Top AI & Machine Learning Jobs

Lead the PK/PD consulting services, guide the adoption of AI solutions, and establish processes for a new services organization. Collaborate with teams, mentor talent, and represent InsightRx in scientific forums.

Lead hands-on automation and AI development for HR by mapping processes, identifying automation/AI opportunities, designing intelligent workflows and agents, deploying solutions, monitoring performance, and driving change management and adoption across HR teams.

Work with the machine learning team and portfolio managers to translate investment questions into ML problems, develop and evaluate data-driven models (including simulation and optimization), maintain production models and tools, document methods and results, and stay current with ML/AI techniques relevant to finance. Gradually take ownership of features, components, and end-to-end projects.

Design, train, evaluate, optimize, and deploy production ML models including recommendation, ranking, personalization, and adaptive decision systems. Apply reinforcement learning, contextual bandits, offline policy evaluation, causal inference, and experimentation to improve creator-facing products. Build scalable training, evaluation, deployment, and inference pipelines; work with logged interaction data; collaborate with Product, Engineering, and Analytics to translate customer problems into production ML solutions.

Develop, optimize, and deploy computer vision models (object detection, tracking, segmentation, facial recognition). Prepare and preprocess large image/video datasets, evaluate and monitor model performance in production, and collaborate with cross-functional teams to integrate scalable vision AI solutions.

The candidate will develop and enhance AI services for nonprofits by selecting appropriate platforms, mentoring consultants, and guiding project teams through the implementation of AI solutions.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

As a Research Scientist, design and execute R&D strategies to enhance LLM agent technologies, prototype context management, and publish findings.

Conduct applied research on user representation learning, transformers, and generative AI; build and deploy large-scale embedding, retrieval, and semantic search systems; collaborate with engineering and product teams to productionize models and run rigorous evaluations.

Build and improve production AI/data pipelines, design model evaluation workflows and Jupyter analyses, add observability to AI systems, experiment with models/retrieval/prompt architectures, integrate and abstract AI APIs, and help define inference serving, fine-tuning, and dataset-generation infrastructure.