Top AI & Machine Learning Jobs

Develops data pipelines, curates and analyzes large datasets, builds quantitative models, validates data and results, and deploys analytics solutions with product teams. Responsibilities include discovering useful datasets, ensuring data quality and reliability, supporting customer-driven requirements, and integrating solutions into interconnected systems. The role requires strong Python and data-handling skills, database expertise, large-scale batch processing experience, and U.S. citizenship.

Build and deploy production machine learning applications, APIs, inference services, and data platforms. Engineer large-scale pipelines using distributed technologies, data modeling, ETL/ELT, transformation, and data quality practices. Translate defense and mission needs into scalable solutions across cloud, containerized, and GPU/CPU environments while collaborating with engineering, data, and mission teams.

Leads architecture, development, and delivery of AI-powered applications and enterprise data platforms. Designs Generative AI solutions using LLMs, agents, RAG, and Vertex AI; develops full-stack cloud-native applications; builds Databricks, Spark, and Lakehouse data architectures; and establishes GCP cloud standards. Provides technical leadership, mentoring, architecture guidance, governance, observability, CI/CD practices, technical evaluations, and technology roadmaps across engineering, data, analytics, and product teams.

Build and operate scalable ML infrastructure and platform capabilities across cloud and on-premises environments. Develop Python-based developer tooling, services, and production systems supporting experimentation, distributed training, model deployment, and operations. Lead complex initiatives from architecture through rollout, improve reliability and developer productivity, and partner with ML and infrastructure teams. The role emphasizes Kubernetes, AWS, distributed compute, GPU-intensive workloads, observability, and production excellence.

Leads enterprise AI and intelligent automation strategy, including Generative AI, machine learning, and RPA initiatives. Manages a multidisciplinary IT team, budgets, vendors, governance, project portfolios, and end-to-end solution delivery. Partners with business and technology leaders to identify automation opportunities, develop business cases, ensure compliance and security, and deliver scalable solutions with measurable business value. The role is hybrid in Camden, New Jersey, with 15% domestic and international travel.

Leads the end-to-end design, deployment, and performance of real-time ML prediction and bid-optimization systems for programmatic advertising. Provides hands-on technical leadership to applied scientists and ML engineers, formulates optimization problems, manages production ML challenges such as latency, delayed feedback, drift, and retraining, and aligns technical roadmaps with business priorities.

Develop and deploy production-ready AI models, agentic applications, and RAG systems for investment and business use cases. Build data pipelines, optimize AI performance, and manage cloud-based deployments. Partner with stakeholders to gather requirements, shape AI product roadmaps, and deliver measurable value. Research emerging AI methods, establish best practices, mentor junior team members, and lead internal training.

Develop statistical and machine learning models using soccer tracking and event data to support player recruitment decisions. Build spatio-temporal models, metrics, analyses, and interpretation tools; validate models; communicate findings to professional club clients; and partner with engineering on cloud deployment and production reliability. The role also includes code review, model maintenance, and advancing analytical methods.

Partner with enterprise customers to identify AI use cases, architect and implement custom applications and integrations using WRITER’s platform, APIs, and Knowledge Graph. Translate complex AI concepts into actionable solutions, collaborate with Product and Engineering, improve technical integration processes, and drive customer adoption, time-to-value, and measurable business outcomes.

Develop and deploy large-scale computer vision and machine learning models for Coupang’s search and product experiences. Responsibilities include experimentation, statistical analysis, scalable model development and serving, A/B testing, researching advanced vision techniques, presenting results to leadership, and mentoring engineers. The role requires applying deep learning, transformers, generative modeling, and other state-of-the-art approaches to user-facing products.