Top Machine Learning Jobs in Boise, ID

Design, productionize, and deploy machine learning forecasting models for ad inventory and campaign performance in low-latency, real-time advertising environments. Build scalable simulation, budgeting, and pacing systems; collaborate with cross-functional teams to deploy models at scale and optimize ad monetization.

Lead design, execution, and optimization of scaled lifecycle campaigns across email and in-product channels. Use marketing automation, behavioral data, and ML techniques to personalize journeys, drive activation, revenue, retention, and cross-sell. Analyze performance, generate insights, and collaborate with Growth, Product, Engineering, Data Science, Analytics, Sales, and Marketing stakeholders.

Lead design, execution, and interpretation of A/B tests and quasi-experiments; apply causal inference methods; partner with product, engineering, and marketing; mentor data scientists; build experimentation frameworks; extract and analyze data using SQL and Python; communicate results to stakeholders.

Design, train, and productionize machine learning models for fraud and identity risk across the full ML lifecycle. Research new fraud types, perform feature engineering and labeling, write production-ready code for real-time decisioning, monitor models, and provide analyses to inform product, sales, and data acquisition.

The Senior Product Manager will set product direction, own the development lifecycle, collaborate with teams, and ensure high-quality outputs. This role requires strong opinions on product quality and customer insights.

The Enterprise Account Executive drives revenue through high-value contracts, managing complex sales processes and relationships with executive stakeholders in financial services.

Lead the Decision Science function, designing ML models, overseeing experimentation frameworks, and ensuring model adoption across the company, driving operational and commercial improvements.

Serve as the technical post-sales contact for enterprise customers: drive adoption of JetBrains products, manage technical account relationships, advise on architecture and tooling, advocate customer needs to product and support teams, recommend enhancements, support product evaluations, and collaborate with sales to grow accounts. Requires travel (~25%) and bilingual English with Portuguese and/or Spanish.

Serve as the technical point of contact for enterprise accounts, driving adoption of JetBrains products, advising on architecture and tooling, advocating customer needs to product and support teams, enabling account expansion with Sales, and delivering product demonstrations and technical guidance. Travel roughly 25% required.

Lead go-to-market and partner development for Personal Loans and Point-of-Sale products. Own end-to-end enterprise sales, build C-level relationships, close complex deals, and coordinate cross-functional teams to launch AI-driven consumer lending integrations and scale market presence.

Author and verify rigorous multiple-choice computer science assessment items across many CS domains to create gold-standard benchmarks for AI research. Produce correct answers, nine plausible distractors, solution explanations, difficulty labels, and authoritative references. Review and edit questions for technical accuracy, clarity, and reproducibility. Contribute asynchronously as an independent contractor, ~10+ hours/week, fully remote.

Define and execute the product roadmap for AI-driven on-chain monitoring tools to detect blockchain threats. Collaborate with engineering, research, and stakeholders, analyze market and customer feedback, prioritize features, ensure timely delivery, and maintain transparent communication across teams.

Lead a global manufacturing engineering organization to standardize processes, drive lean continuous improvement, deploy automation and Industry 4.0 solutions (cobots, ML), and ensure safety, traceability, and zero-defect customer quality across international sites.

Lead security engineering for an AI-native cybersecurity product: architect product security, build and evolve operational security and incident response, collaborate with ML engineers to integrate security into AI agents, implement protections and automation, and represent Cogent externally through writing and speaking.

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.

Partner with a retained search firm to place software engineers and quant developers at top hedge funds. Provide candidate flow from your network; firm supplies clients, process, and fees. Remote, commission-only role with placement and pipeline incentives. Apply with placement examples, outreach metrics, and a candidate submission.

Leads development and productionization of large-scale machine learning models and pipelines for search, ranking, and personalization. Works with structured and unstructured data, builds batch and real-time systems, improves model serving and experimentation, and collaborates cross-functionally to drive business impact. Responsibilities include feature engineering, model optimization, infrastructure development, low-latency serving, interpretability, drift detection, and operating high-scale ML systems.

Own and close the company’s largest, most complex public-sector enterprise deals. Prospect and grow territory, navigate multi-stakeholder procurement, manage forecasting and pipeline, expand revenue within major accounts, and mentor Account Executives by providing strategic deal support and operational leadership.

Lead technical strategy and hands-on engineering for Airbnb's AI-powered ads growth engine. Architect scalable systems for creative generation, bidding, budget optimization, and audience management across paid channels. Write and review code, set standards for availability and quality, collaborate with Marketing/Product/ML teams, roll out staged automation, and mentor engineers to advance platform autonomy while ensuring brand safety and human-in-the-loop controls.

Lead and align ML, data, and engineering teams to define multi-year AI roadmaps, deliver production ML solutions, ensure robust data pipelines, set success metrics tied to business outcomes, and grow/mentor senior managers and engineers.

Lead and build a data science organization to create a prediction engine for vendor matching, order routing, and supply chain optimization. Anchor projects to P&L, design measurement and experiment frameworks, ship rapid wins, hire and coach data scientists, work hands-on in modeling and technical design, partner with product and engineering (Snowflake), and evolve systems toward agentic AI while reporting impact in dollar terms.

Build, ship, and own end-to-end ML models for vendor matching, order routing, and supply-chain optimization. Partner with data engineering to productionize models, quantify impact, document work, and implement decision logic components toward agentic AI in a fast-moving healthcare startup environment.

Own end-to-end modeling for vendor matching, order routing, and supply-chain optimization. Build predictive, causal, RL and OR solutions; design autonomous decision logic; quantify counterfactual impact; ship production models with data engineering; mentor senior data scientists; write technical design docs; partner on quarterly priorities and expand into revenue cycle and finance domains.

Own scalable backend services and full-stack features for Apartment List’s property-listing platform. Design Kotlin and Ruby services, build TypeScript and React interfaces, make architectural decisions, improve reliability and performance, and collaborate with product, design, and analytics. The role includes mentoring engineers, conducting code reviews, shaping technical roadmaps, and solving ambiguous technical problems involving APIs, databases, distributed systems, and marketplace experiences.

Develop and optimize the systems powering large-scale distributed machine learning training. Responsibilities include profiling performance with Nsight and PyTorch Profiler, optimizing data loading and communication, developing GPU kernels in Triton or CUDA, and improving training throughput, reliability, and cost using PyTorch Distributed.