Top Machine Learning Jobs in Boise, ID

Lead design, build, and deploy scalable, reliable Java-based microservices in a cloud-native, event-driven AWS environment. Own backend feature design, code quality, automated testing, and FedRAMP release processes. Mentor engineers, participate in on-call/TechOps, integrate AI tools into development, and drive architecture, observability, and cross-team initiatives.

As a Customer Success Engineer, you'll drive adoption and satisfaction for enterprise customers using Deepgram's voice AI technology, fostering strong relationships and aligning technical solutions with business objectives.

Lead and manage the underwriting and credit risk model validation team, perform hands-on independent validations of complex ML models, assess data integrity and performance, identify and remediate model weaknesses, partner on MRM framework improvements, and coordinate with audit, compliance, and controls to meet regulatory standards.

Lead long-term technical strategy and execution across multiple teams, architecting and evolving foundational frontend/backend systems and platforms at massive scale. Drive AI/ML adoption, solve ambiguous, high-impact problems, remain hands-on in critical system design and implementation, and align senior leaders on roadmaps and engineering standards.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

Lead and transform the Fraud Intelligence Team by designing scalable operating models, QA and measurement frameworks, and talent programs. Drive labeling quality, operational metrics, and fraud prevention impact; convert frontline fraud observations into insights for Product, R&D, Analytics, and GTM; leverage AI, automation, and tooling; and serve as a cross-functional fraud subject-matter expert while developing early-career talent and measurable business outcomes.

Lead the design and implementation of critical Safety AI initiatives, focusing on real-time perception systems for edge devices and optimizing models for production deployment in safety-critical environments.

Lead strategy and execution for enterprise and mid-market GTM across multi-unit restaurant brands. Drive C-suite engagements, modernize sales motions, scale AI-powered forecasting, partner with Product/Engineering, and represent Toast in industry forums to win large, complex contracts.

Lead strategy and execution to attract, engage, and retain a global community of Pluralsight authors. Build author communications, engagement programs, communities, recognition, and events. Elevate author visibility (Author Fellows), integrate author expertise across Sales, Marketing, Customer Success, Product, and Learning Experiences, and lead a multidisciplinary team to drive measurable business impact.

Lead a global product team building automation-first, AI-assisted investigation and agent-facing tooling for AML, KYC, EDD, and sanctions screening. Define roadmap, metrics, vendor strategy, and regulatory controls to improve investigation quality, cycle time, and operational efficiency while ensuring security, privacy, and auditability.

Optimizes and manages digital manufacturing processes and systems in an on-site Guadalajara role. Provides SRV escalation support, aligns operations with global strategy, supports migration from GSF to Critical Manufacturing, identifies technical gaps, develops digital manufacturing solutions, mentors team members, prepares technical reports and presentations, and maintains compliant documentation. Uses automation, analytics, simulation, and machine learning to improve production efficiency, quality, agility, and cost performance.

Supports FP&A and enterprise analytics by developing scalable Power BI reporting, financial models, dashboards, and automated processes. Analyzes financial and operational datasets to identify trends, risks, and opportunities; improves forecasting, budgeting, and recurring reporting workflows using Excel, Python, SQL, Power Automate, and Microsoft platforms. Collaborates with finance, data engineering, IT, and business stakeholders, trains users, maintains governance standards, and contributes to the Pigment planning platform. Evaluates AI-enabled tools to improve reporting efficiency, data quality, and decision-making.

Partner with healthcare clients to discover, design, and deliver production-grade AI/LLM solutions. Architect cloud-native systems, build and deploy ML/LLM applications, prototype rapidly, troubleshoot distributed systems, and lead client engagements to drive measurable business outcomes while collaborating across product, platform, and engineering teams.

Lead B2B activation marketing to drive patient starts from commercial referral channels by building scalable systems, attribution frameworks, and repeatable playbooks. Implement MarTech and data-driven strategies, run A/B and incrementality tests, automate campaign execution using AI/ML and LLM tools, and templatize activation campaigns while managing and growing a cross-functional team.

Lead design and implementation of Headway's insurance systems (eligibility, pricing, matching, claims). Build data-intensive, ML-powered platforms and automation, mentor engineers, write high-impact code, and improve accuracy and reliability across state and payer complexity to scale insurance-covered therapy.

Conduct research on AI tokenomics by evaluating model architecture trends, building simulation models for training and inference efficiency across hardware and workloads, diligencing companies using model tokens, and forecasting economic impacts for investors, corporates, and policymakers.

Own global GTM enablement for a Databricks product area, creating scalable technical content, competitive narratives, demos, labs, AI-powered tools, and learning programs for Solutions Architects and partner technical sellers. Partner with Product and Engineering to translate roadmaps into field-ready assets, establish feedback loops, measure field readiness and deal outcomes, and support selected customer-facing engagements. Build enablement programs from scratch while remaining hands-on with data and AI platforms.

Own Linktree’s production AI platform, including pipelines, model and prompt versioning, evaluations, monitoring, rollback, cost, latency, and reliability. Drive internal AI adoption through tooling, agent workflows, and enablement across Product, Engineering, Marketing, and Support. Establish practical governance for data handling and vendor risk, make build-versus-buy decisions, align AI investment with business priorities, and mentor engineers and analysts.

Evaluate AI model outputs on data science, statistics, machine learning, experimentation, and quantitative problems. Develop expert prompts, datasets, and reference solutions; identify statistical and methodological errors; and provide structured feedback to improve model performance. The role requires Python, machine learning, statistics, data analysis, experimentation, Pandas, and data modeling skills.

Own product vision, strategy, backlog, prioritization, and delivery for Clubessential SaaS products. Translate stakeholder and customer needs into requirements and user stories, coordinate engineering, design, QA, and business teams, and support Scrum ceremonies, releases, launches, demos, and educational efforts. Identify and guide responsible AI and automation opportunities, define success metrics and guardrails, manage feedback and issue resolution, and partner across implementation, support, marketing, sales, and data teams.

Design, productionize, and scale machine learning and optimization models, pipelines, libraries, and deployment platforms. Partner with data scientists, engineers, product managers, and business stakeholders to deliver ML capabilities, personalization systems, and reusable end-to-end workflows. Establish ML engineering best practices, troubleshoot data pipelines, mentor junior professionals, and help define BetterHelp’s ML platform strategy.

Manage enterprise metadata, business glossaries, data catalogs, and end-to-end data lineage for a federal case management modernization program. Configure governance and metadata platforms, integrate data sources and pipelines, establish standards and workflows, monitor metadata quality, support compliant data sharing, develop governance metrics, document procedures, and train data stewards and business users.

Build and integrate AI-driven systems across dashboards, revenue platforms, CRM, and marketing workflows. Develop predictive lead scoring, forecasting, NLP, segmentation, propensity models, chatbots, automated outreach, and revenue intelligence dashboards. Analyze GTM performance and marketing ROI, improve data quality, support experimentation, and collaborate with Sales, Marketing, and Client Success teams to drive acquisition, retention, and growth. Lead AI adoption and provide training across revenue teams.

Own customer outcomes from discovery through production deployment. Build decision systems using ontologies, reasoning, graph analytics, optimization, and machine learning over enterprise data. Write Python, SQL, and PyRel; debug unfamiliar systems; tune performance; harden deployments; document reusable solutions; and upstream platform improvements. Lead technical workshops and proofs of concept while partnering closely with customers, Product, and Engineering.