Top AI & Machine Learning Jobs

Develops and leads data science initiatives using structured and unstructured data to create machine learning and statistical models. Translates client requirements into analytical solutions, develops features and algorithms, validates models, and guides analytical development teams. The role also involves applying AI and machine learning to complex government and intelligence challenges, with potential integration of analytics into production systems.

Design and implement AI/ML solutions for cyber and intelligence workflows, including LLM-powered workflows, agent-based automation, and API or enterprise data integrations. Partner with mission users, analysts, developers, and leadership to document operational processes, build reliable production capabilities, and meet classified-environment security and governance requirements.

Leads the delivery, integration, adoption, and scaling of AI-powered solutions across the firm. Translates AI strategy into production workflows, automation systems, enterprise integrations, and measurable business outcomes. Oversees technical implementation, vendors, delivery roadmaps, governance, change management, training, and continuous improvement. Partners with technology, data, and business teams to embed AI into workflows and improve productivity, client experience, and operational efficiency.

Designs and deploys secure, scalable AI solutions and autonomous workflows. Partners with stakeholders to translate business needs into technical requirements, leads end-to-end AI service delivery, develops integrations and complex AI pipelines, applies MLOps practices, manages cross-functional relationships, and connects technical outcomes to measurable business ROI. Requires working onsite at the client office in Basking Ridge, New Jersey, three days per week.

Research and evaluate AI and machine learning models for orthopedic, wound care, and sports medicine products. Clean and structure datasets, design feature encodings, develop and train models, validate performance using statistical methods, and create interfaces for model exploration. The role collaborates within a multidisciplinary R&D environment and requires strong programming, data science, statistical analysis, and communication skills.

Lead cross-functional teams delivering production-grade AI, machine learning, and generative AI solutions. Define technical product vision, roadmaps, architectures, engineering standards, and operational strategies while evaluating designs, managing model lifecycle needs, and ensuring security, governance, compliance, scalability, responsible AI, and auditability. Translate business objectives into feasible AI/ML solutions, measure business value, mentor colleagues, and coordinate engineering, research, risk, technology, and platform stakeholders.

Six-to-nine-month R&D co-op integrating data science and analytics into paint development. The role involves collaborating with chemists and scientists, completing technical data science projects, creating data visualizations, supporting digital initiatives, and presenting project outcomes. Participants also engage in performance reviews, networking, learning events, and cross-functional teamwork. The position is fully onsite in Brecksville, Ohio, and requires a background check.

Build and scale Surgo’s Python-based AI interview engine, including survey execution, LLM interviewer behavior, APIs, data models, integrations, and Azure infrastructure. Own PostgreSQL migrations, reliability, observability, testing, CI/CD, security, privacy, and compliance for sensitive participant data. Collaborate with product, research, frontend, and data teams while delivering features independently in a remote, cross-functional environment.

Performs technical targeting analytics using ECL, HPCC, and complementary programming languages. Develops and validates methodologies for large-scale parallel processing in clustered computing environments, manipulates structured and unstructured data, performs data modeling, and produces mission-relevant analytic reporting for national security missions.

Develops and applies data science methodologies for large-scale parallel processing in clustered computing environments. The role uses ECL, HPCC, and programming languages such as Python, C, and SQL to model, analyze, and manipulate high-volume structured and unstructured data. Responsibilities include technical targeting analytics, data modeling, analytic validation, and producing mission-relevant reporting for national security missions.

Analyze large datasets to generate business and research insights for national security customers. Develop NLP, text classification, topic modeling, semantic search, and generative language model solutions using Python and deep learning frameworks. Perform statistical analysis, model evaluation, data collection, visualization, and SQL-based data extraction. Communicate methodology and findings to senior leadership, build API and database integrations, support cloud applications, and tune LLMs for mission-specific use cases.

Develop and deploy scalable AI applications and machine learning models using Python, Spark, Azure, and OpenAI. Responsibilities include requirements analysis, software development lifecycle participation, pipeline development, testing, deployment, troubleshooting, documentation, and production support. The role collaborates with data, software, and business teams to deliver data-driven solutions, while applying version control, CI/CD, and software engineering best practices.

Develop and deploy machine learning and LLM-based solutions for cybersecurity challenges. Responsibilities include analyzing complex datasets, building classification and NLP models, optimizing prompting, embeddings, RAG, and fine-tuning techniques, designing evaluation methodologies, and integrating models into scalable production systems. The role requires collaboration with cybersecurity researchers, software engineers, data engineers, and product managers.