Top Remote Machine Learning Jobs in Reno, NV

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.

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.

Build and deploy production AI/ML systems that optimize Samsara’s global hardware supply chain. Responsibilities include demand, inventory, cost, lead-time, supplier-risk, anomaly-detection, and cash-flow modeling; real-time inference pipelines; MLOps; data infrastructure; governance; and cross-functional AI adoption. The role also sets the supply-chain AI roadmap, mentors junior scientists, establishes modeling standards, and partners with Planning, Procurement, Finance, Engineering, and Operations.

Build and scale production machine learning solutions for lottery fulfillment. Develop and optimize computer vision and multimodal models, fine-tune and evaluate models, create data pipelines and evaluation frameworks, and deploy models on cloud infrastructure. Integrate models into real-time systems involving image processing, barcode decoding, and OCR. Collaborate cross-functionally, improve engineering standards, mentor teammates, and support reliable nationwide expansion.

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.

Own the strategy, architecture, development, deployment, monitoring, and continuous improvement of production personalization and recommendation systems. Build custom embeddings, ranking models, and shared representations across feeds, search, and recommendations. Lead ambiguous problems from concept to measurable customer impact, establish AI evaluation standards, partner with product and data teams, make cross-team technical decisions, and coach senior engineers.

Lead growth data science initiatives by partnering with Marketing, Sales, and Customer Experience leaders. Develop analyses, experimentation frameworks, and machine learning models for acquisition, engagement, retention, monetization, targeting, segmentation, uplift modeling, and lifetime value prediction. Productionize reliable models with engineering teams, communicate insights to senior stakeholders, establish experimentation best practices, and mentor junior data scientists. The role requires strong business judgment, advanced technical expertise, and experience operating in ambiguous, zero-to-one environments.

Designs, develops, deploys, and supports complex enterprise data pipelines, data models, ETL/ELT processes, and analytical solutions. Leads data governance engineering initiatives involving metadata catalogs, lineage, data quality, and remediation. Builds governed, AI-ready datasets and integrates AI capabilities into production data workflows while validating performance, security, privacy, and reliability. Collaborates with business, technology, data science, and application teams to deliver scalable, compliant solutions.

Build and deploy production machine learning systems for personalized recommendations, fraud detection, risk scoring, ranking, classification, and anomaly detection. Own the full ML lifecycle, including mathematical formulation, feature engineering, training, evaluation, A/B testing, deployment, monitoring, and reliability. Develop low-latency real-time inference services using large-scale donor and transaction data, collaborate with Platform and DevOps teams, and mentor engineers on ML best practices and scientific rigor.

The General Counsel will lead the in-house legal function, advise executive leadership and the Board, manage legal teams and outside counsel, and oversee corporate, regulatory, privacy, AI, employment, intellectual property, litigation, and contract matters. The role will guide product and sales initiatives, develop scalable legal workflows, manage risk, support HR, and advise on consumer protection, fintech regulations, data privacy, and emerging AI frameworks as the company expands.

Build backend services, data pipelines, detection features, and AI agents for email security. Integrate machine learning and large language models into investigation workflows, evaluate attack detection accuracy, improve reliability and performance, and own features from design through production release. Collaborate with ML engineers, data scientists, and software engineers while contributing tested code, technical designs, and code reviews.

Lead managed services for clients' Azure, Databricks, and Microsoft Fabric data environments. Architect, implement, monitor, troubleshoot, and govern data platforms, ETL pipelines, data warehouses, semantic models, reporting, and AI/ML solutions. Manage incidents and SLAs, advise clients on licensing and technical strategy, communicate solutions, document environments, and mentor distributed engineering teams.

Leads enterprise business intelligence, analytics, data science, and AI-assisted analysis strategy. Oversees analytics modernization, predictive modeling, data governance, semantic frameworks, reporting standards, and reliable data access for business users and AI tools. Partners with Product, Engineering, Data Engineering, and AI Enablement teams to deliver governed datasets and analytical capabilities. Builds and develops high-performing analytics and data science teams while communicating strategy, quality, performance, and business outcomes to executives.

