Top Machine Learning Jobs in Huntsville, AL

Leads complex enterprise AI consulting engagements, designing and implementing generative AI, agentic AI, MLOps, model-serving, and infrastructure solutions. Advises executives, leads architecture reviews and technical governance, supports sales pursuits, develops standards and reusable offerings, and mentors technical teams. The role requires strong expertise in AI architecture, NVIDIA technologies, Python, Kubernetes, GPU infrastructure, security, operations, and client-facing consulting.

Leads the supply chain compliance program supporting defense, government, and Intelligence Community customers. Develops policies, controls, supplier due diligence, risk assessments, audits, flow-down requirements, corrective actions, reporting, and training. Partners cross-functionally to manage regulatory, cybersecurity, quality, export, sanctions, and information-protection obligations. Evaluates ERP, GRC, contract lifecycle, automation, analytics, and AI solutions to improve compliance visibility and supplier risk management. Advises executives and teams while maintaining audit-ready records and supporting supplier visits and customer engagements.

Leads ServiceNow consulting engagements, architecture, engineering, automation, and deployment across enterprise clients. Oversees technical solutions across projects, supports presales and SOW reviews, mentors engineers and architects, conducts customer workshops, and serves as an escalation point. Develops standardized approaches using CI/CD, infrastructure as code, cloud, containers, and AI technologies while supporting practice growth and client relationships. Travel is estimated at 10%.

Define and own the technical vision, product strategy, roadmap, data strategy, and AI integration for CrowdStrike’s Next-Gen SIEM and log management products. Translate customer, market, and threat intelligence into shipped capabilities; lead cross-platform integration across endpoint, cloud, identity, and exposure products; and articulate the platform consolidation narrative. Engage executives, customers, analysts, sales, engineering, and product teams while driving detection, investigation, response automation, and cybersecurity thought leadership.

Build and maintain core infrastructure for developing, training, evaluating, deploying, and operating machine learning models and pipelines for Atlassian’s GenAI products. Solve complex software infrastructure and architecture challenges, lead engineers through technical projects from design to launch, and collaborate with internal teams and customers. The role involves large-scale distributed systems, data processing, cloud platforms, CI/CD, and machine learning lifecycle support.

Designs scalable data architectures, ELT/ETL pipelines, data models, quality frameworks, and self-service data platforms. Partners with engineering, product, program, leadership, and data science teams to translate business needs into technical solutions. The role includes end-to-end technical ownership, large-scale batch and streaming data processing, mentoring junior engineers, system optimization, and on-call support for platform stability.

Build and deploy production-grade AI and machine learning solutions for marketing and sales, including LLM agents, data-quality pipelines, semantic search, RAG, analytics, and integrations with Salesforce, Marketo, and Adobe platforms. Define evaluation and governance practices, monitor AI services, implement privacy controls, and collaborate with platform teams. Train and mentor technical and business stakeholders on responsible AI adoption while supporting DevOps, incident response, and operational runbooks.

Leads frontier research and engineering for AI-powered cybersecurity systems. Defines research direction, designs agentic and autonomous security applications, builds evaluation environments, improves systems through feedback and adversarial simulation, and transitions prototypes into scalable production capabilities. Provides technical leadership across teams, mentors senior researchers and engineers, and contributes to research publications, open source, and the broader AI and cybersecurity communities.

Leads technical pre-sales for supply chain integration solutions, partnering with Sales to conduct discovery, design ERP/WMS/TMS and trading-partner architectures, run POCs, deliver demonstrations, and respond to RFPs. Advises technical and executive stakeholders on business outcomes and AI opportunities, translates capabilities into measurable ROI, and collaborates with Product, Customer Success, and Professional Services on roadmap feedback and post-sale handoffs.

Lead product strategy, roadmap, and delivery for Falcon Complete’s internal MDR tooling, including AI-powered investigation and triage, ticketing, case management, and analyst workbench systems. Partner with security operations, analysts, engineering, and data science teams to translate workflows into product requirements, prioritize automation, improve analyst productivity and response times, define success metrics, and enhance customer outcomes.

Develop and implement data science strategies for machine learning applications including lead scoring, churn modeling, pricing, personalization, and fraud detection. Own end-to-end initiatives spanning data analysis, feature engineering, model training, inference, and monitoring. Collaborate with engineering, infrastructure, analytics, and business teams to deliver measurable impact, improve data capabilities, and communicate findings to technical and non-technical stakeholders.

