Top Remote Machine Learning Jobs in Palm Bay, FL

The AI Application Engineer will design and deploy AI systems, collaborate with teams, implement Generative AI solutions, and promote continuous learning in AI practices.

Lead product strategy and execution for data and AI platforms, driving GenAI/LLM initiatives, cross-functional collaboration, responsible AI governance, experimentation (A/B testing), measurement of model impact, and mentoring product teams to embed scalable ML capabilities into clinical and member experiences.

Own pre-sales technical engagement: consult customers, deliver technical presentations and demos (web, iOS, Android), lead POCs, support RFP/RFI responses, manage onboarding and integrations, and advise sales, product, and engineering teams on implementation and value realization.

Design, build, and scale backend systems and APIs for high-transaction consumer products. Collaborate with product, credit, compliance, support, and analytics teams. Contribute to code reviews, technical planning, security, and operational excellence. Mentor peers and promote engineering best practices.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.

Lead initiatives in designing and building large-scale distributed data systems and ML infrastructure, while collaborating across various engineering teams.

Design, implement, and scale ML-based solutions for search and advertising; define data collection, evaluation, and production serving strategies; analyze data to inform development; communicate cross-functionally; produce technical reports; and stay current with advances in LLMs, vision models, and generative AI.

Design, build, and ship production AI agents integrated end-to-end into a TypeScript/Node.js/React stack. Apply ML judgment to product decisions, improve agent reliability and evaluations, and move quickly in a startup environment owning ambiguous problems.

Review, label, and QA datasets for AI/ML training; maintain trackers, databases, and dashboards; follow annotation guidelines and SOPs; prepare and clean data; document processes; collaborate to resolve data queries while ensuring confidentiality and timely delivery.

Own end-to-end client relationships for a book of B2B SaaS customers: drive adoption, engagement, retention, and expansion of AI-powered contract drafting tools. Lead onboarding, training, large-scale rollouts, and translate customer feedback into product improvements while designing scalable CS processes and tracking health metrics to demonstrate value.

Remote internship to build and deploy data and AI solutions for aerospace engineering. Responsibilities include prototyping ML/LLM/CV systems, architecting distributed data platforms, coding demos, presenting architectures, and shipping production-ready solutions while collaborating across teams.

Build and deploy machine learning models on large healthcare datasets, extract actionable insights, develop scalable data processing systems, collaborate with cross-functional teams, and communicate findings to stakeholders to improve patient outcomes.

Design, develop, and implement AI/ML models; analyze large datasets; integrate AI solutions into existing systems; apply MavLink for autonomous systems; collaborate across teams and improve ML development processes.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

The Enterprise Account Executive will drive revenue by engaging with enterprise insurance clients, managing the sales cycle, and fostering strategic relationships with executives, leveraging Vellum's data analytics platform.

Lead development of new credit line management programs by designing, testing, and scaling policies. Own end-to-end analytical work using SQL/Python, partner with Data Science and Product, and present data-driven recommendations to senior stakeholders to improve spend recovery, utilization, and line-management performance.

The job involves selling AI and Machine Learning technologies to mortgage companies, managing the sales process for enterprise customers, and working with remote teams.

Lead development of AI-powered solutions, architect large language models, capture domain knowledge, and deliver client-focused insights. Manage a team to integrate AI capabilities across products.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions, architect scalable infrastructure, and implement data pipelines across multi-cloud environments while collaborating with cross-functional teams to maximize business value.

The Senior Customer Success Manager drives revenue growth by ensuring customer satisfaction, building strong relationships, managing renewals, and promoting product solutions aligned with client goals.

Lead BI analytics and governance for client accounts: manage BI analysts, deliver dashboards and reports, oversee data mapping, modeling, quality, and platform initiatives (Power BI/Databricks), advise stakeholders, drive analytics roadmap, and apply advanced analytics and ML to optimize workplace and portfolio insights.

Lead the integration of AI and digital solutions in manufacturing processes, driving adoption and measurable impact on efficiency, quality, and performance.

The Staff Machine Learning Engineer will lead AI initiatives, architect LLM systems, design evaluation frameworks, and mentor engineers.

As a Senior Machine Learning Engineer, you will enhance diffusion models, conduct research, collaborate on system implementations, and communicate findings effectively.

As a Principal Solutions Architect, you will oversee technical architecture for VA IT modernization, writing prototypes, guiding engineering teams, and representing Credence to VA stakeholders. You will also contribute to capture strategy and mentor engineers on compliance and integration.