Leads technical discovery, enterprise solution architecture, technology assessments, and implementation roadmaps for consulting clients. Designs architectures across applications, data, cloud, integration, and enterprise technology; advises executives on technology decisions, scalability, security, cost, and risk. Guides technical teams, resolves complex delivery challenges, develops proofs of concept and reusable standards, evaluates emerging technologies, and supports proposals, estimates, statements of work, and new business development.

Build and own ClickUp’s AI evaluation systems, agent harness, self-improvement loops, model benchmarking, routing, and fallback strategies. Architect scalable backend and AI platform services for LLM deployment, orchestration, monitoring, logging, and automated evaluation. Improve reliability, privacy, security, and compliance while integrating AI features into the core product and collaborating cross-functionally.

Own company-level strategic initiatives, establish measurable goals, diagnose delivery risks, and recommend resource reallocations. Lead cross-functional transformation focused on go-to-market scalability, annual planning, quarterly reprioritization, monthly business reviews, and AI-enabled operational reporting. Partner with executives and functional leaders to improve the operating model, automate KPI tracking, communicate priorities, and increase organizational velocity.

Supports energy and sustainability analytics for data center clients by cleaning, validating, and analyzing datasets; developing Power BI or Tableau dashboards, dataflows, and reports; documenting methodologies; performing quality checks; and delivering accurate outputs across concurrent projects. Collaborates with energy and sustainability teams, learns internal analytics platforms, and identifies opportunities to improve reporting, automation, and workflows.

Own the full enterprise sales cycle for Neuron7.ai’s AI-powered Service Resolution Intelligence platform. Responsibilities include prospecting, executive discovery, strategic account planning, ROI development, technical evaluations, negotiation, procurement, and closing new-logo enterprise deals. The role targets high-tech, manufacturing, and medical device organizations, requiring independent pipeline generation, accurate forecasting, executive relationship management, and collaboration with solution consultants, architects, product, and customer success teams.

Own regional enterprise revenue and go-to-market strategy for AI-powered field service solutions. Lead pipeline generation, forecasting, territory planning, major new-logo deals, and C-level relationships. Hire, coach, and retain Account Executives while driving disciplined sales execution across high-tech, manufacturing, and medical device industries. Lead strategic enterprise sales cycles and position Agentic AI and automation solutions for complex service operations.

Leads Cohere’s global Customer Success, Services, and Technical Support teams, driving adoption, customer experience, lifecycle strategy, and executive-level customer advocacy. Defines workflows and handoffs, coaches functional leaders, analyzes customer and support data, improves the customer journey, and influences product strategy. Partners with pre-sales, Product Management, and Machine Learning Engineering to represent customer needs and deliver value to enterprise AI customers.

Own strategy and execution for a gaming-oriented B2C mobile app focused on advertising, rewards, loyalty, and commerce. Responsibilities include roadmap and backlog management, analytics and A/B testing, conversion optimization, user research, competitive analysis, product documentation, prioritization, and cross-functional collaboration with engineering, design, marketing, legal, operations, and support teams.

Own Carrum Health’s member and employer growth funnels, including landing pages, activation journeys, eligibility and sign-up flows, experimentation, attribution, and lower-acuity service-line launches. Partner with engineering, design, marketing, sales, care, compliance, and machine learning teams to improve conversion and access to specialty care. Lead a growth pod, build scalable content systems, use AI for rapid prototyping, and optimize responsibly within healthcare privacy and clinical guardrails.

Lead technical strategy and architecture for Azure Storage geo-replication, data protection, failover orchestration, and business continuity. Drive cross-team delivery, operational excellence, telemetry, automation, AI-assisted operations, and represent the team in executive and customer engagements.

Own product and research launch marketing from technical positioning through distribution. Translate AI research, training runs, and benchmarks into blogs, explainers, social content, landing pages, documentation, sales collateral, and campaigns. Engage technical communities, coordinate cross-platform launches, and use analytics to optimize reach, engagement, traffic, and adoption. The role requires strong technical writing, product marketing judgment, rapid execution, and experience communicating AI, ML, or developer tools to developers and enterprise audiences.