Top AI & Machine Learning Jobs

Designs end-to-end AI solutions aligned with customer outcomes and Presidio capabilities. Partners with sales, engineering, product, and customers on discovery, proposals, RFPs, demonstrations, architectural reviews, and technical feasibility. Creates solution diagrams, reference architectures, and technical documentation; advises customers and supports adoption. The role also mentors junior technical staff, contributes to architecture best practices, and stays current on AI/ML, cloud, data platforms, and modern application architectures.

Build functional, testable AI-powered prototypes for mobile and web customer experiences. Research and integrate LLMs, conversational AI, recommendations, personalization, generative content, voice capabilities, APIs, cloud services, and customer data. Independently turn ambiguous concepts into proof-of-concepts, create reusable components, apply guardrails, and iterate based on customer and user feedback. Collaborate with marketing and design while using AI-native development tools to rapidly explore and validate new experiences.

Lead data science for a core fintech product area, defining metrics, experimentation strategies, causal analyses, and models. Partner with product, engineering, design, and marketing to guide roadmap decisions. Build AI product evaluations, automated scorers, regression tests, and model monitoring practices. Contribute to company-wide data science standards, AI-enabled workflows, and measurement frameworks while mentoring teammates and communicating recommendations to senior audiences.

Design and deliver analyses, reports, and dashboards; translate technical findings for business leaders; perform complex data queries and reconciliation; identify data capabilities and partner with enablement teams; mentor analysts and drive a data-driven culture across functions.

Applied Data Scientist focused on incrementality, causal inference, experimentation, Marketing Mix Modeling, and predictive products. The role partners directly with customers to interpret data, diagnose measurement issues, explain statistical results, and provide actionable recommendations. Responsibilities include building diagnostic tools, analyzing model and experiment outcomes, improving methodologies and production capabilities, and collaborating with Product, Engineering, Media Strategy, Customer Success, and senior data scientists.

Lead Osmo’s Applied AI organization building olfactory intelligence models for prediction, formulation, reformulation, molecule generation, and deformulation. Hire and develop ML engineers and research scientists, set the model roadmap and evaluation standards, own enterprise accuracy commitments, design data and annotation strategies, and move research models into reliable production APIs. This hands-on leadership role partners closely with chemistry, sensory science, software, product engineering, and perfumers while remaining involved in code reviews and experimentation.

Develop machine analytics products using Python, SQL, statistical modeling, machine learning, and industrial IoT data. Build web applications, dashboards, APIs, ETL pipelines, and containerized solutions for machine monitoring, anomaly detection, failure diagnosis, forecasting, and technical support. Collaborate with engineering and service teams to translate diagnostic challenges into practical tools and communicate analytical findings to technical and non-technical stakeholders.

Lead and grow Elliptic’s data science team while remaining technically hands-on. Own research direction, datasets, machine learning models, governance, hiring, performance management, and cross-functional delivery. Build capabilities for compliance involving autonomous agents, improve reliability and throughput, and guide model validation, monitoring, and remediation. The role requires strong Python and SQL skills, modern cloud data-stack experience, AI fluency, technical leadership, and expertise analyzing large behavioral or transactional datasets.

The job description provides limited role details. The AI Fullstack Engineer will presumably help develop AI-powered software solutions for higher education institutions, supporting administrative automation, student engagement, and data-driven decision-making. Specific responsibilities, technologies, qualifications, experience requirements, compensation, travel, and clearance information are not provided.

Owns end-to-end delivery of enterprise fine-tuning engagements, including client discovery, use-case prioritization, ROI, scope, timelines, model hosting, SLAs, security reviews, and stakeholder management. Partners with sales, product, engineering, and machine learning teams; navigates enterprise procurement and IT processes; translates between technical buyers and internal teams; and develops repeatable processes and playbooks to scale the practice.