Top Remote Machine Learning Jobs in Indianapolis, IN

Build and improve Confluence AI experiences across frontend, backend, and AI integrations. Own features from design through launch, apply generative AI, retrieval, agents, and evaluation techniques, create automated quality testing, monitor production performance, run adoption experiments, and collaborate cross-functionally. Mentor engineers and contribute to architecture, observability, testing, safeguards, and scalable software delivery.

Leads the design, development, and delivery of production machine learning and AI systems for government and commercial customers. Responsibilities include data shaping, analytics, model development and optimization, production deployment, technical planning, customer engagement, and mentoring cross-functional engineering teams. The role requires translating complex technical concepts for internal and external stakeholders and traveling up to 25% of the time.

Lead Amazon performance marketing strategy and execution, manage Sponsored Ads and DSP, collaborate with agencies and cross-functional teams, optimize campaigns and budgets, analyze performance with AMC/analytics, and measure commercial impact to drive ROAS and customer acquisition.

Leads strategy, roadmap, investment, and execution for horizontal AI capabilities, shared AI platforms, and AI-native cybersecurity products. Translates AI research into reliable, secure, scalable customer solutions; drives adoption across product teams; establishes launch and autonomy criteria; partners with customers and cross-functional leaders on commercialization; and builds a high-performing AI product organization.

Leads complex, cross-functional technical programs for the Superintelligence Lab. Responsibilities include roadmap execution, milestone and dependency management, risk mitigation, issue resolution, stakeholder alignment, leadership reporting, and implementing program-management best practices. The role requires collaboration with engineering, data science, and leadership teams while using AI technologies and Jira to improve workflows, decision-making, and business outcomes.

Lead firmware and embedded software development for AI-powered video safety products. Architect scalable embedded systems, integrate camera and real-time edge computing capabilities, deploy CV/ML models, and guide technical decisions. Collaborate with hardware, cloud, machine learning, and product teams on next-generation devices and complex multi-team projects. Maintain production systems, improve testing and release infrastructure, mentor engineers, and support products from development through mass production.

Leads the Safety AI organization and architecture for on-device and cloud-based computer vision and machine learning systems. Oversees sensor fusion, model lifecycle management, platform architecture, experimentation, deployment, monitoring, and continuous improvement across more than two million dashcams. Partners with product, firmware, full-stack, and platform teams to deliver reliable, low-latency safety features. Builds and develops teams of applied scientists and engineers while driving measurable improvements in driver safety and customer outcomes.

Lead the design and implementation of AI initiatives for edge devices. Develop and optimize machine learning solutions using large-scale sensor, video, text, diagnostic, transaction, and location data. Partner with engineering and business teams to prototype AI experiences, ship production systems, adopt research advances, and improve edge model performance. Mentor ML engineers and communicate technical concepts to varied audiences.

Own the full B2B sales cycle across EMEA and the US, from outbound prospecting and opportunity creation through negotiation, closing, and account expansion. Sell content syndication, qualified leads, and intent-led demand-generation programs to senior marketing and sales decision-makers. Build pipeline, meet revenue targets, maintain accurate CRM forecasts, grow existing accounts, and collaborate with delivery, data, media, and client success teams.

Own the full sales cycle for enterprise B2B demand-generation clients across EMEA and the US. Responsibilities include prospecting, building outbound pipelines, developing account strategies, engaging executive buyers, negotiating complex contracts, closing net-new business, expanding accounts, forecasting accurately, and collaborating with delivery, data, media, marketing, and client success teams.

Leads a multidisciplinary data science and data engineering team supporting Finance. Sets strategy, prioritizes initiatives, guides analytical models and data architecture, advances AI and machine learning applications, improves data quality and reliability, establishes scalable operating processes, and communicates technical recommendations to Finance and executive stakeholders. The role also manages talent, oversees forecasting and decision-support outcomes, and drives measurable business impact.

Leads GitLab’s Product, Sales, and Finance Data Science teams, managing managers and a 12-person organization. Sets data science standards, prioritizes investments, partners with executives, drives product adoption and revenue growth, and oversees experimentation, causal inference, predictive modeling, and AI initiatives. Develops talent, builds succession, and collaborates with Analytics Engineering and Data Engineering on a shared data and AI roadmap.

Leads AI and automation product strategy for disability and absence claims operations. Responsibilities include prioritizing AI opportunities, owning roadmaps, designing human-in-the-loop workflows, defining safeguards and success metrics, partnering with engineering, coaching Product Owners, managing delivery increments, and communicating operational impact to senior leadership.

