Top Entry Level Machine Learning Jobs in Raleigh, NC

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.

Develop and integrate computer vision and machine learning algorithms for autonomous agricultural and off-highway equipment. Responsibilities include geometric computer vision, SLAM, localization, mapping, triangulation, depth estimation, camera calibration, data collection and processing, model development, training, optimization, deployment, and monitoring. The role uses cameras, LiDAR, radar, edge devices, robotics, cloud technologies, C++, and Python while collaborating onsite with engineering teams.

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.

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.

Write technically accurate case studies, articles, product explainers, launch materials, and social content for AI engineers, researchers, and technical leaders. Interview customers, partners, and internal experts; learn HUD’s platform and workflows; explain technical products and research clearly; support founder communications; manage content from ideation through publication; and improve content using reader and go-to-market feedback.

Build and deploy scalable AI/ML systems for retrieval, ranking, categorization, triage, and generative AI across healthcare data. Own solutions end-to-end from problem framing and model selection through production deployment and optimization. Collaborate with software engineers, product managers, clinicians, and operations teams to translate complex business problems into explainable, maintainable systems with measurable outcomes.

Develop technical employment-marketing content that showcases Socure’s engineering challenges, architecture, APIs, machine learning, identity, fraud, and infrastructure work. Interview engineers and technical leaders, write blogs, deep dives, whitepapers, and recruiting copy, and distribute content through developer communities, publications, social channels, and talent platforms. Partner with engineering, recruiting, employer brand, marketing, design, and subject matter experts while maintaining editorial quality and using AI tools thoughtfully.

Sets technical vision for Pinterest’s ML and media infrastructure, leading distributed training, fine-tuning, evaluation, inference, GPU optimization, content ingestion, and signal-processing architectures. Partners with AI/ML, Ads, Content, Shopping, and GenAI teams to productionize reliable, scalable platforms, drive architecture decisions and migrations, improve operational standards, and mentor senior engineers.

Freelance writers summarize recent machine learning research papers for The Batch, an AI newsletter reaching over two million professionals and students. Writers must understand machine learning technology, explain complex research clearly in an established format, and communicate effectively in English. The role is intended for graduate students and postdocs in machine learning, with negotiable freelance compensation.

Own Avon AI’s US go-to-market motion, including enterprise prospecting, discovery, demos, pilots, negotiations, forecasting, and closing deals with regulated organizations. Build demand through outbound campaigns, events, webinars, partners, and resellers. Develop the sales process, messaging, qualification framework, and playbook while helping recruit the future US sales and marketing team. Collaborate closely with founders and product teams, translating customer and market feedback into product direction.

Build and scale pipelines that transform conversation data into structured customer memory. Develop LLM extraction and retrieval systems using embeddings, vector search, and ranking; create evaluation benchmarks and regression gates; diagnose production issues through logs, metrics, and traces; and partner with Product and ML teams to improve customer-focused AI systems.

Design, develop, evaluate, and refine machine learning models using Python. Manage training data with MongoDB, build preprocessing and data pipelines, tune hyperparameters, benchmark model performance, document experiments, and deliver data-driven insights. Collaborate remotely with cross-functional contributors and support deployment or operationalization of models in cloud or enterprise environments.

Develop, implement, and deploy scalable machine learning models for healthcare solutions. Collaborate cross-functionally to integrate models, analyze data to improve performance, ensure data quality, and stay current with ML advancements to support patient care and operational efficiency.

DoD SkillBridge Fellows gain practical experience through assigned projects, collaboration with experienced professionals, and exposure to operational processes, technologies, and mission objectives. Opportunities span telecommunications, acquisition and procurement, technology, accounting, finance, and other areas. Participants are compensated by their military employer during the fellowship and may be considered for full-time employment afterward based on performance and organizational needs.

Support partner sales opportunities through discovery calls, product demonstrations, technical responses, solution scoping, project planning, proof-of-concept coordination, RFI/RFP responses, and security questionnaires. Collaborate with sales, professional services, product, engineering, and delivery teams while building partner relationships and developing expertise in fraud prevention and financial crime solutions.

The Tarbell Fellowship combines three months of remote training in AI and journalism fundamentals with a nine-month newsroom placement as an artificial intelligence reporter. Fellows write and investigate AI-related topics, build journalism skills, complete coursework and assignments, and attend a weeklong in-person summit. The program is full-time and intended for candidates with journalism or AI expertise, strong writing ability, persistence, curiosity, and open-mindedness. Senior fellowships are available to candidates with at least seven years of experience and exceptional prior work.

Instructor-led AI and machine learning training covering theory, data preprocessing, algorithms, model building, analytics, real-time projects, case studies, and practical business and IT applications. Participants use Python, TensorFlow, and Scikit-learn and receive certification upon successful completion.

Lead research on improving AI agent training data and evaluations. Manage and mentor research engineers, define research direction, design rigorous experiments, validate data quality, diagnose reward and grading failures, and translate findings into scalable tools, workflows, and standards. Collaborate with engineers, domain experts, and vendors while communicating technical conclusions and tradeoffs clearly.

Build and maintain mission-critical wealth management systems for SMB clients. Design data pipelines, ETL/ELT processes, data models, warehouses, analytics, and reporting solutions using AWS, Snowflake, Mage AI, and other big data tools. Collaborate with data scientists and analysts on predictive models, statistical analyses, and machine learning algorithms. Develop software with Next.js and Python while working closely with the team and clients on financial-domain challenges.

Provide technical pre-sales expertise for Jumio’s identity verification, KYC, AML, authentication, and risk management solutions. Responsibilities include consulting with prospects, leading technical presentations, responding to RFPs and RFIs, managing proofs of concept, onboarding customers through go-live, delivering customized web and mobile demos, and supporting sales, account management, product, engineering, and marketing teams.

Conduct frontier AI research and build research-grade datasets, prototypes, tooling, reinforcement learning environments, benchmarks, and evaluation frameworks. Design rigorous experiments, train and evaluate models, investigate synthetic and agentic data generation, and translate findings into scalable products. Collaborate with research, engineering, product, and operations teams, communicate technical insights, contribute to publications and open-source work, and mentor peers. This is a fully onsite role based in San Francisco, Palo Alto, or Seattle.

Conduct original research to evaluate, train, and improve frontier AI systems. Design benchmarks, synthetic-data methods, reliability and hallucination evaluations, verification techniques, and agentic science workflows. Identify research gaps, formulate hypotheses, build experiments and evaluation pipelines, publish findings, and develop new research directions across STEM and AI. The role requires strong Python skills, quantitative reasoning, technical writing, and expertise with modern LLMs.

Build scientific advisory and technical enablement programs for enterprise and research partners adopting an AI materials platform. Engage computational chemists and materials scientists, provide technical guidance, lead workshops and demonstrations, create documentation, notebooks, APIs, and reference materials, and relay partner feedback to AI Research, Chemistry, Product, Marketing, and PR teams.

Design, build, evaluate, and deploy LLM-powered agents and machine learning systems that improve Quora content quality and safety. The role involves developing agentic workflows, conducting offline and online evaluations, monitoring production performance, investigating failures, and improving accuracy, reliability, latency, and cost. New graduates will collaborate with experienced engineers and own projects from development through production.

Lead Cure from company formation through product-market validation and seed financing. Define the market wedge, secure enterprise design partners, shape an AI-native recovery product, establish data and evaluation loops, recruit the founding team, build the company narrative, and lead fundraising. The role requires enterprise AI judgment, commercial credibility, consumer-finance and regulatory understanding, and founder-level ability to create a new category.