Build scalable systems and machine learning models that transform satellite imagery into labeled geospatial data and production computer vision products. Responsibilities include developing data and annotation pipelines, tracking lineage and versioning, deploying inference services, evaluating models, supporting cloud infrastructure, and improving labeling workflows. The role requires strong Python, cloud, containerization, CI/CD, infrastructure-as-code, production support, and deep learning expertise, with preferred experience in GCP, Vertex AI, spatial databases, and satellite imagery.

Own and scale Jellyfish’s security engineering program, including strategy, architecture, secure SDLC governance, AI security, threat modeling, vulnerability remediation, incident response, penetration testing, and bug bounty programs. The role combines hands-on software development with executive advising, cross-functional leadership, mentorship, and security risk management across SaaS infrastructure and customer-facing AI products.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Own the strategy, roadmap, requirements, launch, adoption, and success metrics for a technical platform. Partner with engineering, data, product, and business teams; evaluate architecture, APIs, and system tradeoffs; prioritize foundational investments against customer and revenue outcomes; and apply AI to improve platform capabilities. The role requires strong product management experience, technical depth, analytical skills, and production experience with LLM-based or ML-adjacent products.

Lead AMP's multidisciplinary engineering organization to define and execute technology vision and roadmap. Responsible for scaling teams across hardware, software, AI, and infrastructure; driving product development, quality systems, and reliable deployments; partnering with execs and cross-functional teams on budgets, prioritization, and metrics; recruiting and mentoring leaders; and balancing short-term delivery with long-term investments to create business value.

Leads multidisciplinary systems engineering solutions across defense and space programs. Responsibilities include capturing stakeholder needs, developing requirements and architectures, conducting modeling, simulation, trade studies, and risk analysis, and guiding product-oriented solutions through the lifecycle. Leads teams of 5–10, mentors engineers, communicates with senior stakeholders, develops technical best practices, and serves as a digital engineering thought leader. The role also supports technology assessment, organizational transformation, new business development, proposals, and collaboration with experts across academia, government, and industry.

Develop full-stack agentic cybersecurity capabilities, including user interfaces, APIs, backend services, data storage, and orchestration workflows. Design agents that reason over mission context, select approved tools, maintain state, and coordinate tasks. Implement authorization boundaries, human approvals, audit logging, observability, and failsafe controls. Collaborate with cyber operators, AI engineers, architects, and product teams to support adversary emulation, operational visibility, results analysis, and continuous capability evaluation.

The GRC Analyst manages third-party risk assessments, vendor due diligence, security policies, risk analysis, internal audits, and SOC 2 audit support. The role involves maintaining the GRC program, tracking findings, coordinating stakeholders, promoting security awareness, and using AI and machine learning to automate compliance processes. Candidates should have 1–2+ years of relevant experience, strong communication skills, and familiarity with risk methodologies, vendor assessments, policies, and compliance audits.

Analyze complex software, hardware, and communication systems to identify vulnerabilities and understand their operational impact. Perform static and dynamic analysis, reverse engineer software, develop custom analysis and testing tools, analyze and inject datalink messages and communication protocols, and document vulnerabilities in detail.

Design, build, and maintain scalable data pipelines, warehouses/lakes, and platforms. Lead multidisciplinary teams to implement ETL/ELT (batch and streaming), optimize data lake performance, enforce data governance, and support analytics and ML use cases on cloud and on-prem environments.

Develop and support software, automation tools, dashboards, and alarms for cloud infrastructure, cost attribution, and cloud efficiency. Collaborate with cross-functional teams and senior engineers to design reliable systems, APIs, databases, tests, and AI agents. Contribute to architecture and automation strategies while maintaining strong security, communication, and delivery practices.

Leads the strategy, technical direction, and delivery of insurance data science across pricing, underwriting, cost modeling, demand modeling, and growth. Oversees predictive modeling standards, model lifecycle governance, engineering collaboration, regulatory alignment, and production deployment. Builds and develops a high-performing data science organization while partnering with actuarial, product, underwriting, pricing, and executive leadership to connect analytical work with profitability and business outcomes.

Lead rapid proof-of-concept research and development projects, build tangible technology products, and support commercialization through government and private-sector proposals. Apply expertise in software, machine learning, electrical, mechanical, or materials engineering while collaborating across teams. Identify relevant research, design experiments, protect intellectual property, and evaluate technologies for product potential. The role requires technical ingenuity, self-directed execution, business development experience, and the ability to obtain an active Secret clearance.

Leads rapid proof-of-concept technology projects, develops tangible products, applies expertise in engineering, software, machine learning, or materials science, and supports government and private-sector business development. Requires strong technical ingenuity, collaboration, communication, commercialization, and proposal experience. The role requires a bachelor’s degree in a scientific or engineering field, 15+ years of engineering experience, and an active Secret clearance or ability to obtain one.