Top Entry Level Machine Learning Jobs in Houston, TX

Supports the design, validation, and operationalization of predictive, machine learning, and AI models. Analyzes structured and unstructured data, develops algorithms, validates outcomes, creates visualizations, and communicates findings to stakeholders. Collaborates cross-functionally to integrate solutions and prepares model pipelines for business use. The role also involves statistical analysis, NLP, exploratory data analysis, feature engineering, and research into emerging technologies.

Leads Utility’s AI practice by defining its roadmap, overseeing AI research and deployment, identifying client opportunities, mentoring AI teams, and establishing responsible AI practices. The role combines technical leadership, product strategy, client advisory, and operational execution across machine learning, generative AI, and intelligent automation initiatives.

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.

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.

Build and operate the platform that schedules, runs, and monitors machine learning training, evaluation, and reinforcement-learning workloads on Kubernetes. Responsibilities include job scheduling, workload networking, runtime isolation, checkpoint storage, automation, infrastructure as code, observability, and production troubleshooting. The role collaborates with AI researchers and ML engineers and includes a compensated 24/7 on-call rotation.

Build production agentic applications that automate complex geoscience workflows. Responsibilities include designing multi-agent workflows, integrating tools and APIs, managing persistent state, implementing human-in-the-loop controls, enabling retrieval and evidence grounding, fine-tuning LLMs, evaluating and tracing agent performance, and delivering tested web services with CI/CD. The role also requires sound product judgment, collaboration with domain experts, and responsible use of AI coding agents.

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.

Evaluate, deploy, and optimize machine learning models for on-device execution on Android phones. Benchmark models on mobile hardware, optimize latency, memory, and power consumption, and apply quantization, compression, and distillation. Integrate models with Android applications, system services, and AI agent runtimes. Build hybrid local/cloud model routing and determine which workflows should run locally versus through cloud inference.

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.

Lead complex software and technology initiatives from planning through delivery. Manage scope, schedules, resources, dependencies, risks, roadmaps, Agile processes, and stakeholder communication. Provide technical leadership across cloud, data, AI, APIs, architecture, and enterprise integrations. Coordinate distributed engineering and product teams, guide solution decisions, and ensure scalable, secure, high-quality delivery of AI and data-focused products.

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.

Support and improve manufacturing operations through automation, equipment qualification, troubleshooting, root cause analysis, data analysis, and production process optimization. Develop and validate hardware and software solutions using LabVIEW, SQL, Python, PLCs, and analytics tools. Support equipment testing, performance metrics, yield improvement, downtime reduction, and early production ramp activities. The role is on-site in Sugar Land, Texas, with 5–10% international travel.

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.