Top Remote Machine Learning Jobs in Boise, ID

Own the market growth strategy for Luma in biologics research, including segmentation, positioning, competitive analysis, sales enablement, AI use-case development, thought leadership, and customer adoption. Partner across Siemens, Product, Sales, Marketing, Finance, and Services to translate biologics research needs into software value, build market credibility, support strategic pursuits, and drive pipeline and wins.

Designs and builds data ingestion, feature engineering, analytics, and machine learning pipelines using healthcare and other structured or unstructured data. Develops, tunes, deploys, monitors, and documents predictive models and enterprise data products. Collaborates with data scientists, engineers, product managers, and stakeholders while ensuring data quality, reliability, and production engineering standards.

Develop, train, evaluate, deploy, and monitor machine learning and statistical models using Databricks, Python, SQL, Spark, Delta Lake, and MLflow. Prepare datasets, engineer features, manage model lifecycles, validate data, and support governance practices. Translate client requirements into scalable analytics solutions, analyze trends, and communicate findings to technical and non-technical stakeholders while collaborating across data science, engineering, cloud, security, and business teams.

Builds and maintains Power BI reports, dashboards, data models, DAX calculations, and row-level security. Writes SQL queries for reporting, analysis, and data validation; investigates warehouse structures and inconsistencies; and partners with stakeholders and data teams to deliver accurate insights. The role manages recurring and ad hoc reporting requests, communicates findings through data visualization, and supports business decisions across sales, marketing, and operations.

Leads enterprise AI architecture strategy, standards, governance, and roadmaps across products, platforms, data, and business processes. Guides solutions involving generative AI, agentic AI, RAG, machine learning, automation, cloud platforms, and AI infrastructure. Partners with executives and technical teams on architecture reviews, security, compliance, scalability, and cost optimization; mentors senior engineers and provides hands-on leadership through prototypes and critical problem resolution.

Leads commercial analytics and business intelligence strategy, including executive dashboards, account reporting, revenue and pricing analytics, operational KPIs, forecasting, segmentation, and predictive modeling. Partners with Sales, Finance, Marketing, Operations, and Product to improve revenue, profitability, customer retention, and marketplace performance. Presents insights to executives and customers while managing analytics teams, budgets, vendors, and BI scalability.

Senior Commercial Counsel will draft, review, and negotiate complex subscription, partnership, vendor, and other commercial agreements. The role primarily supports a global Sales organization, advises cross-functional teams, manages contracts managers, and handles enterprise and strategic partnership transactions. Responsibilities include balancing competing priorities, supporting legal projects, and providing practical, business-minded legal guidance in a fast-paced environment.

Own end-to-end customer deployments for an AI platform used in mining. Learn site operations, create deployment plans, manage stakeholder cadences, track risks and value, and support adoption. Build reports, dashboards, and lightweight tools using SQL, Python, or AI coding tools. Translate field observations into product requirements, support sales and account expansion, and help establish scalable deployment processes and playbooks.

Own audience or measurement products for Fetch’s monetization business, translating advertiser goals and purchase behavior into predictive models, datasets, and causal studies. Build and validate audience expansion, measure advertising outcomes, assess bias and uncertainty, and improve products using campaign results. Partner with Product, Engineering, Sales, and GTM, present findings to customers, and develop reproducible analyses and production-ready assets.

Designs, trains, evaluates, and operationalizes intelligent document-processing solutions using OCR, machine learning, LLMs, Python, and cloud data pipelines. Builds extraction, validation, reconciliation, exception-handling, and human-review workflows for sensitive information. Develops secure, auditable, configuration-driven systems with API integrations, monitoring, testing, CI/CD, and infrastructure as code. Partners with business experts to define document fields, quality thresholds, validation rules, and acceptance criteria.

Lead product vision and roadmap for data and analytics products (ML, generative AI, data pipelines, BI). Translate business needs into developer-ready features, maintain backlog, collaborate with engineering and stakeholders, track KPIs, and drive adoption and continuous improvement.

Leads end-to-end advanced analytics initiatives, including statistical modeling, machine learning, predictive modeling, customer lifetime value, churn, propensity, and segmentation models. Partners with stakeholders to define analytical opportunities, deploy and govern production models, monitor performance, communicate insights to executives, and mentor analysts. Collaborates with data engineering and IT teams to scale analytical infrastructure and champions emerging tools and techniques.

