Top AI & Machine Learning Jobs

Develop and deploy machine learning models and analytical solutions from data exploration through production. Apply feature engineering, model selection, statistical analysis, and model evaluation while ensuring data quality, governance, and ethical analytics. Translate business problems into actionable insights, resolve technical challenges, and collaborate with engineering, product, operations, and stakeholders in cross-functional teams.

Build and own production AI-powered products across the frontend, backend, data, and cloud stack. Design multi-agent systems and RAG pipelines, orchestrate AI workflows, and deploy reliable, scalable features. Responsibilities include model serving, latency and cost optimization, prompt engineering, model evaluation, cloud infrastructure, and end-to-end product development using React, Node.js, PostgreSQL, and major cloud platforms.

Conduct applied computer vision and deep learning research for automated construction drawing takeoff and estimation. Own a scoped research problem, train and evaluate models for detection, segmentation, or structured extraction, explore self-supervised learning and multimodal signals, develop prototypes using real data, design evaluations, and present findings to the research team.

Lead platform architecture, development, and reliability for an AI-driven molecular discovery product. Build agentic workflows, full-stack UI features, integrate Console/Builder/Solutions apps, and implement API integrations with sequence and assay providers to support model training, deployment, and researcher workflows.

Develops statistical and machine-learning models for pricing strategy, revenue optimization, demand forecasting, segmentation, and utilization analysis. Designs experiments, validates and documents models, prepares large-scale datasets, and partners with data engineering teams on scalable pipelines and deployment. Translates analytical outputs into pricing recommendations, dashboards, and decision tools while supporting governance, stakeholder presentations, and analyst enablement.

Develop and optimize machine learning and statistical models for fraud detection and anti-money laundering. Analyze large datasets to identify fraudulent patterns, build scalable data pipelines and features, evaluate model performance, and collaborate with engineering, product, and operations teams. Communicate insights to technical and non-technical stakeholders while maintaining data privacy and security compliance. The role offers significant ownership in building Oscilar’s early machine learning stack within a remote-first startup.

Build and architect a production-grade Agentic AI platform for autonomous medical reasoning, initially serving as a hands-on technical lead. Establish orchestration, state management, tools, memory, guardrails, evaluation, and compliance frameworks. Transition into managing and scaling an engineering team, setting technical strategy, delivering AI-driven products, and collaborating with product, clinical, and data science teams. Ensure secure, accurate, deterministic, and FDA-compliant software through strong engineering, testing, logging, and deployment practices.

Build and maintain predictive models throughout their lifecycle, identify data patterns and business insights, develop analytic procedures and automation, perform complex ad hoc analyses, monitor model recalibration, and review model scoring and data transformation quality controls.

Assists with developing, testing, documenting, implementing, and maintaining data science projects and applications. Builds proof-of-concept models using machine learning, optimization, simulation, and generative AI; develops data pipelines and data products; translates business requirements into solution requirements; supports simple to moderate applications and daily IT functions while following cybersecurity practices.

Build and operationalize AI-enabled creative workflows, including prompts, templates, agents, integrations, training, and quality standards. Prototype interactive, generative, web-based, and experiential concepts. Own MATTE’s website and lead client-facing digital builds from concept through launch, including design, development collaboration, QA, responsiveness, accessibility, and performance. Maintain Figma libraries, digital systems, templates, archives, and external technical partnerships while translating creative vision into polished technical execution.