Owns strategic planning, governance, prioritization, risk management, and execution across a portfolio of Superintelligence Lab programs. The role establishes phase-gate standards, manages change, tracks portfolio health through dashboards and metrics, resolves blockers, advises cross-functional teams, and communicates progress to executives. It requires strong technical program management experience, Jira proficiency, Agile and SDLC knowledge, and the ability to apply AI technologies to improve business outcomes.

Build and deploy production-grade AI and machine learning solutions for marketing and sales, including LLM agents, data-quality pipelines, semantic search, RAG, analytics, and integrations with Salesforce, Marketo, and Adobe platforms. Define evaluation and governance practices, monitor AI services, implement privacy controls, and collaborate with platform teams. Train and mentor technical and business stakeholders on responsible AI adoption while supporting DevOps, incident response, and operational runbooks.

Leads AI transformation, governance, quality oversight, risk management, and responsible adoption across Pfizer Global Supply and QSEO. Establishes GxP-compliant AI lifecycle practices, inspection-readiness frameworks, governance forums, portfolio monitoring, inventory management, metrics, and reporting. Advises senior leaders on AI regulations, deployment risks, investment priorities, and compliance while leading cross-functional initiatives and influencing stakeholders across Quality, Digital, Operations, and R&D.

Lead machine learning architecture and technical direction across multiple quarters while remaining involved in experimentation, quality, and production systems. Work across model post-training, personalization and recommendation, and agentic experiences. Define solutions for ambiguous problems, align cross-functional partners, drive execution, and safely bring ML systems into production.

Own and grow strategic enterprise customer relationships, driving retention, renewals, expansion, and seven-figure software transactions. Develop multi-year account plans, build executive and technical stakeholder relationships, identify expansion opportunities, lead negotiations, maintain forecasts and pipeline visibility, and coordinate cross-functional teams. Engage with data scientists and AI/ML engineers to understand adoption, customer outcomes, and opportunities to expand platform usage across business units and use cases.

Own the strategic vision and roadmap for Coursera’s AI-driven search experience. Lead conversational search, personalization, semantic and multilingual search, ranking, and discovery improvements. Partner with engineering, design, research, data science, ML, marketing, and partnerships teams to deliver scalable platform capabilities. Use experimentation, market analysis, KPIs, and customer insights to improve conversion, merchandising, learner experience, and revenue.

Leads GitLab’s Product Data Science team, setting its strategy, roadmap, analytical standards, and priorities. Partners with Product and Engineering leaders on experimentation, causal inference, analytics, and production modeling. Manages, hires, coaches, and retains data scientists while building a high-performing function. Provides hands-on technical review of models, analyses, and queries, and communicates insights and risks to senior leaders.

The Data Scientist will partner with Sales, Revenue Operations, and Finance to analyze GTM performance, build and productionize machine learning models, conduct experiments, forecast outcomes, and identify growth opportunities. Responsibilities include statistical analysis, causal inference, Python and SQL development, MLOps, agentic workflow automation, semantic-layer contributions, executive reporting, and communicating insights to nontechnical stakeholders in a fully remote environment.

Deploys, configures, optimizes, and supports CrowdStrike Falcon’s AI-powered detection and response capabilities. The role tunes machine learning models, develops security automation playbooks, troubleshoots customer environments, integrates Falcon with existing tools, supports threat hunting and forensic analysis, and develops AI training and customer-facing materials. Requires extensive IT deployment, endpoint, security automation, operating system, AI/ML, scripting, and customer consulting experience, with travel up to 25%.

Leads SailPoint’s global corporate communications function, including corporate narrative, media relations, PR campaigns, crisis communications, executive coaching, podcast strategy, partner communications, and measurement. The role manages internal and agency teams, translates complex cybersecurity and AI concepts into compelling stories, supports product launches and company milestones, builds rapid-response capabilities, and advises executives on reputation and communications strategy.

Develop and deploy scalable machine-learning solutions, particularly deep-learning forecasting models for company top-line metrics. Lead the full ML lifecycle from problem definition and experimentation through production deployment and improvement. Design production-grade architectures, evaluate and improve models, collaborate with cross-functional teams, explain technical concepts to varied audiences, and mentor junior engineers.

Develop and deploy machine learning and LLM capabilities for agentic search, query understanding, search planning, and retrieval. Build evaluation datasets, improve model behavior through experimentation and fine-tuning, and optimize quality, latency, cost, and reliability. Collaborate across search, product, infrastructure, and AI teams while owning projects through production and mentoring engineers.