Manages fraud prevention and identity verification solutions for credit unions and community banks. Develops operational frameworks and controls, provides client consulting, integrates fraud prevention technologies, supports regulatory compliance, and leads a high-performing team. The role oversees client satisfaction, collaborates with internal and external partners, monitors risks, and drives continuous improvement across fraud detection, prevention, investigation, and financial-services risk management.

Leads the launch of BGO’s enterprise sales motion for its AI-first data operations proposition. Responsibilities include developing prospecting strategy and sales playbooks, generating new-logo pipeline, selling complex $1M+ enterprise solutions, building executive relationships, closing transformational deals, supporting AI/ML product integration, and representing the company at industry events. The role partners with marketing, communications, client solutions, and leadership on RFPs, product roadmap development, and strategic market initiatives.

Leads a recruiter pod while personally managing quota-carrying GTM hiring across sales teams and regions. Coaches recruiters, owns hiring quality and funnel performance, partners with sales leadership, and builds an AI-forward recruiting function. The role also develops Boston’s GTM talent community through events, manages reporting and forecasting, and serves as a strategic talent partner for territories, competitors, and workforce planning.

Lead implementations of iQueue for Operating Rooms from discovery through configuration, validation, and rollout. Partner with hospital, clinical, operational, IT, and executive stakeholders to optimize OR workflows, scheduling, staffing, utilization, and access. Responsibilities include data analysis, solution design, product configuration, user acceptance testing, change management, risk monitoring, stakeholder alignment, and go-live readiness. Travel to customer sites is required up to 40–50%.

Designs, builds, scales, and operates distributed CI/CD services supporting millions of builds, tests, and releases. Develops code for Azure-based infrastructure spanning virtual machines, containers, and custom lab environments. Responsibilities include requirements analysis, architecture and design documentation, estimation, debugging, optimization, operational playbooks, on-call incident response, monitoring, reliability improvements, and mentoring engineers.

Provides technical leadership for architecture and evolution of large-scale distributed data platforms supporting Azure network telemetry. Designs streaming and batch systems, establishes reusable engineering patterns, drives cross-team technical strategy, and owns capabilities from design through production operations. Ensures scalability, reliability, security, performance, data quality, and operational excellence while mentoring engineers and influencing technical leaders. The role also involves architectural reviews, dependency management, risk reduction, and applying AI or machine learning approaches to operational systems.

Own technical wins for strategic enterprise sales, partnering with Account Executives to discover customer needs and develop production-ready solutions. Build proofs of concept, demonstrations, prototype AI agents, and supporting tools while engaging AI teams, data platform teams, and enterprise architects. Apply hands-on experience with LLMs, agents, data science, machine learning, or data engineering to explain how agents retrieve data and use business context.

Develop and deploy machine learning, statistical, operational research, and semantic analysis solutions for large, complex datasets. Build applied, predictive, and prescriptive analytics; conduct exploratory data analysis; assess and cleanse data; collaborate with software and data engineers to commercialize algorithms; and document and communicate findings to technical teams, stakeholders, and customers.

Lead technical client onboarding, migrations, solution design, integrations, data orchestration, troubleshooting, and project delivery for Movable Ink’s AI-powered personalization platform. Partner with clients and internal teams to implement custom workflows, APIs, webhooks, and data solutions. Conduct training and workshops, provide product expertise, advise on roadmap improvements, and support long-term client success across email and mobile marketing programs.

Analyze large datasets, identify meaningful patterns, develop machine learning models, and deliver actionable insights for business decisions. Collaborate with cross-functional teams to understand data needs, communicate findings clearly to stakeholders, and stay current with advances in data science and AI technologies.

Serve as primary client contact for a portfolio of loyalty-program clients. Scope and manage end-to-end actuarial analyses rooted in predictive modeling and machine learning, validate model outputs, translate results into clear recommendations and presentations, and partner with analysts and data scientists to deliver high-quality, client-facing work in a fully remote consulting environment.

Leads cyber risk assurance strategy and multidisciplinary teams responsible for control monitoring, testing, evidence management, issue remediation, audit support, regulatory readiness, and assurance automation. The role advances continuous, AI-enabled assurance by translating regulatory and cybersecurity requirements into measurable outcomes, maintaining assurance frameworks, evaluating control effectiveness, managing concurrent activities, and reporting metrics to support executive risk decisions.

Analyze telematics, IoT, sensor, and firmware data to evaluate hardware performance, reliability, and field issues. Build dashboards and reports, identify trends and anomalies, apply statistical and machine learning techniques, validate firmware improvements, and provide actionable insights to engineering, product, data science, and customer support teams. Help develop scalable data pipelines and promote data-driven hardware and software development.