Top Machine Learning Jobs in Huntsville, AL

Design and deploy production machine learning models and conversational AI agents that transform advertiser briefs into optimized media plans. Build evaluation systems to improve model and agent quality, collaborate across science and engineering teams, investigate ambiguous problems, and iterate using performance data and seller feedback. Communicate effectively with technical and non-technical stakeholders while contributing broadly across machine learning domains.

Leads end-to-end customer onboarding and implementation programs, translating customer goals into project plans, milestones, dependencies, risks, and success metrics. Coordinates Sales, Product, Engineering, Support, Customer Success, trainers, and subject-matter experts without performing hands-on technical implementation or training. Establishes scalable operational frameworks, manages cross-functional accountability, oversees technical readiness, tracks adoption, facilitates stakeholder communications, and ensures customers are prepared for go-live.

Own the full sales cycle across North America, including prospecting, pipeline generation, client meetings, contract negotiation, and closing new business. Build markets across eCommerce, fintech, real-money gaming, and mobile apps while partnering with Customer Success, Marketing, and Product. Represent the company at industry events, monitor mobile advertising trends, and achieve personal and regional revenue targets exceeding $1 million annually.

Own lifecycle marketing performance across patient onboarding, activation, early care, and retention. Design and analyze multichannel experiments, build reporting and dashboards, write SQL, diagnose funnel and segment performance, and integrate AI and machine learning signals into lifecycle journeys. Collaborate with Product, Operations, Data Engineering, Marketing Operations, Analytics, and Creative to improve patient outcomes and measurable business performance.

Lead the roadmap and delivery of an AI-native L1 IT operations agent. Partner with customers, design partners, engineering, and go-to-market teams to ship enterprise-scale capabilities, improve self-service adoption, and build trust through transparent agent experiences and feedback loops. Drive product strategy from discovery through launch in a fast-paced, ambiguous environment.

Designs, develops, and maintains scalable data warehouses, data lakes, platforms, and ETL/ELT pipelines. Builds batch and streaming workflows, processes structured and unstructured data, optimizes cloud storage and pipeline performance, and implements data governance and lifecycle management. Guides multidisciplinary teams in agile environments while delivering mission-focused data engineering solutions.

Build data foundations and end-to-end pipelines, research and implement quantitative pricing, market-making, and risk models for prediction markets, model cross-market dependencies and parlays, develop backtesting/simulation frameworks, monitor model performance and collaborate closely with traders to improve pricing and trading outcomes.

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.

Own the enterprise architecture vision for scalable, high-performance, cost-efficient multi-tenant SaaS systems. Lead AWS cloud optimization, distributed data and AI infrastructure, architectural governance, and Architecture Review Council activities. Guide engineering teams on microservices, event-driven systems, automation, and cloud-native practices while driving GenAI adoption across the software lifecycle. Build prototypes, establish architectural standards, optimize total cost of ownership, and mentor technical leaders.

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 product strategy and delivery for agentic document management, policy and procedure workflows, and compliance gap assessments. Partner with customers, design, engineering, and go-to-market teams to build reliable, explainable AI experiences that accelerate audit readiness and security program expansion. Responsibilities include defining product requirements, evaluating AI outputs, improving quality, synthesizing customer feedback, prioritizing roadmaps, and shaping product culture.

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.

Provides strategic legal counsel on clinical trials, commercial biopharma services, healthcare regulation, privacy, data protection, and EU employment matters. Advises on GDPR, HIPAA, clinical data use, cross-border transfers, privacy impact assessments, contracts, workforce initiatives, works councils, and regulatory developments. Partners with clinical, commercial, HR, compliance, technology, and senior leadership teams while supporting privacy program implementation and risk management.

Leads credit risk analytics for Prosper’s Credit Card business, overseeing underwriting, portfolio, pricing, credit line, fraud, and credit risk strategies. Uses machine learning, AI, and advanced analytics to manage growth while controlling losses within risk appetite. Presents recommendations to executives, the Credit Risk Committee, and investors; monitors performance and emerging trends; evaluates vendors and alternative data; and collaborates across Capital Markets, Product, Engineering, Legal, Compliance, Operations, and Marketing. Also builds and mentors high-performing credit risk teams.

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.

Leads regional life science enterprise sales by developing pipeline, closing complex deals, expanding accounts, and building executive relationships across health plans, health systems, biotech, and pharmaceutical organizations. The role requires consultative selling of AI/ML healthcare solutions, cross-functional collaboration, CRM management, contract negotiation, and trusted-advisor engagement with C-level decision-makers. This remote position requires 25–50% travel.

Drive enterprise sales of Snowflake’s AI and machine learning solutions by generating pipeline, achieving revenue targets, developing territory strategies, and executing tailored sales plays. Engage executives and technical decision-makers, manage complex sales cycles, collaborate with account executives, sales engineers, field CTOs, and cross-functional teams, and provide customer insights to inform product strategy. Track sales performance and guide customers through AI/ML solution adoption, implementation, and deployment.

DoD SkillBridge Fellows gain practical experience through assigned projects, collaboration with experienced professionals, and exposure to operational processes, technologies, and mission objectives. Opportunities span telecommunications, acquisition and procurement, technology, accounting, finance, and other areas. Participants are compensated by their military employer during the fellowship and may be considered for full-time employment afterward based on performance and organizational needs.

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.

Develop analytical models, simulations, and algorithms for RF, electronic warfare, PNT, communications, and autonomous systems. Perform performance assessments, trade studies, sensitivity analyses, and data validation. Build MATLAB and Python simulation environments and develop navigation, signal processing, tracking, detection, classification, and sensor fusion algorithms. Collaborate with multidisciplinary engineering teams, support prototypes and demonstrations, and contribute to technical reports, customer briefings, proposals, and technology roadmaps.

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.

Develop and deploy AI solutions from problem framing through production. Responsibilities include identifying AI opportunities, leading MVP development, building data pipelines, experimenting with generative LLMs, fine-tuning NLP models, and delivering scalable features. The intern will collaborate cross-functionally, communicate technical impact to business audiences, and work with cloud platforms such as AWS or Google Cloud.