Top Machine Learning Jobs in Huntsville, AL

One-year, full-time fellowship supporting design, delivery, and evaluation of interventions for smallholder farmers. Duties include research and analysis, pilot design, field implementation, M&E, and cross-team collaboration with heavy mentorship and rotating in-country placements.

Support revenue cycle by performing coding reviews, claim scrubbing, and payer audit management to prevent denials and recoupments. Use Power BI, advanced Excel, and a machine-learning tool to detect trends, validate exceptions, and drive upstream/downstream interventions. Liaise with stakeholders, track payer audit performance, and deliver operational improvements and monthly scorecards to leadership. Remote role focused on mental/behavioral health revenue integrity.

Lead planning, execution, and optimization of cross-functional hardware and software projects for robot development, manufacturing, testing, upgrades, and deployments. Coordinate mechanical, electrical, embedded, systems, manufacturing, and operations teams, define scope and timelines, mitigate risks, implement process improvements, run sprints, and maintain project documentation and stakeholder communication.

Lead statistical activities for Phase I-IV clinical trials from protocol design through reporting. Represent statistics on cross-functional teams, oversee programmers/CROs, perform QC and inferential analyses using SAS/R, apply statistical, machine learning and deep learning methods for modeling/simulation, and mentor junior statisticians.

Lead Woolpert's partner marketing for the Google relationship: develop and execute joint go-to-market plans, run integrated campaigns, enable sales, create partner collateral, measure KPIs, and coach one specialist to drive co-selling and pipeline growth for Digital Innovations.

Lead statistical activities for Phase I-IV clinical trials from protocol design through reporting. Provide statistical oversight, collaborate cross-functionally, supervise programmers/CROs, apply SAS/R and ML/DL methods for analyses and automation, and support regulatory, safety, and publication deliverables.

Lead development of Vanta's business analytics function: build scalable product data assets, define measurement frameworks, use AI-assisted analytics, partner with cross-functional teams, and deliver executive-level recommendations to drive product and business decisions.

Lead and grow a global engineering team building endpoint visibility, prevention, and on-device ML across Windows, macOS, and Linux. Own roadmap and delivery, direct model development and telemetry, drive cross-platform protection parity, coordinate with product and partner teams, and represent the team externally through research and conferences.

Build and own end-to-end product features across React/TypeScript frontend, Ruby on Rails backend, relational databases, and GCP/AWS infrastructure. Partner with product, design, clinical, and operations teams to translate complex healthcare workflows into simple experiences. Improve reliability and performance, mentor engineers, raise engineering standards, and integrate AI-powered features into production.

Lead statistical activities for Phase I-IV clinical trials from protocol design through reporting. Represent statistics on cross-functional teams, oversee programming/CRO work, perform QC, inferential analyses, modeling/simulation, and apply machine learning/deep learning to generate actionable insights. Mentor junior statisticians and support safety, publications, and regulatory responses.

The Digital Engineering Data Solutions Architect will develop data architectures, support system lifecycle management, and collaborate on innovative solutions in national security projects.

Lead and execute full-lifecycle capture and proposal activities, manage BD team and pipeline, develop customer and partner relationships, and align BD strategies with corporate technical capabilities and priorities to win defense contracts.

Lead statistical design and analysis for Phase I-IV clinical studies, develop protocols and SAPs, perform efficacy and exploratory analyses, run simulations, apply advanced methods (mixed models, longitudinal), oversee datasets (ADaM/CDISC), use R and SAS for analyses, and provide strategic statistical guidance to cross-functional teams supporting regulatory submissions.

Lead strategy, build and scale a global partnerships ecosystem (ERP, fintech, banks, ISVs, VARs, SIs) to drive partner-sourced pipeline, revenue, and platform expansion. Own partner negotiations, commercial models, cross-functional integration, and team development while leveraging AI/data insights and ensuring compliance.

Lead and grow a team of 5-7 enterprise sales reps in the Bay Area, recruit and develop sales leaders, build business plans, drive new-logo acquisition and account expansion, manage the sales cycle from lead generation to close, develop GTM strategy, and report to the VP of Sales. Role supports ambitious quarterly and annual goals and may require occasional work outside standard hours.

Drive supply chain efficiency through data analytics, KPI development, process redesign, ERP/WMS/automation selection and implementation, Lean Six Sigma continuous improvement, AI-driven forecasting, cross-functional project leadership, audits, and change management with suppliers and 3PLs.

Sell ExtraHops network security analytics to U.S. Federal/Department of War customers by developing territory accounts, engaging senior federal decision-makers, driving new business and renewals, coordinating with resellers and engineers, delivering tailored demos, and executing strategic account plans to meet revenue targets.

Design and implement data integration and data warehouse solutions using Big Data and open-source technologies. Build cost-efficient, performant cloud data pipelines, apply data modeling and ML concepts, and implement real-time streaming and aggregation patterns. Hands-on SQL/NoSQL and programming experience required.

Lead the vision and execution of data product roadmap; translate business needs into epics and acceptance criteria; partner with data engineering and analytics; run agile ceremonies and manage backlog; champion data-as-a-product; scope and pilot AI/ML capabilities; present roadmaps and business cases to leadership.

The Machine Learning Engineer will build data-intensive products, deploy ML models, analyze datasets, and collaborate with product teams to enhance Nextdoor's platform.

Sell Fiddler’s AI observability platform to enterprise customers: prospect, navigate complex multi-stakeholder deals, demonstrate technical and business value for ML/AI solutions, close revenue, grow accounts, and collaborate cross-functionally. Travel as needed (10–25%).

Build and maintain high-performance, reliable backend systems for Yahoo Mail AntiSpam and Delivery. Design and develop complex server applications on Unix, leverage cloud platforms (GCP/AWS), containerization (Docker/Kubernetes), and ML/AI models to detect and deliver messages. Troubleshoot, optimize performance, and collaborate cross-functionally to ensure scalability and uptime.

Lead Merlin's civil certification program (FAA/EASA) while managing Military Airworthiness and Cyber Certification teams. Own certification strategies, liaison with regulators, integrate cybersecurity with safety and systems engineering, oversee compliance documentation, drive process standardization and continuous improvement, and report program health to the VP of Airworthiness & Certification.

Full-cycle territory sales role selling Greenway Health's EHR, RCM, and AI-driven healthcare solutions. Responsibilities include prospecting, lead generation, demos, RFP management, proposal configuration, negotiation, closing, maintaining Salesforce, meeting quota, and providing market feedback. Role requires heavy travel (50–75%) and collaboration with internal solutions consultants to deliver value-based technology and revenue cycle capabilities to ambulatory healthcare clients.

Conduct research and develop identity and probabilistic-matching models for Netflix's ad-supported tier. Apply ML and statistical methods, ensure privacy-preserving solutions (differential privacy, anonymization), prototype and deploy production models, deliver datasets and tools, and partner with product, engineering, and business stakeholders to measure and drive impact.