Top Entry Level Machine Learning Jobs in Las Vegas, NV

Analyze malware, binary files, customer detection tickets, and machine learning detections to improve detection efficacy and manage false positives. Review product detections, assess legitimacy and risk, address internal detection questions, and provide insights to data science teams. The role collaborates with technical account managers, incident response teams, data scientists, and malware researchers.

Analyze malware, binary files, customer detection tickets, and machine learning detections to improve detection efficacy and reduce false positives. Review product detections, assess binary legitimacy, address internal detection questions, and provide insights to data science teams. The role collaborates with technical account managers, incident response teams, data scientists, and malware researchers. Required capabilities include malware analysis, reverse engineering, Python scripting, binary fundamentals, threat assessment, research methods, operating systems, and AI-assisted workflow improvement.

Leverage data science, machine learning, statistical analysis, and big-data techniques to solve business problems and support commercial strategy. Develop, deploy, and measure models, algorithms, automation, and analytical solutions. Collaborate with BI and enterprise data teams to improve reporting, visualizations, and data models. Present insights and recommendations to varied audiences while tracking business impact and evaluating emerging data engineering technologies.

Build and operate production AI capabilities across enterprise platforms, including agent runtimes, RAG, model routing, tool calling, guardrails, evaluation, monitoring, and cost optimization. Ship reliable, safe, measurable AI features; develop evaluation frameworks and quality controls; monitor production behavior; and collaborate with client-facing product, engineering, platform, backend, and security teams to deliver practical AI solutions.

Build and deploy generative AI solutions for creative enterprise workflows across image, video, 3D, vector graphics, and design. Partner with customers to identify opportunities, prototype integrations, adapt multimodal models, integrate AI into production systems, diagnose technical issues, evaluate solution quality, and develop reusable deployment patterns. Collaborate with research, product, engineering, and design teams to translate customer needs into scalable technical solutions.

Research and improve real-time conversational AI for voice drive-thru ordering. Responsibilities include advancing speech, intent, turn-taking, voice activity detection, and order-accuracy models; curating and generating data for rare scenarios; building statistically rigorous benchmarks; evaluating audio and conversational quality under real-time constraints; and translating research into production improvements with applied AI and backend teams.

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.

Rotational technology development program providing hands-on experience across cybersecurity, data analytics, technical product and project management, artificial intelligence, application development, and IT infrastructure. Participants receive structured training, mentorship, and leadership development while contributing to healthcare-focused digital transformation initiatives.

Design and deploy production-ready LLM pipelines and agentic workflows, automate large-scale multimodal dataset pipelines, monitor and improve agent performance, and integrate AI agents with 3D scene composition. The role also involves process documentation, incident response, and continuous improvement, with collaboration across the engine team and company founders.

Develop threat models, statistical verification algorithms, calibrated tests, and production verification services for decentralized training and inference on untrusted heterogeneous hardware. The role focuses on detecting incorrect model outputs, malicious training behavior, free-riding, poisoning, data extraction, and reward manipulation while controlling false positives and negatives. Candidates need deep statistics and probability expertise, experience shipping or publishing calibrated decision systems, and familiarity with statistical testing, re-execution, cryptographic proofs, and trusted hardware.

Provides clinical expertise, customer support, product demonstrations, training, onboarding, and certification for Transpara Breast AI across the USA and Canada. Supports research initiatives, clinical adoption, customer engagement, NPS tracking, workshops, webinars, educational content, case curation, and customer feedback resolution. Collaborates with Sales, Customer Success, Marketing, Engineering, Innovation, and Product Management teams. Requires medical imaging experience, preferably in mammography or breast imaging AI, strong communication and training skills, and approximately 20% travel.

Develop and support internal low-code applications and AI agents using Microsoft Power Platform and Copilot Studio. Assist with API and database integrations, automated testing, Agile delivery, intelligent automation, documentation, and application monitoring. Collaborate with cross-functional teams to create secure, compliant, reliable digital solutions that improve enterprise productivity and workflows. The role is remote with occasional travel to Vermeer campuses.

Develop and deploy mineral exploration instruments, sensor systems, data acquisition methods, and proprietary software. Integrate geospatial, geophysical, geochemical, geological, and geographic data; build statistically rigorous and physics-based models; identify ore-forming anomalies; and generate 2D and 3D exploration predictions. Collaborate with data scientists, engineers, geoscientists, vendors, and external partners to design field programs, deploy sensors, reduce uncertainty, and guide exploration decisions.

Owns the end-to-end product strategy and execution for AI-powered systems. Defines requirements, evaluation frameworks, quality standards, and system behavior while balancing quality, latency, cost, reliability, safety, and user experience. Partners closely with ML, backend, and client engineering teams to identify failure modes, improve model performance, prioritize roadmaps, and deliver predictable, useful, trusted AI experiences.

Own the end-to-end strategy, requirements, quality, and execution of an AI-powered email product. Partner closely with ML, backend, and client engineers to define system behavior, evaluate model performance, manage trade-offs across quality, latency, cost, reliability, safety, and UX, and establish feedback loops. Drive prioritization, specifications, experimentation, failure handling, and product quality in a technical zero-to-one environment.

Design, build, and deploy production-ready intelligent solutions using machine learning, deep learning, generative AI, and large language models. Develop RAG pipelines, integrate AI services, manage model deployment and MLOps workflows, and apply strong software engineering practices. Collaborate with engineering, product, and data teams in a distributed environment to create scalable, reliable, responsible AI-powered products.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

Clean, standardize, enrich, and import product data into the PIM while maintaining data integrity and governance standards. Oversee bulk ingestion processes, leverage AI and automation, support data model improvements, resolve product listing issues, and contribute to data hygiene and workflow modernization. The role also involves collaborating with client-facing teams, documenting processes, proofreading product data, communicating progress, and adapting to changing priorities.

Review, label, and QA datasets for AI/ML training; maintain trackers, databases, and dashboards; follow annotation guidelines and SOPs; prepare and clean data; document processes; collaborate to resolve data queries while ensuring confidentiality and timely delivery.

Design, develop, and implement AI/ML models; analyze large datasets; integrate AI solutions into existing systems; apply MavLink for autonomous systems; collaborate across teams and improve ML development processes.

OneSix is seeking motivated professionals for future opportunities in data and AI consultancy. Interested candidates should submit their resumes to stay in touch.

Join Invoca's Talent Community to stay updated on job openings and to explore exciting career opportunities across various departments.

The AI/Machine Learning Specialist designs and implements AI solutions, collaborates with cross-functional teams, and continuously improves ML processes.

Design and implement machine learning and optimization algorithms for Netflix’s ad marketplace. Build, train, and evaluate models using large-scale production data; develop online and offline evaluation frameworks; and partner with product teams to define objectives and trade-offs. Communicate technical decisions and experiment results to diverse stakeholders while providing technical guidance and aligning ML solutions with business goals.

This is an open talent‑community posting inviting U.S.-based candidates across multiple disciplines (software, AI/ML, XR, UX/UI, DevOps, cybersecurity, data, instructional design, etc.) to submit a resume and brief introduction. HTX Labs will retain candidate information for future contract-to-hire opportunities. Must be authorized to work in the U.S.; no visa sponsorship available. Remote-first role supporting immersive learning for Department of Defense clients.