websites. Responsibilities include diagnosing and resolving crawlability, indexing, rendering, performance, structured data, internal linking, and international SEO issues; implementing CMS changes; partnering with engineering on requirements and release QA; leading migration workstreams; and building monitoring, dashboards, automation, and repeatable processes using search, analytics, crawl, log, and CMS data.

Own the vision, strategy, roadmap, discovery, delivery, and continuous improvement of Rezilient’s member experience products. Partner with clinical operations, engineering, design, customer success, and sales to ship accessible, engaging healthcare experiences. Define requirements, prioritize backlogs, establish product metrics, ensure healthcare compliance, and help integrate AI into care delivery. The role requires experience scaling consumer health products, building AI or machine learning features, and operating effectively in a regulated startup environment.

Own and grow strategic Financial Services accounts through executive relationship management, consultative selling, renewals, and expansion. Lead commercial strategy, SOWs, negotiations, QBRs, delivery governance, escalations, and value realization. Coordinate delivery, sales, solutions, cloud, and Databricks partners while managing scope, budgets, timelines, margins, retention, profitability, and customer satisfaction. Translate Databricks, data engineering, analytics, ML, AI, and cloud transformation capabilities into measurable business outcomes.

Lead data science projects from ideation through enterprise impact, building scalable and well-tested solutions that improve healthcare outcomes. Apply probability, statistics, machine learning, SQL, and Python to develop data-driven products and insights. Partner with stakeholders, assess product performance, identify strategic improvements, mitigate risks, and mentor teammates while aligning initiatives with business objectives.

Own end-to-end strategy, roadmap, delivery, adoption, safety, and commercial readiness for AI-native cybersecurity products. Conduct customer and partner discovery, lead 0-to-1 launches, define experimentation and evaluation frameworks, and collaborate with engineering, design, sales, finance, and executives. The role requires hands-on LLM product expertise, strong judgment in ambiguous environments, and a focus on trusted AI experiences for security professionals and MSP/MSSP partners.

Lead end-to-end product design for an AI-powered women’s health platform. Responsibilities include defining UX vision, creating interaction models, information architecture, wireframes, high-fidelity interfaces, prototypes, design systems, and user research. Collaborate with product, engineering, ML, marketing, and leadership teams to translate business needs into customer-focused solutions, manage design initiatives, and measure product success through user feedback and metrics.

Leads the transformation of Sophos’s pricing operations by building a centralized function, establishing pricing governance and review cadences, developing AI-assisted competitive and discount analysis capabilities, and aligning pricing across SecOps and Network Security. The role provides executive market visibility, defines performance metrics, supports organizational change, and builds a high-performing team serving sales, finance, and customer-facing stakeholders.

Own the full lifecycle of production classification and detection models, including transformer fine-tuning, entity detection, behavioral risk scoring, training, serving, versioning, evaluation, drift detection, and retraining. Build SageMaker-based ML systems and define output contracts supporting audit and policy enforcement. Lead the evaluation harness and mentor a co-op while operating as the company’s sole ML engineer.

Own the strategy, roadmap, and investment priorities for foundational agricultural data products, including pipelines, data models, APIs, and shared services. Partner with engineering, architecture, data science, and product teams to deliver scalable, governed, high-quality data capabilities. Prioritize initiatives based on customer and commercial value, define success metrics, resolve cross-team tradeoffs, and expand data support for analytics, predictive modeling, machine learning, and AI applications.

Lead end-to-end LLM inference performance across serving systems, models, GPU hardware, and workloads. Define rigorous benchmarks, diagnose bottlenecks from scheduling through kernels and interconnects, optimize single- and multi-node deployments, and deliver production-ready runtimes and configurations. Collaborate with product and infrastructure teams, evaluate inference technologies, and implement runtime fixes. The role requires strong Python engineering, production experience with serving engines such as vLLM or SGLang, GPU profiling, and knowledge of modern inference optimization techniques.

Build and deploy production machine learning systems that optimize Samsara’s global hardware supply chain. Responsibilities include demand, inventory, lead-time, spend, and supplier-risk forecasting; anomaly detection; feature engineering and ETL; real-time inference; MLOps; data infrastructure improvements; governance; and model monitoring. The role defines the AI transformation roadmap, partners with executive and cross-functional stakeholders, mentors scientists, and drives adoption of AI-enabled operational workflows.

Lead UX design initiatives across a healthcare product suite, solving complex user and business problems through research, prototyping, interaction and visual design. Mentor designers, influence cross-functional teams, contribute to the design system, and establish scalable design standards. Collaborate with engineering, product, leadership, and data science teams to integrate ML features and deliver intuitive, consumer-quality healthcare experiences.

Lead UX design initiatives across a healthcare product suite, solving complex problems through prototyping, user research, and strategic design. Collaborate with engineering, product, leadership, and data science teams to create consumer-quality experiences, integrate ML features, and evolve scalable design systems. Mentor designers, resolve stakeholder feedback, establish design standards, and drive innovation across large-scale projects.

Design, build, evaluate, and productionize machine learning and LLM-based agentic systems for healthcare products. Own projects end-to-end, including problem framing, dataset development, modeling, evaluation, deployment, monitoring, and safety guardrails. Build ML infrastructure, data pipelines, inference systems, and evaluation frameworks. Collaborate with clinicians, product managers, and engineers, while setting technical direction and mentoring team members.

Designs and implements enterprise cloud and AI solutions for unstructured data workloads. Responsibilities include building ingestion pipelines, API integrations, document extraction and HITL workflows, tuning machine learning models, benchmarking performance, and ensuring security, availability, disaster recovery, and data isolation. The role also supports customer developers, leads technical proofs of concept, mentors engineering teams, develops reusable blueprints, and provides feedback to product engineering.

Designs, deploys, and operates production machine learning systems for identity resolution, scoring, deliverability, and personalization. Responsibilities include feature engineering, model training, real-time inference, graph database integration, monitoring, drift detection, retraining, low-latency APIs, and scalable data processing. The role also contributes to MLOps standards, GPU acceleration, and ML architecture while partnering with platform engineering.