Top Machine Learning Jobs in Indianapolis, IN

The Technical Product Owner drives product vision and execution by translating business needs into technical requirements and collaborating with teams to deliver cloud-ready solutions, championing Agile practices.

Lead pre-sales technical engagements for Conversational and Generative AI solutions, collaborate across teams, and design value-driven demos for enterprise customers.

Lead the Data Science & POCs team to optimize fraud analytics and decision systems, managing projects, mentoring staff, and collaborating with teams to reduce fraud losses.

Lead the strategy and execution of AI-powered neuro solutions at Viz.ai, collaborating cross-functionally and driving commercialization efforts.

The role includes developing B2B marketing strategies, collaborating with sales, creating targeted materials, and conducting market research to support growth.

Lead a small engineering team in developing and deploying core product functionality, ensuring high quality and security standards. Collaborate with cross-functional partners while managing and scaling the team effectively.

The Principal Partner Marketing Manager will lead strategic co-marketing initiatives, develop joint marketing plans, execute integrated campaigns, enable field teams, and collaborate cross-functionally to drive awareness, demand, and revenue growth through partnership with Microsoft.

As a Machine Learning Engineer, you'll evaluate neural network quality, coordinate with researchers, manage experiments, and report results to streamline AI software development.

The Product Manager will lead platform offerings, engage with cross-functional teams, define product metrics, and ensure the integration of intelligent machines for customers.

The role involves leading a team to design, develop, and implement AI-driven applications on the ServiceNow platform while managing all aspects of application development and integration with other systems.

Lead the Data & Analytics team, focusing on building data platforms, improving delivery speeds, and integrating Generative AI into data strategies.

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.

Lead the Data Science team, overseeing the development and deployment of ML solutions, managing analytics workflow, and collaborating with cross-functional teams.

As a Lead AI Engineer, design and implement AI and machine learning models and pipelines to enhance healthcare outcomes and efficiency.

The Lead Database Engineer designs and oversees data architecture, leveraging AI and machine learning to manage structured and unstructured data and ensure data integrity.

The Associate Principal leads Data & AI business development, managing client relationships and driving market strategies to exceed client expectations.

The Research Scientist at Yahoo will design machine learning solutions, analyze data, and collaborate with engineering teams to implement research results.

Lead the Revenue Optimization team for Netflix's ad business, focusing on optimization algorithms and collaboration with various stakeholders to enhance advertising systems.

As a Senior Data Scientist, you will leverage statistical modeling and machine learning to optimize ad-related projects, collaborating with various teams to drive impactful product decisions and metrics measurement.

As a Senior Data Scientist/Machine Learning Engineer, you'll develop and deploy machine learning solutions, engage with clients, and optimize data processes.

As an ML Platform Engineer, you will enhance our core ML platform's performance and scalability, collaborating with teams to innovate solutions.

Design and oversee deployment of data architecture, manage structured and unstructured data, and develop tools using AI and machine learning.

The VP of AI and Innovation will define and lead the AI strategy at BeOne Medicine, focusing on innovation, data management, and organizational enablement in healthcare. They will mentor teams and engage stakeholders to drive AI adoption and ensure alignment with business objectives.

Design, build, and improve recommender systems and ML tooling; take models from ideation to production; optimize models and data pipelines; integrate ML into backend systems to drive product personalization.

Develop and optimize unimodal and multimodal perception models for 3D/BEV terrain and surface inference, build large-scale data pipelines and annotation tools, deploy and optimize models on edge compute, collaborate with robotics/software/hardware teams, mentor juniors, and translate research into production-grade autonomous vehicle perception systems.