Top Machine Learning Jobs in Indianapolis, IN

Senior leader responsible for building and scaling pre-award solution engineering capabilities to support federal sales. Oversees technical demonstrations, RFP/RFI responses, demo readiness, reusable accelerators, and cross-functional alignment with Growth and executive leadership to drive differentiated, secure solutions using modern data and AI platforms.

Senior individual contributor responsible for leading pet/P&C insurance pricing model development (GLMs and ML), owning end-to-end projects, performing EDA and root-cause analysis, communicating results to stakeholders, and mentoring junior team members.

The role involves engaging in data labeling, annotation, content evaluation, and user-based testing to support AI/ML projects, with flexible work opportunities.

As an AI/ML Data Contributor, you will perform data labeling, content evaluation, and assist in improving machine learning models. This flexible role may involve both remote and on-site tasks.

Assist in improving machine learning models through data labeling, content evaluation, and user-based testing tasks, both remote and on-site.

Lead development of an AI-enabled Ethereum Layer 2 platform: build front-end and back-end systems, deploy and optimize AI models, create data pipelines, collaborate on model training, and contribute to product innovation and other company projects.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

Embed with clients to gather requirements and design AI-driven solutions for fraud and fincrime. Architect, train, evaluate, and deploy custom AI agents and workflows, optimize model performance, establish risk metrics and evaluation pipelines, and collaborate with engineering/product teams to scale into production.

Sell HiddenLayer's AI security platform to federal agencies by developing account strategies, driving pipeline and revenue, leading technical and executive engagements, navigating federal acquisition and contracting, coordinating cross-functional teams, and supporting adoption, expansion, and renewals across the Intelligence Community, DoD, DHS, and civilian agencies.

Own Oscilar's AML product suite (transaction monitoring, KYC/KYB, screening, case management, SAR filing, AI agents). Define detection rules, model calibration, data strategy, and defensible audit trails. Collaborate with engineers and compliance, use AI across discovery/design/analysis, deliver PRDs, validate models, and ship production features.

This is a general talent-community application inviting candidates across many functions to submit resumes. Recruiting will review and retain applications for future openings; candidates should highlight experience, accomplishments, and interests for potential remote roles.

Lead end-to-end research applying advanced ML/DL (transformers, GNNs, RL, ensembles) to generate alpha across digital asset markets, build production-grade pipelines, prevent leakage/overfitting, analyze microstructure and on-chain data, and mentor junior researchers.

As Director of AI/ML, lead the ML organization, set technical vision, mentor a high-performing team, and contribute to model development and production deployment.

The AI & Data Science Director will lead AI strategies, foster technical leadership, support team development, and integrate generative AI into products.

Lead high-impact strategy and BizOps workstreams including M&A diligence, investor relations, new-market expansion, and cross-market operations. Frame ambiguous, board-level problems, build analysis and recommendations, align stakeholders, and own execution end-to-end while leveraging AI and automation.

The AI Sales Executive drives new business growth and expands client relationships by selling AI-driven solutions for engineering and manufacturing sectors, managing the full sales cycle with a consultative approach.

Develop and deploy end-to-end machine learning solutions, collaborate with cross-functional teams, and implement MLOps frameworks while monitoring model performance in production.

The Senior Generative AI Engineer will design and deploy AI/ML solutions, focusing on Generative AI systems and their operational excellence across various sectors like R&D and Clinical Trials.

This role involves leading strategic planning, product innovation, and cross-functional collaboration to enhance pharmacy analytics and drive growth initiatives for CVS Health.

As Software Engineering Manager, you'll lead a team in enhancing content workflows through automation and AI, develop scalable solutions, and manage cross-functional collaboration.

Conduct ML research for query understanding, ranking, clustering, and AI-powered search. Prototype and productionize algorithms, define data and evaluation requirements, design scalable systems, collaborate with engineers, run experiments, and publish patents/papers to integrate state-of-the-art ML into Yahoo Search products.

Summer data science internship working on ML projects (anomaly detection, numerical optimization, PII/PHI NLP). Interns will develop models, write high-quality Python, use Linux and development tools, work with git, Docker, CI/CD and Kubernetes, participate in code reviews and agile rituals, and present results to technical and non-technical audiences.

Develop and productionize AI features from PoC to scalable deployments. Write production-ready Python code, implement testing and debugging, refine user stories, participate in ethical and security reviews, and collaborate with stakeholders to align AI solutions with business needs.

Build and maintain full-stack product features, backend services, APIs, data pipelines, and AI integrations to transform customer interaction data into AI-powered experiences. Collaborate with cross-functional teams to design, test, and support production systems, internal tools, and user-facing interfaces. Own ambiguous problems end-to-end and raise engineering quality across the data and AI platform.

Lead a team to develop groundbreaking technology combining NLP, big data, and AI to enhance digital communication and interaction.